Meteorological elements of the dataset include the near-surface land-air exchange parameters, such as downward/upward longwave/shortwave radiation flux, momentum flux, sensible heat flux, latent heat flux, etc. In addition, the vertical distributions of 3-dimensional wind, temperature, humidity, and pressure from the surface to the tropopause are also included. Independent evaluations were conducted for the dataset by comparison between the observational data and the most recent ERA5 reanalysis data. The results demonstrate the accuracy and superiority of this dataset against reanalysis data, which provides great potential for future climate change research.
LI Fei, Ma Shupo, ZHU Jinhuan, ZOU Han , LI Peng , ZHOU Libo
Numerical experiments: The climate model used is the fast air sea coupling model (FAMOUS) jointly developed by the British Meteorological Office and British universities The horizontal resolution of the atmospheric model in the FAMOUS model is 5 ° × 7.5 °, 11 layers in vertical direction; The horizontal resolution of the ocean model is 2.5 ° × 3.75 °, 20 layers in vertical direction The atmosphere and ocean are coupled once a day without flux adjustment The tests included the Middle Paleocene (MP,~60Ma BP, test name flat_60ma_1xCO2_sea_3d_ * * 100yr_mean. nc) and the Late Oligocene (LO,~25Ma BP, test name orog_25ma_1xCO2_sea_3d_ * * 100yr_mean. nc) The sea land distribution data is mainly taken from the global coastline basic data set (abbreviated as Gplates, website: http://www.gplates.org/ ）Considering that the initial uplift of Cenozoic terrains such as the Qinghai Tibet Plateau started at about 50~55 Ma (Searle et al., 1987), the global terrain height was set to 0 in the MP test to omit the role of plateau terrain. At 25 Ma, Greenland (Zachos et al., 2001) and the Qinghai Tibet Plateau (for example, Wang et al., 2014; Ding et al., 2014; Rowley and Currie, 2006; DeCells et al., 2007; Polisar et al., 2009) were revised The change of ancient latitude is also considered when reconstructing the ancient topography of the Qinghai Tibet Plateau (Besse et al., 1984; Chatterjee et al., 2013; Wei et al., 2013) At the same time, referring to the change of Cenozoic atmospheric CO2 (Beerling and Royer, 2011), the atmospheric CO2 concentration in the two periods of experiments was 280 ppmv (1 ppmv=1 mg L – 1) before the industrial revolution For simplicity, all land vegetation and soil properties are set to globally uniform values, that is, various land surface properties on each land grid point except Antarctica are assigned to the global average value of non glacial land surface before the industrial revolution, which is also convenient for highlighting the impact of land sea distribution and topographic changes In addition, since we mainly discuss the average climate state and its change in the characteristic geological period on the scale of millions of years, we can omit the influence of orbital forcing, that is, the Earth's orbital parameters are set to their modern values in all experiments Output time: All tests were integrated for 1000 years, using the average results of the last 100 years of each test. This data is helpful to explore the formation and evolution mechanism of the Cenozoic monsoon and drought.
LIU Xiaodong
This data set is the daily vorticity related flux observation data of Naqu flux station (31.64 ° N 92.01 ° E, 4598 m a.s.l.), including ecosystem net ecosystem productivity (NEP), total primary productivity (GPP) and ecosystem respiration (ER) data. The main steps of data pre-processing include wild point removal (± 3 σ）、 Coordinate axis rotation (3D wind rotation), Webb Pearman Leuning correction, outlier elimination, carbon flux interpolation and decomposition, etc. Missing data are interpolated through the nonlinear empirical formula between CO2 flux value (Fc) and environmental factors.
ZHANG Yangjian
This dataset is the daily vorticity related flux observation data of Naqu flux station (31.64 ° N 92.01 ° E, 4598 m a.s.l.), including net ecosystem productivity (NEP), total primary productivity (GPP), ecosystem respiration (ER), evapotranspiration, latent heat, sensible heat, air temperature, relative humidity, wind speed, soil temperature, soil moisture and other data. The main steps of data pre-processing include wild point removal (± 3 σ）、 Coordinate axis rotation (3D wind rotation), Webb Pearman Leuning correction, outlier elimination, carbon flux interpolation and decomposition, etc. Missing data are interpolated through the nonlinear empirical formula between CO2 flux value (Fc) and environmental factors.
ZHANG Yangjian
This data set is the data set of water balance (precipitation, evapotranspiration, runoff, liquid soil moisture) and energy balance (short wave radiation, sensible heat, latent heat and surface soil temperature) for the source of the Yellow River and the Qilian Mountains over the past 40 years. The initial data source is ERA5 Land monthly average data, which is accumulated/averaged to the annual scale through time aggregation. The time range of the data is 1981-2020, the spatial range is 88.5 ° E – 104.5 ° E, 32 ° N – 43 ° N, and the spatial resolution is 0.1 °. The data set can be further used to study the ecological hydrological processes in the source area of the Yellow River and the Qilian Mountains, and provide scientific basis for the optimal allocation of the "mountains, rivers, forests, fields, lakes and grasses" system.
ZHENG Donghai
This data set is the conventional meteorological observation data of Maqu grassland observation site in the source region of the Yellow River from 2017 to 2020, obtained by using Kipp&Zonen CNR4, Vaisala HMP155A, PTB110 and other instruments, with a time resolution of half an hour. Mainly include wind speed, wind direction, temperature, relative humidity, air pressure, downward short-wave radiation, downward long-wave radiation, precipitation.
MENG Xianhong, LI Zhaoguo
This data set is the conventional meteorological observation data of the Ngoring Lake Grassland Observation site (GS) in the source region of the Yellow River from 2017 to 2020, obtained by using Kipp&Zonen CNR4, Vaisala HMP155A, PTB110 and other instruments, with a time resolution of half an hour. Mainly include wind speed, wind direction, temperature, relative humidity（specific humidity in 2020）, air pressure, downward short-wave radiation, downward long-wave radiation, precipitation.
MENG Xianhong, LI Zhaoguo
Normalized Difference Vegetation Index (NDVI) has been widely used for monitoring vegetation. This dataset employed all available Landsat 5/7/8 data on the Qinghai-Tibetan Plateau (QTP) (> 100,000 scenes), and reconstructed high spatiotemporal NDVI time-series data (30-m and 8-d) during 2000-2020 on the TP (QTP-NDVI30) by using the MODIS-Landsat fusion algorithm (gap filling and Savitzky–Golay filtering；GF-SG). For the details of GF-SG, please refer to Chen et al. (2021). This dataset has been evaluated carefully. The quantitative assessments show that the reconstructed NDVI images have an average MAE value of 0.02, correlation coefficient of 0.96, and SSIM value of 0.94. We compared the reconstructed images in some typical areas with the PlanetScope 3-m images and found that the spatial details were well preserved by QTP-NDVI30. The geographic coordinate system of this dataset is GCS_WGS_84. The spatial range covers the vegetation area of the QTP, which is defined as the areas with average NDVI during July- September larger than 0.15.
CAO Ruyin , XU Zichao , CHEN Yang , SHEN Miaogen , CHEN Jin
This data is the debris flow risk assessment data obtained from the analysis and Research on the debris flow disaster in the China Pakistan Economic Corridor, and the data source is the risk and vulnerability analysis results obtained from this study; The research method is based on the risk expression given by the United Nations Department of Humanitarian Affairs (1992): risk = hazard × Vulnerability, risk analysis of debris flow disaster in the study area.. The purpose of this data is to assess the risk of debris flow disaster in the China Pakistan Economic Corridor, understand the relationship between the intensity of major debris flow risk, and provide scientific guidance for the decision-making of local government departments in disaster prevention and mitigation and urban governance.
SU Fenghuan
This data is the debris flow risk assessment data obtained from the analysis and Research on the debris flow disaster in the China Pakistan Economic Corridor, and the data source is the risk and vulnerability analysis results obtained from this study; The research method is based on the risk expression given by the United Nations Department of Humanitarian Affairs (1992): risk = hazard × Vulnerability, risk analysis of debris flow disaster in the study area.. The purpose of this data is to assess the risk of debris flow disaster in the China Pakistan Economic Corridor, understand the relationship between the intensity of major debris flow risk, and provide scientific guidance for the decision-making of local government departments in disaster prevention and mitigation and urban governance.
SU Fenghuan
This data is the debris flow risk assessment data, which is obtained from the analysis and research of the debris flow disaster in the China Pakistan Economic Corridor. The sample data of debris flow is the detailed data of debris flow disaster through remote sensing interpretation and on-site verification. A risk assessment system is established to evaluate the debris flow risk in the study area by using the information method, and then the risk area is divided by using the natural breakpoint method. This data can be used to assess the risk of major debris flow disasters, understand the relationship between the risk degree of major debris flow, and provide scientific guidance for the decision-making of local government departments in disaster prevention and mitigation and urban governance.
SU Fenghuan
This dataset includes the schematic diagrams and lithologic histograms of the measured sections of typical unconsolidated sediments in Shigatse, Yarlung Tsangpo River Basin, as well as the statistical table of measured sections. The source data comes from a two-month field measurement in Shigatse, Tibet. 16 sections of unconsolidated sediments were measured, and 128 samples were collected, including 89 cosmic nuclide samples and 39 optically stimulated luminescence samples. 16 schematic diagrams and 38 lithologic histograms were shown. The dataset primarily shows the genetic types of typical unconsolidated sediments in the Shigatse area, such as alluvium, eluvium, diluvium, colluvium, and moraine deposits. The exposed range of measured sediment thickness is about 1.6–70 m, the average thickness is about 29 m, and the horizontal distribution is 41–9059 m. The dataset demonstrates the discrete, porous, sandy and weakly cemented structural characteristics of the unconsolidated sediments with high gravel content (80%–95%), and the main gravel diameter distribution is 0.05–0.1m; sorting and roundness of alluvium are good, while the colluvial materials are poor. Fining-upward trends are commonly seen in most sections, and parallel and tabular cross-bedding are occasionally developed. Untangling the sedimentary characteristics of unconsolidated sediments in the Yarlung Tsangpo River Basin is vital to reveal the storage of fluvial solid matter across the basin, and provide important instructions for disaster warning and prevention and control of related features caused by sliding, unloading, and collapse of the ground surface. It is also of great scientific value to reveal the source-sink process and evolution of fluvial and alluvial systems in the Tibet Plateau and its surrounding basins.
LIN Zhipeng, WANG Chengshan , HAN Zhongpeng, BAI Yalige, WANG Xinhang, ZHANG Jian, MA Xinduo
Focusing on the objective of estimating the total amount of unconsolidated sediments in the Yarlung Tsangpo River Basin (YTRB), we marked a series of Quaternary sections of unconsolidated sediments in the whole basin to measure their thickness. The dataset presents a collection of field photos of unconsolidated sediments obtained in the scientific expedition in YTRB in 2020. Specifically, this dataset comprises of 16 composite first–class sub basins, from upstream to downstream, including Dangque–Laiwu Tsangpo, Resu–Lierong Tsangpo, Chaiqu–Menqu, Xiongqu–Wengbuqu, Jiada Tsangpo, Pengji Tsangpo–Sakya Chongqu, Duoxiong Tsangpo, Shabu–Danapu, Nianchu River, Xiangqu–Wuyuma, Manqu, Nimuma–Lhasa River, Gonggapu–Luoburongqu, Niyang River, Yigong Tsangpo–Palong Tsangpo, and Xiangjiang River Basin. A total of 584 sites of unconsolidated sediments were marked. The atlas displays different types of unconsolidated sediments, such as alluvium, eluvium, diluvium, colluvium, eolian, lacustrine and moraine deposits, showing their spatial distribution in hillsides, foothills, floodplains, terraces, alluvial–diluvial fans and glacier fronts. With a scale of 1m benchmarking, it shows the significant difference in distribution of thickness. Generally, the thickness of the eluvium on the upper part of the hillside is about 0.3–2.5m, and the thickness of the alluvium is difficult to bottom out. The thickness of diluvium in the gentle area of the piedmont with steep slope is usually between 5 and 10 m, while the thickness of the deposit at the piedmont gully mouth is related to the scale of the pluvial fan, which can reach tens of meters thick and only 3 to 4 meters thin. From the upstream to the downstream, the thickness of alluvium varies greatly. The bedrock in the canyon area is exposed, and the thickness is almost 0. However, the thickness of alluvium in the upstream river valley is large and difficult to see the bottom interface; The maximum thickness of measured moraine deposits can reach more than 20 m. Aeolian deposits are common in the middle and upper reaches, with a wide range of thickness, ranging from a few meters to more than 20 meters. The dataset provides a wide variety of in–suit photos and measurements of unconsolidated sediments covering the whole basin, showing their characteristics of spatial distribution and genetic types, which lays a material foundation and prior knowledge for further detailed characterization and investigation of unconsolidated sediments. This work presents data for estimating the total accumulation of solid debris deposited in the YTRB, and provides a basis for assessing the risk of natural disasters related to unconsolidated sediments and formulating scientific preventive measures.
LIN Zhipeng, WANG Chengshan , HAN Zhongpeng, BAI Yalige, WANG Xinhang, HU Taiyu
The considerable amount of solid clastic material in the Yarlung Tsangpo River Basin (YTRB)) is one of the important components in recording the uplift and denudation history of the Tibet Plateau. Different types of unconsolidated sediments directly reflect the differential transport of solid clastic material. Revealing its spatial distribution and total accumulation plays an important value in the uplift and denudation process of the Tibet Plateau. The dataset includes three subsets: the type and spatial distribution of unconsolidated sediments in theYTRB, the thickness spatial distribution, and the quantification of total deposition. Taking remote sensing interpretation and geological mapping as the main technical method, the classification and spatial distribution characteristics of unconsolidated sediments in the whole YTRB (16 composite sub-basins) were comprehensively clarified for the first time. Based on the field measurement of sediment thickness, the total accumulation was preliminarily estimated. A massive amount of sediment is an important material source of landslide, debris flow and flood disasters in the basin. Finding out its spatial distribution and total amount accumulation not only has theoretical significance for revealing the key information recorded in the process of sediment source to sink, such as surface environmental change, regional tectonic movement, climate change and biogeochemical cycle, but also has important application value for plateau ecological environment monitoring and protection, flooding disaster warning and prevention, major basic engineering construction, and soil and water conservation.
LIN Zhipeng, WANG Chengshan , HAN Zhongpeng, BAI Yalige, WANG Xinhang, ZHANG Jian, MA Xinduo, HU Taiyu, ZHANG Chenjin
This data provides the distribution of debris flows in the China-Pakistan Economic Corridor and the Tianshan Mountains by 2021. Based on historical data collection, field surveys and interpretation of remote sensing images, combined with digital topographic maps (DEM) and geological maps, the latest China-Pakistan economic The debris flow distribution data of the corridor (foreign section) has good reliability of data information, and the data can be used as the basic data for debris flow distribution law, debris flow risk, and risk calculation. The extraction of the debris flow basin mainly adopts the hydrological analysis method in ArcGIS, taking into account the accuracy limitation of DEM, combined with Google Earth images to perform necessary manual correction.
SU Fenghuan
This data is the material physical property data of the typical debris flow trenches of G217 and G30, the main traffic roads in the Tianshan area. This data is the detailed information of the typical debris flow disaster points in the study area, including watershed parameters, channel parameters, and debris flow accumulation material physical parameters; these data can be Combined with the rainfall data, the research contents such as the rainfall threshold of debris flow activities in this area can be further carried out. Including the area of the debris flow basin, the width of the ditch, the length of the ditch, the vertical gradient, the area of the glacial lake, and the physical properties of the debris flow deposits. The physical property data of the accumulation were obtained by experimental equipment such as a laser particle size analyzer, and the saturated permeability coefficient was obtained by a triaxial experiment.
CHEN Ningshen
Based on the compilation of major mountain torrent disaster cases from 1840 to 2019, this data is the mountain torrent disaster investigation data along the Sichuan Tibet railway, including time, location, disaster type, cause, longitude, latitude, rainfall, railway section and disaster loss information. According to the characteristics of different data sources such as investigation and compilation of historical flood data in China, national mountain flood disaster prevention and control project (2013-2015), mountain flood disaster investigation results and field investigation in Sichuan Province and Tibet Autonomous Region, the authenticity and consistency of the original data are checked and standardized; Then analyze, sort and summarize according to the data source and data; Finally, the use of SuperMap software for processing.
WANG Zhonggen
Four point bending failure tests (bending failure and shear failure of pure reinforced anti slide pile; bending failure and shear failure of prestressed anti slide pile) were carried out on four anti slide piles with different structures, and the whole failure process was monitored by acoustic emission. The monitoring equipment is the German eight channel vallen acoustic emission monitor, and seven sensors are arranged to monitor the damage of piles in the whole area. The collected AE data mainly include amplitude, energy, ring count, frequency and other key AE indicators. By studying the characteristics of acoustic emission signals in the whole process, we can get the acoustic emission characteristics of anti slide piles in different stages and different failure forms, establish the damage model, and provide a feasible scheme for the prediction and early warning of structural failure.
JIANG Qinghui
1) In mountainous areas, due to the complex topographic and geological background conditions, landslides are very easy to occur triggered by external factors such as rainfall, snow melting, earthquake and human engineering activities, resulting in the loss of life and property and the destruction of the natural environment. In order to meet the safety of project site construction, the rationality of land use planning and the urgent needs of disaster mitigation, it is necessary to carry out regional landslide sensitivity evaluation. When many different evaluation results are obtained by using a variety of different methods, how to effectively combine these results to obtain the optimal prediction is a technical problem that is still not difficult to solve at present. It is still very lack in determining the optimal strategy and operation execution of the optimal method for landslide sensitivity evaluation in a certain area. 2) Using the traditional classical multivariate classification technology, through the evaluation of model results and error quantification, the optimal evaluation model is combined to quickly realize the high-quality evaluation of regional landslide sensitivity. The source code is written based on the R language software platform. The user needs to prepare a local folder separately to read and store the software operation results. The user needs to remember the folder storage path and make corresponding settings in the software source code. 3) The source code designs two different modes to display the operation results of the model. The analysis results are output in the standard format of text and graphic format and the geospatial mode that needs spatial data and is displayed in the standard geographic format. 4) it is suitable for all people interested in landslide risk assessment. The software can be used efficiently by experienced researchers in Colleges and universities, and can also be used by government personnel and public welfare organizations in the field of land and environmental planning and management to obtain landslide sensitivity classification results conveniently, quickly, correctly and reliably. It can serve regional land use planning, disaster risk assessment and management, disaster emergency response under extreme induced events (earthquake or rainfall, etc.), and has great practical guiding significance for the selection of landslide monitoring equipment and the reasonable and effective layout and operation of early warning network. It can be popularized and applied in areas with serious landslide development
YANG Zhongkang
The data set is the watershed scale erosion rate of the eastern Tibet Based on 10Be. The data includes the first author, publication year, longitude and latitude and erosion rate. The data were collected in published journal articles, and the data has significant spatial distribution characteristics, and different research results are consistent with each other. The spatial characteristics of basin-wide erosion rate are always related to river geomorphic characteristics (such as steepness), climate and tectonic activities. Therefore, the systematic data set can provide important data support for the analysis of the main controlling factors of regional erosion rate , making it possible to quantify the contribution of climate and structure to the surface process in the region.
ZHANG Huiping
1) Data content: this data set is the landslide disaster data of Sanjiang Basin in the southeast of Qinghai Tibet Plateau; 2) Data source and processing method: this data set was independently interpreted by Dai Fuchu of Beijing University of technology using Google Earth; This data file is finally formed by remote sensing interpretation - on-site verification - re interpretation - re verification and other methods after 7 systematic interpretation. More than 5000 landslides have been verified on site with high accuracy; 4) This data has broad application prospects for hydropower resources development, traffic engineering construction and geological disaster evaluation in the three river basins in the southeast of Qinghai Tibet Plateau.
DAI Fuchu
The thematic map of comprehensive zoning of multi disaster susceptibility shows the spatial distribution of multi disaster susceptibility and the combination mode of disaster types in the region. It is composed of geological disaster susceptibility, earthquake disaster susceptibility, frozen soil freeze-thaw disaster susceptibility and rainstorm flood disaster susceptibility. The data is mainly generated by the calculation of remote sensing data input susceptibility evaluation model. The input data includes disaster cataloging, landform data, climate data and geological data. The data mainly includes a thematic map and the prone grid and vector data (. SHP) used for mapping. The grid size of grid data (. TIF) is 0.01 degrees, about 1200m. The data will provide reference for the development planning of the Qinghai Tibet Plateau.
TANG Chenxiao, ZHANG Guoming, LIU Lianyou
The disaster catalogue of the Qinghai Tibet Plateau contains the spatial distribution and type information of various historical disasters, ranging from Pakistan and Kashmir in the west, Qinghai Province in the East, the foothills of the Himalayas in the South and Arkin mountain in the north. The production of data is completed by a large number of manual remote sensing interpretation, field investigation, collection of geological survey data and open source data. The data is stored in the form of vector points, mainly including attribute table, indicating disaster type, coordinates and other information. This data can be used to study the spatial distribution law of disasters and disaster evaluation. This data contains a total of 23536 pieces of data. Due to the reference of geological survey data, most of the debris flow data are distributed along the road, and there are few data in no man's land.
TANG Chenxiao
According to the task assignment, the research group of "research and development of key technologies and equipment for monitoring and early warning of debris flow in complex mountainous areas" developed a prototype of multi index intelligent early warning and monitoring equipment for debris flow disasters such as mud water level and ground sound, and carried out demonstration application of the prototype in Guxiang gully, Tianmo gully and Peilong gully along G318 National Highway in Bomi County, Nyingchi City, Tibet in October 2019. The data submitted are the original data collected by the debris flow professional monitoring equipment deployed in Guxiang gully, Tianmo gully and Peilong gully, including the monitoring data of geoacoustic equipment, rainfall and mud water level. The monitoring data of professional equipment submitted by the Institute provides a technical guarantee for the research on the evolution characteristics of the breeding, development and formation stages of debris flow disasters in Guxiang gully, Tianmo gully and Peilong gully to a certain extent.
DONG Hanchuan , GUO Wei
The dataset of soil evaporation in the middle and lower Heihe River Basin at the north of Qilian Mountains (2001-2015) is stimulated by the Hydrological-Ecological Integrated watershed Flow Model (HEIFLOW). HEIFLOW is a three-dimensional distributed eco-hydrological coupling model, integrating the Precipitation-Runoff Modeling System (PRMS) with the Modular Groundwater Flow Model (MODFLOW) and several ecological modules, which can completely describe the hydrological cycle and vegetation ecological process of the basin. For the modeling details of generating this data, please refer to Han et al. (2021), and for the technical details of HEIFLOW model, please refer to Han et al. (2021), Tian et al. (2018), and sun et al. (2018)
ZHENG Yi , HAN Feng , TIAN Yong
The dataset of leaf area index in the middle and lower Heihe River Basin at the north of Qilian Mountains (2001-2015) is stimulated by the Hydrological-Ecological Integrated watershed Flow Model (HEIFLOW). HEIFLOW is a three-dimensional distributed eco-hydrological coupling model, integrating the Precipitation-Runoff Modeling System (PRMS) with the Modular Groundwater Flow Model (MODFLOW) and several ecological modules, which can completely describe the hydrological cycle and vegetation ecological process of the basin. For the modeling details of generating this data, please refer to Han et al. (2021), and for the technical details of HEIFLOW model, please refer to Han et al. (2021), Tian et al. (2018), and sun et al. (2018)
ZHENG Yi , HAN Feng , TIAN Yong
The dataset of available soil water content in the middle and lower Heihe River Basin at the north of Qilian Mountains (2001-2015) is stimulated by the Hydrological-Ecological Integrated watershed Flow Model (HEIFLOW). HEIFLOW is a three-dimensional distributed eco-hydrological coupling model, integrating the Precipitation-Runoff Modeling System (PRMS) with the Modular Groundwater Flow Model (MODFLOW) and several ecological modules, which can completely describe the hydrological cycle and vegetation ecological process of the basin. For the modeling details of generating this data, please refer to Han et al. (2021), and for the technical details of HEIFLOW model, please refer to Han et al. (2021), Tian et al. (2018), and sun et al. (2018)
ZHENG Yi , HAN Feng , TIAN Yong
The dataset of vegetation transpiration in the middle and lower Heihe River Basin at the north of Qilian Mountains (2001-2015) is stimulated by the Hydrological-Ecological Integrated watershed Flow Model (HEIFLOW). HEIFLOW is a three-dimensional distributed eco-hydrological coupling model, integrating the Precipitation-Runoff Modeling System (PRMS) with the Modular Groundwater Flow Model (MODFLOW) and several ecological modules, which can completely describe the hydrological cycle and vegetation ecological process of the basin. For the modeling details of generating this data, please refer to Han et al. (2021), and for the technical details of HEIFLOW model, please refer to Han et al. (2021), Tian et al. (2018), and sun et al. (2018)
ZHENG Yi , HAN Feng , TIAN Yong
Climatic warming alters the onset, duration and cessation of the vegetative season. While prior studies have shown a tight link between thermal conditions and leaf phenology, less is known about the impacts of phenological changes on tree growth. Here, we assessed the relationships between the start of the thermal growing season (TSOS) and tree growth across the extratropical Northern Hemisphere using 3451 tree-ring chronologies and daily climatic data for 1948-2014. An earlier TSOS promoted growth in regions with high ratios of precipitation to temperature but limited growth in cold dry regions. Path analyses indicated that an earlier TSOS enhanced growth primarily by alleviating thermal limitations on wood formation in boreal forests and by lengthening the period of growth in temperate and Mediterranean forests. Semi-arid and dry subalpine forests, however, did not benefit from an earlier onset of growth and a longer growing season, presumably due to associated water loss and/or more frequent early spring frosts. These broadly relevant patterns of how climatic impacts on wood phenology affect tree growth at regional to hemispheric scales, enhance our understanding of how future phenological changes may affect the carbon sequestration capacity of extra-tropical forest ecosystems.
LIANG Eryuan, GAO Shan
This dataset is the water balance dataset in the Yellow River source region and Qilian Mountains in the future 50 years (runoff, precipitation, evapotranspiration, soil liquid water content). It is simulated by the Geomorphology-Based Ecohydrological Model (GBEHM). The variables in the dataset include monthly runoff, monthly precipitation, monthly evapotranspiration, the monthly average 5cm soil liquid water content and the monthly average 50cm soil liquid water content. The temporal range is 2020-2070 and the spatial resolution is 1 km. The input data of the model include meteorological forcings, vegetation, soil and land use data, and the meteorological forcings are obtained from the ensemble mean of 38 CMIP6 models under SSP2-4.5 scenario. The simulation results can reflect the spatio-temporal changes of the hydrological variables in the Yellow River source region and Qilian Mountains. The dataset can be further used for researches into the eco-hydrological processes in the Yellow River source region and Qilian Mountains, and help provide a scientific basis for the optimal allocation of " mountains, rivers, forests, farmlands, lakes and grasslands " system.
WANG Taihua, YANG Dawen
This dataset is the water balance dataset in the Yellow River source region and Qilian Mountains in the past 40 years (runoff, precipitation, evapotranspiration, soil liquid water content). It is simulated by the Geomorphology-Based Ecohydrological Model (GBEHM). The variables in the dataset include monthly runoff, monthly precipitation, monthly evapotranspiration, the monthly average 5cm soil liquid water content and the monthly average 50cm soil liquid water content. The temporal range is 1980-2019 and the spatial resolution is 1 km. The input data of the model include meteorological forcings, vegetation, soil and land use data. The simulation results can reflect the spatio-temporal changes of the hydrological variables in the Yellow River source region and Qilian Mountains. The dataset can be further used for researches into the eco-hydrological processes in the Yellow River source region and Qilian Mountains, and help provide a scientific basis for the optimal allocation of " mountains, rivers, forests, farmlands, lakes and grasslands " system.
WANG Taihua, YANG Dawen
1) Data content It includes the observation year, latitude and longitude, altitude, ecosystem type and soil layer (soc0-100 (kgcm-2); 0-100 represents soil layer), underground biomass content. 2) Data sources This part of the data is obtained from the literature, specific literature sources refer to the documentation. 3) Data quality description The data cover a wide range, including comprehensive indicators, showing the content of soil organic carbon under different soil layers, with high integrity and accuracy, which can meet the estimation of soil carbon storage of grassland in Qinghai Tibet Plateau. 4) Data application achievements and Prospects It provides basic data for predicting the carbon source sink effect of soil and realizing the sustainable development of ecosystem carbon in the future.
HU Zhongmin
1) Data content It includes the observation year, longitude and latitude, ecosystem type, annual rainfall, drought index, annual net primary productivity, aboveground biomass, underground biomass and other data. 2) Data sources One part is from literature (1980-1995), the other part is from field sampling (2005-2006). 3) Data quality description The data has a long observation year, a large time span, a wide coverage, and many indicators, which has high integrity and accuracy, and can meet the estimation of grassland carbon storage in the Qinghai Tibet Plateau. 4) Data application achievements and Prospects It provides basic data for predicting the carbon source sink effect and realizing the sustainable development of ecosystem carbon in the future.
HU Zhongmin
The data set is based on the NBP simulated by 16 dynamic global vegetation models (TRENDY v8) under S2 Scenario (CO2+Climate) and represents the net biome productivity of the ecosystem. Data was derived from Le Quéré et al. (2019). The range of source data is global, and the Qinghai Tibet plateau region is selected in this data set. Original data is interpolated into 0.5*0.5 degree by the nearest neighbor method in space, and the original monthly scale is maintained in time. The data set is the standard model output data, which is often used to evaluate the temporal and spatial patterns of gross primary productivity, and compared with other remote sensing observations, flux observations and other data.
STEPHEN Sitch
The data set is based on the GPP simulated by 16 dynamic global vegetation models (TRENDY v8) under S2 Scenario (CO2+Climate) and represents the gross primary productivity of the ecosystem. Data was derived from Le Qu é r é Et al. (2019). The range of source data is global, and the Qinghai Tibet plateau region is selected in this data set. Original data is interpolated into 0.5*0.5 degree by the nearest neighbor method in space, and the original monthly scale is maintained in time. The data set is the standard model output data, which is often used to evaluate the temporal and spatial patterns of gross primary productivity, and compared with other remote sensing observations, flux observations and other data.
STEPHEN Sitch
This dataset includes data recorded by the Heihe integrated observatory network obtained from an observation system of Meteorological elements gradient of Daman Superstation from January 1 to December 31, 2018. The site (100.372° E, 38.856° N) was located on a cropland (maize surface) in the Daman irrigation, which is near Zhangye city, Gansu Province. The elevation is 1556 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (AV-14TH;3, 5, 10, 15, 20, 30, and 40 m, towards north), wind speed and direction profile (windsonic; 3, 5, 10, 15, 20, 30, and 40 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 2.5 m, 8 m in west of tower), four-component radiometer (PIR&PSP; 12 m, towards south), two infrared temperature sensors (IRTC3; 12 m, towards south, vertically downward), photosynthetically active radiation (LI190SB; 12 m, towards south, vertically upward; another four photosynthetically active radiation, PQS-1; two above the plants (12 m) and two below the plants (0.3 m), towards south, each with one vertically downward and one vertically upward), soil heat flux (HFP01SC; 3 duplicates with G1 below the vegetation; G2 and G3 between plants, -0.06 m), a TCAV averaging soil thermocouple probe (TCAV; -0.02, -0.04 m), soil temperature profile (AV-10T; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m), soil moisture profile (CS616; -0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m). The observations included the following: air temperature and humidity (Ta_3 m, Ta_5 m, Ta_10 m, Ta_15 m, Ta_20 m, Ta_30 m, and Ta_40 m; RH_3 m, RH_5 m, RH_10 m, RH_15 m, RH_20 m, RH_30 m, and RH_40 m) (℃ and %, respectively), wind speed (Ws_3 m, Ws_5 m, Ws_10 m, Ws_15 m, Ws_20 m, Ws_30 m, and Ws_40 m) (m/s), wind direction (WD_3 m, WD_5 m, WD_10 m, WD_15 m, WD_20 m, WD_30m, and WD_40 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m^2), infrared temperature (IRT_1 and IRT_2) (℃), photosynthetically active radiation (PAR) (μmol/ (s m-2)), average soil temperature (TCAV, ℃), soil heat flux (Gs_1, below the vegetation; Gs_2, and Gs_3, between plants) (W/m^2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_80 cm, Ts_120 cm, and Ts_160 cm) (℃), soil moisture (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_80 cm, Ms_120 cm, and Ms_160 cm) (%, volumetric water content), above the plants photosynthetically active radiation of upward and downward (PAR_U_up and PAR_U_down) (μmol/ (s m-2)), and below the plants photosynthetically active radiation of upward and downward (PAR_D_up and PAR_D_down) (μmol/ (s m-2)). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day.The meterological data during September 17 and November 7 and TCAV data after November 7 were wrong because the malfunction of datalogger. The missing data were denoted by -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2018-6-10 10:30. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2018) (for sites information), Liu et al. (2011) for data processing) in the Citation section.
LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
The dataset is a 30-minute eddy covariance flux observation data from nine flux stations in the Three Poles, including the data of ecosystem Net Carbon Exchange (NEE), Gross Primary Productivity(GPP), and Ecosystem Respiration (ER) . The time coverage of the data is from 2000 to 2016. The main steps of data pre-processing include outlier removal (±3σ), coordinate axis rotation(three-dimensional wind rotation), Webb-Pearman-Leuning correction, outlier elimination, carbon flux interpolation and decomposition. And missing data is interpolated by the nonlinear empirical formula between CO2 flux value(Fc) and environmental factors.
ZHANG Yangjian, NIU Ben
This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Dunhuang Station from January 1 to December 31, 2018. The site (93.708° E, 40.348° N) was located on a wetland in the Dunhuang west lake, Gansu Province. The elevation is 990 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (4m and 8 m, towards north), wind speed and direction profile (windsonic; 4m and 8 m, towards north), air pressure (1 m), rain gauge (4 m), infrared temperature sensors (4 m, towards south, vertically downward), soil heat flux (-0.05 and -0.1m ), soil soil temperature/ moisture/ electrical conductivity profile (below the vegetation in the south of tower, -0.05 and -0.2 m), photosynthetically active radiation (4 m, towards south), four-component radiometer (4 m, towards south), sunshine duration sensor(4 m, towards south). The observations included the following: air temperature and humidity (Ta_4 m, Ta_8 m; RH_2 m, RH_4 m, RH_8 m) (℃ and %, respectively), wind speed (Ws_4 m, Ws_8 m) (m/s), wind direction (WD_4 m, WD_8 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m^2), infrared temperature (IRT) (℃), photosynthetically active radiation (PAR) (μmol/ (s m-2)), soil heat flux (Gs_0.05m, Gs_0.1m) (W/m^2), soil temperature (Ts_0.05m, Ts_0.2m) (℃), soil moisture (Ms_0.05m, Ms_0.2m) (%, volumetric water content), soil conductivity (Ec_0.05m, Ec_0.2m)(μs/cm), sun time(h). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. The data were missing during Jan. 23 to Jan. 24 because of collector failure; the data during Mar. 17 and May 24 were wrong because of the tower body tilt; The air humidity data were rejected due to program error. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2018-6-10 10:30.
ZHAO Changming, ZHANG Renyi
The near surface atmospheric forcing and surface state dataset of the Tibetan Plateau was yielded by WRF model, time range: 2000-2010, space range: 25-40 °N, 75-105 °E, time resolution: hourly, space resolution: 10 km, grid number: 150 * 300. There are 33 variables in total, including 11 near surface atmospheric variables: temperature at 2m height on the ground, specific humidity at 2m height on the ground, surface pressure, latitudinal component of 10m wind field on the ground, longitudinal component of 10m wind field on the ground, proportion of solid precipitation, cumulative cumulus convective precipitation, cumulative grid precipitation, downward shortwave radiation flux at the surface, downward length at the surface Wave radiation flux, cumulative potential evaporation. There are 19 surface state variables: soil temperature in each layer, soil moisture in each layer, liquid water content in each layer, heat flux of snow phase change, soil bottom temperature, surface runoff, underground runoff, vegetation proportion, surface heat flux, snow water equivalent, actual snow thickness, snow density, water in the canopy, surface temperature, albedo, background albedo, lower boundary Soil temperature, upward heat flux (sensible heat flux) at the surface and upward water flux (sensible heat flux) at the surface. There are three other variables: longitude, latitude and planetary boundary layer height.
PAN Xiaoduo
1、Based on field eddy correlation (EC) measurement data, using the standard data processing method for EC data, including despiking, coordinate rotation, air density corrections, outlier rejection, and friction velocity threshold (u*) corrections, gap filled, and NEE partition. The dataset collects carbon flux data and microclimate measurement data from 2003 to 2016 in three typical alpine grassland ecosystems on the Qinghai-Tibet Plateau, including Damxung alpine meadow, Haibei alpine meadow ，Naqu alpine meadow，Zoige alpine grassland，Qilian mountion grassland . The time resolution of data is high (30 min), and the interpolation of data is complete throughout the year. This dataset can be applied to carbon flux assessment, comparison and prediction in these alpine meadows, attribution of climate factors affecting carbon flux, validation of model simulation results, etc. 2、Based on the MCDGF43 dataset, we produce the visible and near-infared albedo of Tibetan Plateau, using the standard data processing of hdf to tif , including the moasic, resample and masked by Tibetan Plateau's boundary. The time resolution of dataset is 8 days and the spatial resolution is 500 meters, which span the period of 2003-2016.
ZHANG Yangjian, SU Peixi, YANG Yan
This is the meteorological observation data of Selincuo Lake Camp. It includes the radiosonde data, turbulent flux, radiation observation data, general meteorologrical elements near the surface layer and others. The radiosonde data is observed separately at 14:00 and 18:00 July 2, at 8:00, 12:00, 16:00 and 20:00 July 3, at 8:00, 12:00, 16:00, 20:00, and 23:00 July 4, at 6:00 July 5, 2017. The observation time of turbulent flux and radiation observation data is from 17:30 June 29 to 10:00 July 6, 2017. The observation time of general meteorologrical elements near the surface layer is from 18:30 June 29 to 10:10 July 6, 2017. The wind lidar observation time is from 2:24 June 30 to 3:49 July 6, 2017. The data is stored as an excel file.
HAN Yizhe, MA Weiqiang*
This data set includes the 2013 observation data of 10 water net nodes in the 5.5km × 5.5km observation matrix (red box in the thumbnail) of Yingke / Daman irrigation area in the middle reaches of Heihe River. The 10 water net nodes contain 4cm and 10cm two-layer hydro probe II probes to observe the main variables such as soil moisture, soil temperature, conductivity and complex permittivity; the si-111 infrared temperature probe is set up at 4m height to observe the surface infrared radiation temperature of the underlying surface. The time and frequency of conventional observation is 10 minutes. In order to ensure the accurate synchronization of si-111 and remote sensing, one minute intensive observation is conducted at 00:00-04:30, 08:00-18:00 and 21:00-24:00 every day. This data set can provide spatiotemporal continuous observation data set for remote sensing estimation of key water and heat variables of heterogeneous surface, remote sensing authenticity test, ecological hydrology research, irrigation optimization management and other research. For details, please refer to "2013 middle reaches of Heihe River waternet data document 20141231. Docx"
KANG Jian, LI Xin, MA Mingguo
Zhanye Airport desert observation system can offer in situ calibration data for TASI, WiDAS and L band sensor used in aerospace experiment. Observation Site: This point is located in a large, homogeneous and flatten desert near by Zhangye Airport. The main vegetation type is Sparse and low shrub. The coordinates of this site: 38°4′41.30" N, 100°41′48.10" E. Observation Instrument: The observation system consists of two SI-111 infrared radiometers (Campbell, USA), one installed vertically downward to land surface, another face to south of zenith angle 35°. SI-111 sensor installed at 4.0 m height. Observation Time: This site operates from 10 June, 2012 to today. Observation data laagered by every 5 seconds uninterrupted. Output data contained sample data of every 5 seconds and mean data of 1 minute. Accessory data: Land surface infrared temperature (by SI-111), sky infrared temperature (by SI-111) can be obtained. Dataset is stored in *.dat file, which can be read by Microsoft excel or other text processing software (UltraEdit, et. al). Table heads meaning: TarT_Atm, Sky infrared temperature @ facing south of zenith angle 35° (℃); SBT_Atm, body temperature of SI-111 sensor (℃) measured sky; TarT_Sur, land surface infrared temperature @ 4.0 m height; SBT_Sur, body temperature of SI-111 sensor (℃) measured land surface. Dataset is stored day by day, named as: data format + site name + interval time + date + time. The detailed information about data item showed in data header introduction in dataset.
MA Mingguo
A land surface temperature and upward/downward shortwave radiation observation system was set up on the roof, which locate on the edge of No.4 eddy covariance system (EC4) of the MUlti-Scale Observation EXperiment on Evapotranspiration over heterogeneous land surfaces 2012 (MUSOEXE-12). This observation site can offer in situ calibration data for TASI, WiDAS and L band sensor used in aerospace experiment. Observation Site: This point is located in a large and homogeneous adobe roof in Shiqiao Village, Xiaoman Town, Zhangye City. Land surface of observation site is relatively flat and uniform, and also not tall trees around. It’s about 20 meters away from southwest No.4 eddy covariance system (EC4) observation points. The coordinates of this site: 38°52′38.50″ N，100°21′27.00″ E。 Observation Instrument: Observation system is composed of a SI-111 infrared radiometer (Campbell, USA) installed vertically downward, two CMP3 pyranometer (Kipp&Zonen, Netherlands) one upward, another downward. Observation height is 1.0 m, data logging by a Campbell CR850 logger. Sensor orientation： Observation mounting arm has 3 m long, parallel to roof edge, azimuth angle: 156° (East by south 66°) Observation Time: This site operates from 23 June, 2012 to 20 September, 2012. Observation data laagered by every 5 seconds uninterrupted. Output data contained sample data of every 5 seconds and mean data of 1 minute. Accessory data: Land surface (adobe roof) temperature, downward/upward total solar radiation, surface albedo. Dataset is stored in *.dat file, which can be read by Microsoft excel or other text processing software (UltraEdit, et. al). Table heads meaning: Rs_downwell, downward shortwave radiation (W/m^2); Rs_upwell, upward (reflect) shortwave radiation (W/m^2); albedo, calculate by Rs_upwell/ Rs_downwell. SBT_C, body temperature of SI-111 sensor (℃); Target_C, Target of surface temperature (℃). Dataset is stored day by day, named as: data format + site name + interval time + date + time. The detailed information about data item showed in data header introduction in dataset.
MA Mingguo
Er’ba Reservoir surface temperature of water body can offer in situ calibration data for TASI, WiDAS and L band sensor used in aerospace experiment. Observation Site: This site is 14 KM away from East of ZhangYe city. It’s located in Er’ba village, JianTan town, ZhangYe city. The coordinates of this site: 38°54′57.14" N, 100°36′57.39" E. Observation Instrument: The observation system consists of two SI-111 infrared radiometers (Campbell, USA) and two 109SS temperature probes (Campbell, USA). Two SI-111 sensors, one installed vertically downward to water surface, another face to south of zenith angle 35°. Temperature probes float under water surface at 0 cm. SI-111 sensor installed at 3.0 m height, 3.4 m away from water edge. Observation Time: This site operates from 27 May, 2012 to 27 September, 2012. Observation data laagered by every 5 seconds uninterrupted. Output data contained sample data of every 5 seconds and mean data of 1 minute. Accessory data： Water surface infrared temperature (by SI-111), sky infrared temperature (by SI-111), water surface temperature (by 109ss) can be obtained. Dataset is stored in *.dat file, which can be read by Microsoft excel or other text processing software (UltraEdit, et. al). Table heads meaning: TarT_Atm, Sky infrared temperature (℃) @ facing south of zenith angle 35°; SBT_Atm, body temperature of SI-111 sensor (℃) measured sky; TarT_Sur, water surface infrared temperature @ 3.0 m height; SBT_Sur, body temperature of SI-111 sensor (℃) measured water surface; WaterT_1, WaterT_2, water surface temperature (℃) measured by 109SS temperature probes. Dataset is stored day by day, named as: data format + site name + interval time + date + time. The detailed information about data item showed in data header introduction in dataset.
MA Mingguo
This data set includes the observation data of 25 water net sensor network nodes in Babao River Basin in the upper reaches of Heihe River from January 2015 to December 2015. 4cm and 20cm soil moisture / temperature is the basic observation of each node; some nodes also include 10cm soil moisture / temperature, surface infrared radiation temperature, snow depth and precipitation observation. The observation frequency is 5 minutes. The data set can be used for hydrological simulation, data assimilation and remote sensing verification. For details, please refer to "2015 data document 20160501. Docx of water net of Babao River in the upper reaches of Heihe River"
KANG Jian, LI Xin, MA Mingguo
This data set includes the 2015 observation data of 9 water net nodes in the 5.5km × 5.5km observation matrix (red box in the thumbnail) of Yingke / Daman irrigation area in the middle reaches of Heihe River. The nine nodes contain 4cm and 10cm two-layer hydro probe II probes to observe the main variables such as soil moisture, soil temperature, conductivity and complex permittivity; the si-111 infrared temperature probe is set up at 4m height to observe the surface radiation infrared temperature of the underlying surface. The observation time frequency is 5 minutes. This data set can provide spatiotemporal continuous observation data set for remote sensing estimation of key water and heat variables of heterogeneous surface, remote sensing authenticity test, ecological hydrology research, irrigation optimization management and other research.
KANG Jian, LI Xin, MA Mingguo
This data set includes the observation data of 40 water net sensor network nodes in Babao River Basin in the upper reaches of Heihe River since the end of June 2013. Soil moisture of 4cm, 10cm and 20cm is the basic observation of each node; 19 nodes include the observation of soil moisture and surface infrared radiation temperature; 11 nodes include the observation of soil moisture, surface infrared radiation temperature, snow depth and precipitation. The observation frequency is 5 minutes. The data set can be used for hydrological simulation, data assimilation and remote sensing verification.
KANG Jian, LI Xin, MA Mingguo
The dataset of automatic meteorological observations was obtained at the Dayekou Guantan forest station (E100°15′/N38°32′, 2835m), south of Zhangye city, Gansu province, from Oct. 1, 2007 to Dec. 31, 2009. Guantan forest station was dominated by the 15-20m high spruce and the surface was covered by 10cm deep moss. All the vegetation was in good condition. Observation items were the multilayer (2m and 10m) wind speed and direction, the air temperature and moisture, rain and snow gauges, snow depth, photosynthetically active radiation, four components of radiation from two layers (, 1.68m and 19.75 m), stem sap flow, the surface temperature, the multi-layer soil temperature (5cm, 10cm, 20cm, 40cm, 80cm and 120cm),soil moisture (5cm, 10cm, 20cm, 40cm, 80cm and 120cm) and soil heat flux (5cm & 15cm). As for detailed information, please refer to Meteorological and Hydrological Flux Data Guide.
MA Mingguo, Wang Weizhen, TAN Junlei, HUANG Guanghui, Zhang Zhihui
This dataset includes soil moisture, soil temperature and land surface temperature observations of 50 WATERNET wireless sensor network (WSN) nodes during the period from May to September 2012, which is one type of WSN nodes in the Heihe eco-hydrological wireless sensor network (WSN). The WATERNET located in the 4×4 MODIS grids in the observation matrix in the Zhangye oasis. Each WATERNET node observes the soil moisture, soil temperature, soil conductivity and complex dielectric constant at 4 cm and 10 cm depths by the Hydra Probe II sensor. There are 29 nodes among the WATERNET with the SI-111 sensor at 4 m height to measure the surface radiance temperature. The operational observation interval is 10 minutes, and the intensive observation mode with 1 minute is activated during 00:00-04:30, 08:00-18:00 and 21:00-24:00 (UTC+8), in order to synchronize with airborne or satellite-borne remote sensors. This dataset can be used in the estimation of surface hydrothermal variables and their validation, eco-hydrological research, irrigation management and so on. The detail description please refers to "WATERNET_Data_Document_HRBMiddle.docx”.
KANG Jian, Wang Zuocheng, Dong Cunhui, LI Xin, MA Mingguo
This data set includes the 2014 observation data of 9 water net nodes in the 5.5km × 5.5km observation matrix (red box in the thumbnail) of Yingke / Daman irrigation area in the middle reaches of Heihe River. The nine nodes contain 4cm and 10cm two-layer hydro probe II probes to observe the main variables such as soil moisture, soil temperature, conductivity and complex permittivity; the si-111 infrared temperature probe is set up at 4m height to observe the surface radiation infrared temperature of the underlying surface. The observation time frequency is 5 minutes. This data set can provide spatiotemporal continuous observation data set for remote sensing estimation of key water and heat variables of heterogeneous surface, remote sensing authenticity test, ecological hydrology research, irrigation optimization management and other research. Please refer to "2014 middle reaches of Heihe River waternet data document 20141231. Docx" for details
KANG Jian, LI Xin, MA Mingguo
This data set includes the observation data of 40 water net sensor network nodes in Babao River Basin in the upper reaches of Heihe River since January 2014. Soil moisture of 4cm, 10cm and 20cm is the basic observation of each node; 19 nodes include the observation of soil moisture and surface infrared radiation temperature; 11 nodes include the observation of soil moisture, surface infrared radiation temperature, snow depth and precipitation. The observation frequency is 5 minutes. The data set can be used for hydrological simulation, data assimilation and remote sensing verification. Please refer to "waternet data document 20141206. Docx" for details
KANG Jian, LI Xin, MA Mingguo
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in No. 1 and 2 quadrates of the E'bao foci experimental area on Oct. 17, 2007 during the pre-observation period The data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 23:04 BJT. Both the quadrates were divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. 25 sampling points were chosen, including centers and corners. Simultaneous with the satellite overpass, numerous ground data were collected, soil volumetric moisture, soil conductivity, the soil temperature, and the real part of soil complex permittivity by the WET soil moisture tachometer; the surface radiative temperature by the hand-held infrared thermometer; soil gravimetric moisture, volumetric moisture, and soil bulk density by drying soil samples from the cutting ring. Meanwhile, vegetation parameters as height, coverage and water content were also observed. Meanwhile, vegetation parameters as height, coverage and water content were also observed. Those provide reliable ground data for retrieval and verification of soil moisture, soil freeze/thaw status and the microwave radiative transfer model from active remote sensing approaches.
CHAO Zhenhua, CHE Tao, QIN Chun, WU Yueru
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in No.2 quadrate of the A'rou foci experimental area on Oct. 17, 2007 during the pre-observation period. The Envisat ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 23:04 BJT. The quadrate was divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. 25 sampling points were chosen, including centers and corners of each subsites. Simultaneous with the satellite overpass, numerous ground data were collected, soil volumetric moisture by ML2X; soil volumetric moisture, soil conductivity, soil temperature, and the real part of soil complex permittivity by WET soil moisture sensor; the surface radiative temperature by the hand-held infrared thermometer; soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). Meanwhile, vegetation parameters as height, coverage and water content were also observed. Surface roughness was detailed in the "WATER: Surface roughness dataset in the A'rou foci experimental area". Those provide reliable ground data for retrieval and validation of soil moisture and freeze/thaw status from active remote sensing approaches.
BAI Yunjie, HAO Xiaohua, LI Hongyi, LI Xin, LI Zhe
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in No. 1 and 2 quadrates of the Biandukou foci experimental area on Oct. 17, 2007 during the pre-observation period. The ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 23:04 BJT. Both the quadrates were divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. 25 sampling points were chosen, including centers and corners. Simultaneous with the satellite overpass, numerous ground data were collected: the soil temperature , volumetric soil moisture (cm^3/cm^3), soil salinity (s/m), soil conductivity (s/m) by the Hydra probe, the surface radiative temperature by the handheld infrared thermometer, gravimetric soil moisture, volumetric soil moisture, and soil bulk density by drying soil samples from the cutting ring (100cm^3). Meanwhile, vegetation parameters as height, coverage and water content were also observed. Those provide reliable ground data for the development and validation of soil moisture, soil freeze/thaw algorithms and the forward model from active remote sensing approaches.
BAI Yunjie, CAO Yongpan, LI Xin, Wang Weizhen, WANG Xufeng
The dataset of ground truth measurement synchronizing with MODIS was obtained in the Linze grassland foci experimental area on Jun. 22, 2008. Simultaneous east-west ground measurements on the canopy temperature, the half-height temperature and the land surface radiative temperature were carried out by the hand-held infrared thermometer at intervals of 125m in 8 quadrates (2km×2km), No.1 quadrate (H01-H08) on Jun. 22, No.2 quadrate (H09-H16) on Jun. 23,No.3 quadrate (H17-H24) on Jun. 22, No.4 quadrat (H25-H32) on Jun. 23, No.5 quadrate (H33-H40) on Jun. 22, No.6 quadrate (H41-H48) on Jun. 23, No,7 quadrate (H49-H56) and No.8 quadrate (H57-H64) on Jun. 23. Data were archived in Excel format. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
CHAO Zhenhua, NIAN Yanyun, WANG Xufeng, LIANG Wenguang
The dataset of ground truth measurements synchronizing with the airborne WiDAS mission was obtained in the Linze station foci experimental area on Jun. 29, 2008. WiDAS, composed of four CCD cameras, one mid-infrared thermal imager (AGEMA 550), and one infrared thermal imager (S60), can acquire CCD, MIR and TIR band data. The simultaneous ground data included: (1) soil moisture (0-5cm) nine times by the cutting ring (50cm^3) along LY06 and LY07 strips, and once by the cutting ring method and once by ML2X Soil Moisture Tachometer in the six points of Wulidun farmland quadrates. The preprocessed soil volumetric moisture data were archived as Excel files. (2) surface radiative temperature measured three times by three handheld infrared thermometer (5# and 6# from Cold and Arid Regions Environmental and Engineering Research Institute, and one from Institute of Geographic Sciences and Natural Resources, which were all calibrated) in LY06 and LY07 strips (98 sample points and repeated three times) and the Wulidun farmland quadrates (various points and repeated three times). Data were archived as Excel files. (3) maize canopy component temperature measured by the 5# handheld infrared thermometer (from Cold and Arid Regions Environmental and Engineering Research Institute) in Wulidun farmland quadrates. Six directions were measured, canopy backlighting and frontlighting, half height backlighting and frontlighting, the light and the shaded bareland, with each direction 20 measurements. (4) spectrum of maize, soil and soil with known moisture measured by ASD Spectroradiometer (350～2 500 nm) from BNU, and the reference board (40% before Jun. 15 and 20% hereafter) in Wulidun farmland quadrates. Raw spectral data were binary files , which were recorded daily in detail, and pre-processed data on reflectance (by ViewSpecPro) were archived as Excel.files (5) mltiangle maize spectrum measured by ASD Spectroradiometer (350～2 500 nm) from BNU, the reference board (40% before Jun. 15 and 20% hereafter), two observation platforms of BNU make and one of Institute of Remote Sensing Applications make in Wulidun farmland. Raw spectral data were archived as binary files, which were recorded daily in detail, and pre-processed data on reflectance and transmittivity were archived as text files (.txt). (6) LAI of maize measured by the fisheye camera (CANON EOS40D with a lens of EF15/28), shooting straight downwards, with exceptions of higher plants, which were shot upwards. Data included original photos (.JPG) and those processed by can_eye5.0 (in excel). (7) LAI of maize measured by LAI2000 in Wulidun farmland quadrates. Data educed from LAI2000 periodically were archived as text files (.txt) and marked with one ID. Raw data (table of word and txt) and processed data (Excel) were included. Besides, observation time, the observation method and the repetition were all archived. See the metadata record “WATER: Dataset of setting of the sampling plots and stripes in the Linze station foci experimental area” for more information of the quadrate locations.
DONG Jian, YU Yingjie, BAI Yanfen, HAO Xiaohua, Qian Jinbo, SHU Lele, WANG Yang, XU Zhen
The dataset of ground truth measurements synchronizing with MODIS, ALOS PALSAR and AMSR-E was obtained in the Biandukou foci experimental area on May 24, 2008. Observation items included: (1) the surface temperature in No. 1 (grassland), No. 2 (the rape land), No. 3 (the rape land), No. 4 (the wheat land) and No. 5 quadrate (wheat and rape); (2) the soil moisture by WET in No. 2 quadrate; (3) GPR and WET; (4) The spectrum by ASD Fieldspec FRTM (Boulder, Co, USA), 350nm-2500nm, 3nm for the visible near-infrared band and 10nm for the shortwave infrared band). The spectrum data were archived in the ASCII format, with the first five rows as the file header and the following two columns as wavelength (nm) and reflectance (percentage) respectively, and can be opened by .txt or wordpad. The .txt file was not reflectance but intermediate file for further calculation. Raw data were binary files direct from ASD (by ViewSpecPro). The surface radiative temperature and the physical temperature were measured by the handheld infrared thermometer. Besides, the cover type was also recorded. The data can be opened by Microsoft Office. Soil moisture was acquired by WET and the cutting ring. The data can be opened by Microsoft Office. Six data files were included, soil moisture, the surface temperature, GPR, coverage photos and preprocessed data, ground objects spectrum and satellite images.
BAI Yunjie, CAO Yongpan, CHE Tao, DU Ziqiang, HAO Xiaohua, WANG Zhixia, WU Yueru, CHAI Yuan, CHANG Sheng, QIAN Yonggang, SUN Xiaoqing, WANG Jindi, YAO Dongping, ZHAO Shaojie, ZHENG Yue, ZHAO Yingshi, LI Xiaoyu, PATRICK Klenk, HUANG Bo, LI Shihua, LUO Zhen
The dataset of ground truth measurements synchronizing with airborne WiDAS mission was obtained in the Linze grassland foci experimental area on Jul. 11, 2008. WiDAS, composed of four CCD cameras, one mid-infrared thermal imager (AGEMA 550), and one infrared thermal imager (S60), can acquire CCD, MIR and TIR band data. These simultaneous ground data were mainly the land surface temperature measured by the hand-held infrared thermometer in the reed plot A, the saline plots B and C, the alfalfa plot D and the barley plot E, the maximum of which were 120m×120m and the minimum were 30m×30m. Data were archived in Excel file. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
CAO Yongpan, CHAO Zhenhua, GE Chunmei, HU Xiaoli, HUANG Chunlin, LI Hongxing, LIU Chao, WU Yueru, SHEN Xinyi, YU Fan
The dataset of ground truth measurement synchronizing with the airborne microwave radiometers (L&K bands) mission was obtained in the Linze station foci experimental area on Jul. 8, 2008. Observation items included: (1) soil moisture (0-5cm) measured by the cutting ring method (50cm^3) in P1 to P6 strips (17 sample points each). Photos were taken. The preprocessed soil volumetric moisture data were archived as Excel files. (2) surface radiative temperature measured by three handheld infrared thermometer (5# and 6# from Cold and Arid Regions Environmental and Engineering Research Institute, and one from Institute of Geographic Sciences and Natural Resources, which were all calibrated) from P1 to P6 strips. There are 34 sample points in total and each was repeated three times synchronizing with the airplane. Photos were taken. Data were archived as Excel files. See the metadata record “WATER: Dataset of setting of the sampling plots and stripes in the Linze station foci experimental area” for more information of the quadrate locations.
XIE Tingting, JIANG Hao, SONG Yi, BAI Yanfen, GAO Song, Qian Jinbo, SHU Lele, SONG Yi, XU Zhen, XIE Tingting, JIANG Hao, LI Shihua
The dataset of ground truth measurements synchronizing with ASTER was obtained in the Linze station foci experimental area on May 28, 2008. Observation items included: (1) soil moisture (0-5cm) measured once by the cutting ring method at the corner points of the 40 subplots of the west-east desert transit zone strip once by cutting ring method in the corner points of nine subplots of the north-south desert transit zone, once by the cutting ring method and once by ML2X Soil Moisture Tachometer in the center points of nine subplots of the farmland. The preprocessed soil volumetric moisture data were archived as Excel files. (2) surface radiative temperature measured by the handheld infrared thermometer (5# and 6# from Cold and Arid Regions Environmental and Engineering Research Institute which were both calibrated) in 40 subplots of the west-east desert transit zone strip (repeated 14-30 times), and nine subplots of the north-south desert transit zone strip (repeated 12-30 times). Data were archived as Excel files. (3) BRDF of maize and desert scrub measured by ASD Spectroradiometer (350～2 500 nm) from BNU, the 40% reference board , two observation platforms of BNU make and one of Institute of Remote Sensing Applications make in Wulidun farmland quadrates and the desert transit zone strips. Raw spectral data were archived as binary files, which were recorded daily in detail, and pre-processed data on reflectance and transmittivity were archived as text files (.txt). (4) LAI measured by two methods in the the Wulidun farmland quadrates and Linze station quadrates. One is manual method. The LAI, plant height and the spacing of selected samples were measured by the ruler and the number of the sapmles in the quadrate were counted. Then the LAI can be calculated. The other method is LI-3100. Data were archived as Excel files.
Qian Jinbo, SONG Yi, WANG Zhixia, WANG Yang, PAN Xiaoduo, LI Jing, Li Xiangyun, Qu Yonghua, SUN Qingsong
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in No. 1 and 2 quadrates of the Biandukou foci experimental area on Oct. 18, 2007, during the pre-observation period. The ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:17 BJT. Both the quadrates were divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. 25 sampling points were chosen, including centers and corners. Simultaneous with the satellite overpass, numerous ground data were collected: the soil temperature , volumetric soil moisture (cm^3/cm^3), soil salinity (s/m), soil conductivity (s/m) by the Hydra probe, the surface radiative temperature by the handheld infrared thermometer, gravimetric soil moisture, volumetric soil moisture, and soil bulk density by drying soil samples from the cutting ring (100cm^3). Meanwhile, vegetation parameters as height, coverage and water content were also observed. Those provide reliable ground data for the development and validation of soil moisture, soil freeze/thaw algorithms and the forward model from active remote sensing approaches.
BAI Yunjie, CAO Yongpan, WANG Jian, Wang Weizhen, WANG Xufeng, JIN Rui, Qu Yonghua, ZHOU Hongmin
The dataset of ground truth measurements synchronizing with Landsat TM was obtained in the Biandukou foci experimental area from 11:10-13:30 on Mar. 17, 2008. Those provide reliable ground data for objects modelling and background modelling, remote sensing image simulation and scaling. Simultaneous with the satellite overpass, numerous ground data were collected, spectrum (ASD Fieldspec FRTM (Boulder, Co, USA), 350nm-2500nm, 3nm for the visible near-infrared band and 10nm for the shortwave infrared band), the surface temperature, atmospheric parameters, the soil profile gravimetric moisture (0-1cm, 1-3cm and 3-5cm), the shallow layer frost depth and the soil roughness in C1, G1, W1, W2, B1 and B2, mostly the grassland, the wheat stubble land, the deep plowed land and the rape stubble land. The quadrates of 90m×90m and 450m×450m were compartmentalized into 81 subgrids of 10m×10m and 50m×50m. Based on the resolution of 30m×30m and 150m×150m, the influence of adjacent eight pixels on the center pixel was studied. Section lines of each subgrid were adopted to acquire the pixel spectrum, which were measured more than once for the mean value. The spectrum data were archived in the ASCII format, with the first five rows as the file header and the following two columns as wavelength (nm) and reflectance (percentage) respectively. The .txt file was not reflectance but intermediate file for further calculation. Raw data were binary files direct from ASD (by ViewSpecPro). The surface radiative temperature and the physical temperature were measured by the handheld infrared thermometer. Besides, the cover type was also recorded. The data can be opened by Microsoft Office. Atmospheric parameters were measured by CE318 to retrieve the total optical depth, aerosol optical depth, Rayleigh scattering coefficient, column water vapor in 936 nm, and various parameters at 550nm to obtain horizontal visibility with the help of MODTRAN or 6S. Those provide reliable data for atmosphere correction of the same period in this area. The gravimetric soil moisture (samples from 0-1cm, 1-3cm and 3-5cm) was measured by the microwave drying method. The frost depth by the chopstick and the ruler. The soil was considered frozen when it was hard and with ice crystal. The data can be opened by Microsoft Office. Nine data files were included, TM data, CE318 data, B1, B2, C1, G1, W1 and W2.
CHANG Sheng, CHANG Yan, Fang Qian, QU Ying, LIANG Xingtao, LIU Zhigang, PAN Jinmei, PENG Danqing, REN Huazhong, ZHANG Yongpan, ZHANG Zhiyu, ZHAO Shaojie, Zhao Tianjie, ZHENG Yue, Zhou Ji, LIU Chenzhou, YIN Xiaojun, ZHANG Zhiyu
The dataset of ground truth measurements synchronizing with Envisat ASAR and ALOS PALSAR was obtained in the Linze station foci experimental area on May 24, 2008. The data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:34 BJT. Observation items included: (1) soil moisture (0-5cm) measured once by cutting ring method at corner points of the 40 subplots of the west-east desert transit zone strip, one time by cutting ring method in nine subplots of the north-south desert transit zone, strip and once by the cutting ring and three times by ML2X Soil Moisture Tachometer in the center points of nine subplots of Wulidun farmland quadrates . The preprocessed soil volumetric moisture data were archived as Excel files. (2) surface radiative temperature by measured two handheld infrared thermometer (5# and 6# from Cold and Arid Regions Environmental and Engineering Research Institute which were both calibrated) in 40 subplots of the west-east desert transit zone strip (repeated 14-30 times each), and nine subplots of the north-south desert transit zone strip (repeated 12-30 times). There are 34 sample points in total and each was repeated three times synchronizing with the airplane. Photos were taken. Data were archived as Excel files. (3) LAI, the plant height and the spacing measured by the ruler and the set square in Wulidun farmland quadrates and Linze station quadrates. Part of the samples were also measured by LI-3100. Data were archived as Excel files. See the metadata record “WATER: Dataset of setting of the sampling plots and stripes in the Linze station foci experimental area” for more information of the quadrate locations.
BAI Yanfen, DING Songchuang, PAN Xiaoduo, WANG Yang, ZHU Shijie, LI Jing, XIAO Zhiqiang, SUN Jinxia
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in the saline plot B, the alfalfa plot D and the barley plot E of the Linze grassland foci experimental area on May 24, 2008. The data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:34 BJT. The quadrate was divided into 6×6 subsites, with each one spanning a 120×120 m2 plot. Corner points were chosen. Simultaneous with the satellite overpass, numerous ground data were collected, soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3), the mean soil temperature from 0-5cm by the probe thermometer, and the land surface radiative temperature measured three times by the hand-held infrared thermometer in plot B; soil moisture, soil conductivity, the soil temperature, and the real part of soil complex permittivity by WET, the mean soil temperature from 0-5cm by the probe thermometer, and the land surface radiative temperature measured three times by the hand-held infrared thermometer in plot D; the soil temperature, soil moisture, the loss tangent, soil conductivity, the real part and the imaginary part of soil complex permittivity by the POGO soil sensor, the mean soil temperature from 0-5cm by the probe thermometer, and the land surface radiative temperature measured three times by the hand-held infrared thermometer in plot E. Data were archived in Excel file. Those provide reliable ground data for retrieval and validation of soil moisture and alinity content with active microwave remote sensing approaches. See WATER: Dataset of setting of the sampling plots and stripes in the Linze station foci experimental area for more information.
CHAO Zhenhua, HU Xiaoli, LIANG Ji, Wang Weizhen, LIU Zhaoyan, TANG Bohui, HAN Hui, WANG Xiaoping
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in No. 1 and 2 quadrates of the E'bao foci experimental area on Oct. 18, 2007 during the pre-observation period. The data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:17 BJT (Beijing Time). Both the quadrates were divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. 25 sampling points were chosen, including centers and corners. Simultaneous with the satellite overpass, numerous ground data were collected, soil volumetric moisture, soil conductivity, the soil temperature, and the real part of soil complex permittivity by the WET soil moisture tachometer; the surface radiative temperature by the hand-held infrared thermometer; soil gravimetric moisture, volumetric moisture, and soil bulk density by drying soil samples from the cutting ring (100cm^3). Meanwhile, vegetation parameters as height, coverage and water content were also observed. Surface roughness was detailed in the "WATER: Surface roughness dataset in the A'rou foci experimental area". Those provide reliable ground data for retrieval and verification of soil moisture, soil freeze/thaw status and the microwave radiative transfer model from active remote sensing approaches.
CHAO Zhenhua, CHE Tao, QIN Chun, WU Yueru
The dataset of continuous LST (Land Surface Temperature) observation was obtained by the automatic thermometer in the Linze grassland foci experimental area. Six devices numbered from #1 to #6 were used. Observations were carried out in the reed plot A, the saline plots B and C, the alfalfa plot D, the barley plot E and the temporary farmland on Jun. 10 and 11, 2008 and in plots A, B and E on Jul. 11, 2008. Observation time and the land surface radiative temperature were archived in Word, txt and Excel format. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental of Linze station area for more information.
HUANG Chunlin, CHAO Zhenhua, GE Chunmei, HU Xiaoli, LIU Chao, NIAN Yanyun, WANG Shuguo, WANG Xufeng, WU Yueru, WANG Jing
The dataset of ground truth measurement synchronizing with the airborne microwave radiometers (L&K bands) mission was obtained in L2, L4 and L5 of the A'rou foci experimental area on Mar. 19, 2008. The samples were collected every 100 m along the strip from south to north. In L2, the soil temperature, soil volumetric moisture, the loss tangent, soil conductivity, and the real part and the imaginary part of soil complex permittivity were acquired by the POGO soil sensor, the mean soil temperature from 0-5cm by the probe thermometer, and soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). In L4, the soil temperature, soil volumetric moisture, the loss tangent, soil conductivity, and the real part and the imaginary part of soil complex permittivity were acquired by the POGO soil sensor, the mean soil temperature from 0-5cm by the probe thermometer, the surface radiative temperature measured three times by the hand-held infrared thermometer, and soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). In L5, soil volumetric moisture was acquired by ML2X, the mean soil temperature from 0-5cm by the probe thermometer, and soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). Surface roughness was detailed in the "WATER: Surface roughness dataset in the A'rou foci experimental area". Besides, GPR (Ground Penetration Radar) observations were also carried out in L6 and the handheld thermal imager observations in L4. Those provide reliable ground data for retrieval and validation of soil moisture and freeze/thaw status from active remote sensing approaches.
CAO Yongpan, GU Juan, HAN Xujun, LI Zhe, WANG Jianhua, Wang Weizhen, WU Yueru, ZHOU Hongmin, LI Hua, CHANG Cun, YU Meiyan, ZHAO Jin, PATRICK Klenk, SUN Jicheng, YAN Yeqing
The dataset of ground truth measurements synchronizing with the airborne microwave radiometers (L&K bands) mission was obtained along the sample lines 1, 2, 3, 4, 5 and 6 of the Linze grassland foci experimental area on Jul. 8, 2008. 25 points at intervals of 100m were selected along each line. Simultaneous with the satellite overpass, numerous ground data were collected, soil gravimetric moisture, volumetric moisture, and soil bulk density by the cutting ring, the mean soil temperature from 0-5cm by the probe thermometer, the canopy and the land surface temperature by the hand-held infrared thermometer. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
GE Chunmei, GE Yingchun, HU Xiaoli, HUANG Chunlin, LI Hongxing, WANG Yang, WANG Xufeng, WU Lizong, WU Yueru, ZHU Shijie, YU Fan, LI Xiaoyu
The dataset of ground truth measurement synchronizing with the airborne microwave radiometers (L&K bands) mission was obtained in the Biandukou foci experimental area on Jul. 4, 2008. Observation items included: (1) the soil temperature by the handheld infrared thermometer from L1 to L8 (1km from one another) in Biandukou and soil moisture by ML2X; nine samples were collected every 200 m along each line (1.6km). (2) 5 quadrates (50cm×50cm) investigations including GPS, the vegetation cover types and the height, the actual numbering, the valve bag numbering, wet weight+the refuse bag (g), dry weight+the envelope (g), the envelope (g) and the photo numbering. The data were archived as Excel files.
CAO Yongpan, LI Hongxing, LIU Chao, MA Mingguo, RAN Youhua, WANG Yang
The dataset of ground truth measurement synchronizing with MODIS was obtained in the Linze grassland foci experimental area on Jun. 11, 2008. Simultaneous east-west ground measurements on the canopy temperature, the half-height temperature and the surface radiative temperature were carried out by the hand-held infrared thermometer at intervals of 125m in 8 quadrates (2km×2km), No.1 quadrate (H01-H08), No.2 quadrate (H09-H16), No.3 quadrate (H17-H24), No.4 quadrate (H25-H32), No.5 quadrate (H33-H40), No.6 quadrat (H41-H48), No.7 quadrate (H49-H56) and No.8 quadrat (H57-H64). Data were archived in Excel file. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
CHAO Zhenhua, HUANG Chunlin, MA Mingguo, Qian Jinbo, RAN Youhua, WANG Xufeng, FENG Lei, YU Fan
The dataset of ground truth measurement synchronizing with Envisat ASAR was obtained in No. 1, 2 and 3 quadrates of the A'rou foci experimental area on Jul. 5 and Jul. 6, 2008. The Envisat ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:14 BJT. The quadrates were divided into 4×4 subsites, with each one spanning a 30×30 m2 plot. Observation items included: (1) the quadrate investigation in No. 2 and 3 quadrates: GPS by GARMIN GPS 76, plant species by manual cognition, the plant number by manual work, the height by the measuring tape repeated 4-5 times, phenology by manual work, the coverage by manual work (compartmentalizing 0.5m×0.5m into 100 to see the percentage the stellera takes) and the chlorophyll content by SPAD 502. (2) spectrum of stellera and pasture by ASD FieldSpec (350～2 500 nm), with 20% reference board. The preprocessed canopy spectrum was archived. (3) BRDF by ASD FieldSpec (350～2 500 nm), with 20% reference board. The processed reflectance and transmittivity were archived as .txt files. (4) photosynthesis of stellera and pasture by LI-6400. The data were archived in Excel format. (5) soil moisture by WET soil moisture tachometer. Acquisition time, soil moisture (%vol), Ecp (ms/m), Tmp Eb and Ecb (ms/m) of 25 corner points were archived. (6) the soil temperature by the handheld infrared thermometer. Acquisition time, the soil temperature measured three times and the land cover types were archived. The data included the canopy reflectance on Jul. 5 and 6, photosynthesis on Jul. 5 and 6, BRDF on Jul. 5, photos on Jul. 5, the infrared land surface temperature and soil moisture by WET on Jul. 5, biomass on Jul. 5 and the surface temperature along No. 3 flight on Jul. 6.
DING Songchuang, GE Yingchun, LI Hongyi, MA Mingguo, Qian Jinbo, WANG Yang, YU Yingjie, LIU Sihan
The dataset of ground truth measurement synchronizing with the airborne microwave radiometers (L&K bands) was obtained in the Biandukou foci experimental area from 11:20 to 12:30BJT on Mar. 19, 2008. Observation items included: (1) the frost depth by the chopstick and the ruler. The soil was considered frozen when it was hard and with ice crystal. The data can be opened by Microsoft Office Word. (2) the surface radiative temperature by the handheld infrared thermometer and the physical temperature by the thermocouple. The data can be opened by Microsoft Office Word. (3) the soil moisture (soil samples from 0-1cm, 1-3cm and 3-5cm) by the microwave drying method. The data can be opened by Microsoft Office Word. (4) photos of each sampling point in .jpg for further reference. Six data files were included, the ground-based K-band microwave radiometer, the ground-based L-band microwave radiometer, the frost depth, soil moisture, the surface temperature and the surface conditions.
CHANG Sheng, Fang Qian, QU Ying, LIANG Xingtao, LIU Zhigang, PAN Jinmei, PENG Danqing, REN Huazhong, ZHANG Yongpan, ZHANG Zhiyu, ZHAO Shaojie, Zhao Tianjie, ZHENG Yue, Zhou Ji, CHE Tao, LIU Chenzhou, YIN Xiaojun, ZHANG Zhiyu
The dateset of the ground-based RPG-8CH-DP microwave radiometer observations was obtained in the Biandukou foci experimental area from Mar. 14 to 17, 2008. Observation items included the brightness temperature by the ground-based microwave radiometer (18.7GHz and 36.5GHz), the soil temperature by the thermal resistor, the gravimetric soil moisture by the microwave drying method, and the surface roughness by the grid board. The wheat stubble land (38°15'44.13"N, 100°55'35.34"E) was chosen for continuous observations from 11:00 to 24:00 on Mar. 14, with the incidence 20°-70° and the step length 5°. The rape stubble land (38°15'23.17"N, 100°58'37.84"E) was chosen for continuous observations from 10:00 to 21:30 on Mar. 16, with the incidence 20°-70° and the step length 5°. The deep plowed land (38°18'8.28"N, 101° 3'27.22"E) was chosen for short time observations from 17:26 to 19:20 on Mar. 17, with the azimuth angle 240°-300° and the step length 10°, the incidence 40°-70° and the step length 5°. The brightness temperature was archived as .BRT and .txt files (the ASCII format). Each row in .txt was listed by year, month, date, hour, minute, second, 6.925GHz (h), 6.925GHz (v), 10.65GHz (h), 10.65GHz (v) , 18.7GHz (h), 18.7GHz (v), 36.5GHz (h), 36.5GHz (v), the elevation angle, and the azimuth angle. Values for 6.925GHz and 10.65GHz were zero due to malfunction. The roughness data were obtained by the grid board and the camera and the RMS height (cm) and correlation length (cm) were also calculated and archived, which could be opened by Notepad or Microsoft Office Word. Those provide reliable reference for the roughness of the same land cover type. The gravimetric soil moisture (soil samples from 0-1cm, 1-3cm and 3-5cm) was measured by the microwave drying method. The file can be opened by Microsoft Office Word. The shallow layer soil moisture was measured by hydra prob from 12:00 to 17:00 on 14 and by the Hydra probe (straight downward for 0-5cm) and HH2 (level into the soil surface) on 16. The surface temperature was measured by the thermal resistor. The file can be opened by Microsoft Office Word. Four data files were included, the brightness temperature, the surface temperature, the soil moisture and the surface roughness.
CHANG Sheng, LIANG Xingtao, PAN Jinmei, PENG Danqing, ZHANG Yongpan, ZHANG Zhiyu, ZHAO Shaojie, Zhao Tianjie, ZHENG Yue, YIN Xiaojun, ZHANG Zhiyu
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in No.1 (freeze/thaw status), No. 2 (snow parameters) and No. 3 (freeze/thaw status) quadrates of the A'rou foci experimental areas on Mar. 12, 2008. The Envisat ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:29 BJT. The quadrates were divided into 4×4 subsites, with each one spanning a 30×30 m2 plot. Center and corner points of each subsite were chosen for all observations except for the cutting ring measurements which only observed the center points. In No. 1 quadrate, numerous ground data were collected, the soil temperature, soil volumetric moisture, the loss tangent, soil conductivity, and the real part and the imaginary part of soil complex permittivity by the POGO soil sensor, soil volumetric moisture by ML2X, the soil volumetric moisture profile (10cm, 20cm, 30cm, 40cm, 60cm and 100cm) by PR2, the mean soil temperature from 0-5cm by the probe thermometer, soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). In No. 2 quadrate, simultaneous with ASAR, snow parameters were measured, the snow surface temperature by the thermal infrared probe, the snow layer temperature by the probe thermometer, the snow grain size by the handheld microscope, snow density by the aluminum case, the snow surface temperature and the snow-soil interface temperature by the thermal infrared probe, snow spectrum by ASD, and snow albedo by the total radiometer. In No. 3 quadrate soil volumetric moisture, soil conductivity, the soil temperature, and the real part of soil complex permittivity were measured by WET, the mean soil temperature from 0-5cm by the probe thermometer (5# and 7#), the surface radiative temperature by the hand-held infrared thermometer (5#), and soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). Surface roughness was detailed in the "WATER: Surface roughness dataset in the A'rou foci experimental area". Besides, GPR (Ground Penetration Radar) observations were also carried out in No. 1 quadrate of A'rou. Those provide reliable ground data for retrieval and verification of soil moisture and freeze/thaw status from active remote sensing approaches.
BAI Yanfen, CAO Yongpan, GE Chunmei, GU Juan, HAN Xujun, LI Zhe, LIANG Ji, MA Mingguo, SHU Lele, WANG Jianhua, WANG Xufeng, WU Yueru, XU Zhen, QU Wei, CHANG Cun, DOU Yan, MA Zhongguo, YU Meiyan, ZHAO Jin, JIANG Tenglong, XIAO Pengfeng , LIU Yan, ZHANG Pu, PATRICK Klenk, YUAN Xiaolong
The dataset of ground truth measurement synchronizing with Envisat ASAR and MODIS was obtained in the arid region hydrological experimental area on May 24, 2008. The Envisat ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:34 BJT. Observation items included: (1) The radiative temperature of Reaumuria soongorica and the bare soil in Huazhaizi desert No. 2 plot (HZZHMYD2)was collected using ThermaCAM SC2000 (1.2m above the ground, FOV = 24°×18°), along the diagonal (NW-SE). The data included raw data (read by ThermaCAM Researcher 2001), recorded data and the blackbody calibrated data (archived as Excel files). (2) The radiative temperature by the automatic thermometer (FOV: 10°; emissivity: 0.95), were measured at nadir with time intervals of one second. Raw data, blackbody calibrated data and processed data were all archived as Excel files. (3) The radiative temperature in Huazhaizi desert No. 2 plot by the handheld infrared thermometer (which belongs to BNU) along the diagonal (NW-SE). Raw data (.doc), blackbody calibrated data and processed data (in Excel format) were all archived. (4) Soil moisture (0-40cm) by the cutting ring and the soil temperature by the thermocouple thermometer in Yingke oasis and Huazhaizi foci experimental area. Besides, (a) roughness of No. 1 and 2 Huazhizi desert plots was also measured by self-made instruments . Sample points were selected every 30m along the diagonal of each plot. (b) soil profile moisture (0-100cm) and the temperature in the maize field of Yingke oasis. (c) soil profile moisture (0-100cm) and the temperature in one orchard of Yingke Oasis. Data were all archived as Excel files. (5) the photosynthetic rate of alfalfa and barley at Linze grass station by LI-6400. Raw data were archived in the user-defined format (by notepat.exe) and processed data were as Excel files. (6) ground object reflectance spectra of new-born rape and the bare land in Biandukou foci experimental area by ASD FieldSpec (350～2500 nm) from Institute of Remote Sensing Applications (CAS). Raw data were binary files direct from ASD (by ViewSpecPro), and pre-processed data on reflectance were in Excel format. (7) LAI by the measuring tape and the ruler in the alfalfa field of Linze grass station. The maximum length and width of alfalfa leaves and barley were measured. Data were archived as Excel files. (8) surface roughness in Huazhaizi desert No. 2 plot with the self-made roughness board (Cold and Arid Regions Environmental and Engineering Research Institute, CAS), the digital camera and the compass. Sample points were selected at equal intervals along the diagonals and marked in the photos.
CHEN Ling, KANG Guoting, QIAN Yonggang, REN Huazhong, WANG Haoxing, WANG Jindi, YAN Guangkuo, GE Yingchun, SHU Lele, WANG Jianhua, XU Zhen, GUANG Jie, LI Li, XIN Xiaozhou, ZHANG Yang, ZHOU Chunyan, TAO Xin, YAN Binyan, YAO Yanjuan, CHENG Zhanhui, YANG Tianfu
The dataset of ground truth measurement synchronizing with Envisat ASAR was obtained in No. 2 and 3 quadrates of the A'rou foci experimental area on Mar. 14, 2008. The Envisat ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 23:21 BJT. The quadrates were divided into 4×4 subsites, with each one spanning a 30×30 m2 plot. Only the corner points of each subsite were chosen for observations. Those provide reliable ground data for retrieval and verification of soil moisture from active remote sensing approaches. In No. 2 quadrate, simultaneous with the satellite overpass, numerous ground data were collected, the soil temperature, soil volumetric moisture, the loss tangent, soil conductivity, and the real part and the imaginary part of soil complex permittivity by the POGO soil sensor, the mean soil temperature from 0-5cm by the probe thermometer, the surface radiative temperature measured three times by the hand-held infrared thermometer, soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). In No. 3 quadrate, simultaneous with the satellite overpass, numerous ground data were collected, the soil temperature, soil volumetric moisture, the loss tangent, soil conductivity, and the real part and the imaginary part of soil complex permittivity by the POGO soil sensor, soil volumetric moisture by ML2X, the mean soil temperature from 0-5cm by the probe thermometer, the surface radiative temperature measured three times by the hand-held infrared thermometer, soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). Surface roughness was detailed in the "WATER: Surface roughness dataset in the A'rou foci experimental area".
CAO Yongpan, GU Juan, LI Xin, LI Zhe, MA Mingguo, SHU Lele, WANG Jianhua, WANG Xufeng, WU Yueru, ZHU Shijie, CHANG Cun
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in No. 1, 2 and 3 quadrates of the A'rou foci experimental area on Jul. 14, 2008. The Envisat ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:31 BJT. The quadrates were divided into 4×4 subsites, with each one spanning a 30×30 m2 plot. Those provide reliable ground data for retrieval and validation of soil moisture from active remote sensing approaches. Observation items included: (1) soil moisture by POGO soil sensor in No. 1, 2 and 3 quadrates; 25 corner points of each subsite were chosen for the soil temperature, soil volumetric moisture, the loss tangent, soil conductivity, and the real part and the imaginary part of soil complex permittivity; (2) the soil temperature by the handheld infrared thermometer 3# and 5# from BNU in No. 1 quadrate, 1# and 4# in No. 2 quadrate, and 2# and 6# in No. 3 quadrate; 25 corner points of each subsite were measured twice by two groups, and time, the maximum, the minimum and the mean value, and the land cover types were all recorded. (3) spectrum of the grassland, the bare land and the stellera by the thermal infrared spectrometer, 102F. The dataset includes ASAR images, preprocessed data of the thermal infrared spectrometer, 102F, the surface temperature and soil moisture synchronizing with Envisat ASAR.
GAO Hongchun, LI Hongxing, LIU Chao, RAN Youhua, REN Huazhong, YU Yingjie
The dataset of albedo observations was obtained in the Linze grassland foci experimental area. Measurements were carried out by using the shortwave radiometer (the upward radiometer: 071392; the downward radiometer: 071389) in the reed plot A, the saline plots B and C, the alfalfa plot D, the barley plot E and the temporary cement floor. Manual work was applied before Jun. 6, 2008 with the probe 1.3m-1.46m high and automatic observations hereafter with the probe 1.20m or 1.30m. Observation site cover type observation date Plot E barley May 25, 2008 Plot D alfalfa May 26, 2008 Plot D alfalfa May 27, 2008 Plot E cumin May 28, 2008 Plot E cumin May 30, 2008 Plot A reed Jun. 1, 2008 Plot B saline Jun. 2, 2008 Plot A reed Jun. 3, 2008 Temporary cement floor Jun. 4, 2008 Vicinity of plot E Jun. 6, 2008 Plot A reed Jun. 20, 2008 Plot A reed Jun. 22, 2008 Plot D alfalfa Jun. 23, 2008 Plot E barley Jun. 24, 2008 Plot E barley Jul. 11, 2008 Self-recording observations included: TIMESTAMP: observation time SOLAR_UP_AVG: downward shortwave radiation SOLAR_DOWN_AVG: upward shortwave radiation SOLAR_NET_AVG: net radiation = SOLAR_UP_AVG - SOLAR_DOWN_AVG albedo_Avg: albedo = SOLAR_DOWN_AVG / SOLAR_UP_AVG batt_volt_Min: voltage ptemp: CR1000 temperature Data were archived in Excel file. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
CHAO Zhenhua, GE Chunmei, HU Xiaoli, HUANG Chunlin, LIANG Ji, WANG Xufeng, WU Yueru, WANG Ying, Wang Jing
The dataset of albedo observations was obtained by the shortwave radiometer (1#: CMP3-060580 and 2#: CMP3-060584 from Institute of Remote Sensing Applications) in the arid region hydrology experiment area from May 20 to Jul. 14, 2008. The dataset of ground truth measurement was synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner), OMIS-II, Landsat TM, ASTER, Hyperion and CHRIS. Observation items included: (1) Albedo in Yingke oasis and Huazhaizi desert steppe foci experimental area. Yingke maize field was measured on May 28 and 30, Jun. 3, 16, 20, 27 and 29, Jul. 11 and 14, 2008, Yingke wheat field on May 20 and 29, Jun. 1, 4, 6, 9, 15 and 24, Jul. 7 and 14, 2008, Huazhaizi desert No. 2 plot on Jun. 14, 22 and 30, 2008 and the flax field on Jun. 23, 2008. (2) Albedo in Linze foci experimental area. Maize was measured on May 25, 2008 and desert and alfalfa on May 24, 2008. (3) Albedo in Biandukou foci experimental area. The rape field, the grassland and the barley were measured on Jun. 24, 2008, and barley on Jul. 6, 2008. (4) Zhangye intensive experimental area. The intra-city grassland and the roof of Jingdu Hotel were measured on May 27, 2008. Besides the shortwave radiometer, the digital multimeter (UNIT) was also used for voltage measuring. Raw data were archived in paper forms and Excel after input into the computer. Besides, shorter plants were chosen for measurements as the platform was not high enough. And the distance between the probe and the plant was shorter during the later observation period.
LIU Sihan, Liu Qiang, XIN Xiaozhou, SU Gaoli, XIA Chuanfu, ZHOU Mengwei
The dataset of ground truth measurement synchronizing with MODIS was obtained in the Linze grassland foci experimental area on Jun. 10, 2008. Simultaneous east-west ground measurements on the canopy temperature, the half-height temperature and the surface radiative temperature were carried out by the hand-held infrared thermometer at intervals of 125m in 8 quadrates (2km×2km), No.1 quadrat (H01-H08), No.2 quadrat (H09-H16), No.3 quadrat (H17-H24), No.4 quadrat (H25-H32), No.5 quadrat (H33-H40), No.6 quadrat (H41-H48), No.7 quadrat (H49-H56) and No.8 quadrat (H57-H64). Data were archived in Excel file. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
GE Chunmei, HAO Xiaohua, HUANG Chunlin, WANG Xufeng
The dataset of ground truth measurements synchronizing with the airborne WiDAS mission was obtained in 5 quadrates (30 m×30 m) the Biandukou foci experimental area on May 31, 2008. WiDAS, composed of four CCD cameras, one mid-infrared thermal imager (AGEMA 550), and one infrared thermal imager (S60), can acquire CCD, MIR and TIR band data. The simultaneous ground data were the surface radiative temperature and soil moisture. The quadrates were covered with wheat, rape and bare land. The radiative temperature of 25 corner points (located in No. 2, 3, 4 and 5 quadrates) were acquired. (1) the surface radiative temperature by the handheld infrared thermometer; the quadrate of 30 m×30 m was divided into 21 corner points and each point was measured three times; two for the bare land and one for the vegetation if the two coexist. The data included raw data, recorded data and the blackbody calibrated data. (2) soil moisture (0-5cm) by TDR; 16 center points of the subplot (7.5m×7.5m) were measured three times and the data were archived as Excel files. (3) the time-continuous surface radiative temperature by the fixed automatic thermometer (FOV: 10°; emissivity: 0.95), observing straight downwards at intervals of 1s. Raw data, blackbody calibrated data and processed data were archived as Excel files. Four data files were included, the fixed point temperature in No. 2, 3, 4 and 5 quadrates, the radiative temperature by the handheld infrared thermometer, calibration data and the time-continuous data.
CHAI Yuan, KANG Guoting, QIAN Yonggang, REN Huazhong, WANG Haoxing, LIU Xiaocheng, LIANG Wenguang, LI Xiaoyu, HUANG Bo, LUO Zhen
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in the Linze grassland foci experimental area on Jul. 11, 2008. The data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:26 BJT. Observations were carried out in the reed plot A, the saline plots B and C, the alfalfa plot D and the barley plot E, which were divided into 6×6 subsites, with each one spanning a 120×120 m2 plot. Soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by using the cutting ring, the mean soil temperature from 0-5cm by the probe thermometer, and the canopy temperature and the land surface temperature by the hand-held infrared thermometer were measured in A, B and C; the soil temperature, soil moisture, the loss tangent, soil conductivity, the real part and the imaginary part of soil complex permittivity by the POGO soil sensor, the mean soil temperature from 0-5cm by the probe thermometer, the canopy temperature and the land surface temperature by the hand-held infrared thermometer in D and E. Data were archived in Excel file. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
CAO Yongpan, CHAO Zhenhua, GE Chunmei, HU Xiaoli, HUANG Chunlin, LIU Chao, WU Yueru, SHEN Xinyi
The dataset of ground truth measurements synchronizing with airborne WiDAS mission was obtained in the Linze grassland foci experimental area on May 30, 2008. WiDAS, composed of four CCD cameras, one mid-infrared thermal imager (AGEMA 550), and one infrared thermal imager (S60), can acquire CCD, MIR and TIR band data. The simultaneous ground data included the land surface temperature measured by the hand-held infrared thermometer in the reed plot A, the saline plots B and C, the alfalfa plot D and the barley plot E, the maximum of which were 120m×120m and the minimum were 30m×30m, and soil gravimetric moisture, volumetric moisture, and soil bulk density after drying measured by the cutting ring and the mean soil temperature from 0-5cm measured by the probe thermometer in plot A, B and C; the soil temperature, soil moisture, the loss tangent, soil conductivity, the real part and the imaginary part of soil complex permittivity measured by the POGO soil sensor, and the mean soil temperature from 0-5cm measured by the probe thermometer in plot D and E. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
CAO Yongpan, CHAO Zhenhua, GE Chunmei, HAN Xujun, HU Xiaoli, HUANG Chunlin, LIANG Ji, WANG Shuguo, WU Yueru, FENG Lei, YU Fan, WANG Jing
The dataset of ground truth measurements synchronizing with the airborne WiDAS mission was obtained in No. 1 and No. 3 quadrates of the A'rou foci experimental area on May 31, 2008. WiDAS, composed of four CCD cameras, one mid-infrared thermal imager (AGEMA 550), and one infrared thermal imager (S60), can acquire CCD, MIR and TIR band data. The simultaneous ground data were the surface radiative temperature and surface soil moisture. The surface radiative temperature (emissivity: 1.0) was measured by the automatic thermometer at intervals of 0.05s, and the data were archived as .txt files (.dat format). The first seven rows were the header file, including acquisition date, time, and intervals; besides, Time (starting time), TObj (target temperature), Tint (the interior temperature of the probe), TBox (the temperature of the box) and Tact (the actual temperature calculated from the given emissivity) were also listed. Soil moisture (0-12cm and 0-20cm) was measured by TDR. The data including the soil temperature, soil complex permittivity and soil conductivity, were archived in Excel format.
HUANG Chunlin, GE Chunmei, HAN Xujun, LI Li, XIN Xiaozhou, ZHOU Mengwei
The dataset of ground truth measurements synchronizing with airborne WiDAS mission was obtained in the Linze grassland foci experimental area on Jun. 29, 2008. WiDAS, composed of four CCD cameras, one mid-infrared thermal imager (AGEMA 550), and one infrared thermal imager (S60), can acquire CCD, MIR and TIR band data. The simultaneous ground data were mainly the land surface temperature measured by the hand-held infrared thermometer in the reed plot A, the saline plots B and C and the barley plot E, the maximum of which were 120m×120m and the minimum were 30m×30m. Data were archived in Excel file. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
CAO Yongpan, GE Chunmei, HU Xiaoli, HUANG Chunlin, WANG Shuguo, Wang Jing
The dataset of ground truth measurement synchronizing with the airborne imaging spectrometer (OMIS-II) mission was obtained in the Linze station foci experimental area on Jun. 6, 2008. Observation items included: (1) soil moisture (0-5cm) measured by the cutting ring (50cm^3) along LY06, LY07 and LY08 strips (repeated nine times). The preprocessed soil volumetric moisture data were archived as Excel files. (2) surface radiative temperature measured by three handheld infrared thermometers (5# and 6# from Cold and Arid Regions Environmental and Engineering Research Institute, and one from Institute of Geographic Sciences and Natural Resources, which were all calibrated) in LY06 and LY07 strips. There are 49 sample points in total and each was repeated three times synchronizing with the airplane. Data were archived as Excel files. See the metadata record “WATER: Dataset of setting of the sampling plots and stripes in the Linze station foci experimental area” for more information of the quadrate locations.
GAO Song, HAO Xiaohua, PAN Xiaoduo, Qian Jinbo, SONG Yi, WANG Yang
The dataset of ground truth measurements synchronizing with the airborne microwave radiometers (L&K bands) mission was obtained along the sample lines 1, 2, 3, 4, 5 and 6 of the Linze grassland foci experimental area on May 25, 2008. Complementary measurements were carried out along Line 7 on Jun. 2. 25 points at intervals of 100m were selected at each line. Simultaneous with the satellite overpass, numerous ground data were collected, the soil temperature, soil moisture, the loss tangent, soil conductivity, the real part and the imaginary part of soil complex permittivity measured by the POGO soil sensor, the mean soil temperature from 0-5cm measured by the probe thermometer, and the surface radiative temperature measured three times by the hand-held infrared thermometer in L1, L2, L3 and L4; soil volumetric moisture, soil conductivity, the soil temperature, and the real part of soil complex permittivity were measured by WET, the mean soil temperature from 0-5cm measured by the probe thermometer, and the surface radiative temperature measured three times by the hand-held infrared thermometer in L5 and L6; the soil temperature, soil moisture, the loss tangent, soil conductivity, the real part and the imaginary part of soil complex permittivity by the POGO soil sensor, the mean soil temperature from 0-5cm measured by the probe thermometer, and the surface radiative temperature measured by the hand-held infrared thermometer, and soil gravimetric moisture, volumetric moisture, and soil bulk density measured by the cutting ring in L7. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
CHAO Zhenhua, GE Chunmei, HAN Xujun, HUANG Chunlin, RAN Youhua, SONG Yi
The dataset of ground truth measurements synchronizing with MODIS was obtained in C1, W2 and B2 of the Biandukou foci experimental area from 12:00-15:00 on Mar. 14, 2008. Observation items included: (1) the frost depth from 11:37-12:11 by the chopstick and the ruler. The soil was considered frozen when it was hard and with ice crystal. The cover type photos were archived. (2) the gravimetric soil moisture (soil samples from 0-1cm, 1-3cm, 3-5cm, 5-10cm and 10-20cm) by the microwave drying method. (3) the surface radiative temperature by the handheld infrared thermometer and the physical temperature by the thermocouple thermometer. (4) the soil roughness, which can be acquired from related dataset of other period.
CHANG Sheng, Fang Qian, QU Ying, LIANG Xingtao, LIU Zhigang, PAN Jinmei, PENG Danqing, REN Huazhong, ZHANG Yongpan, ZHANG Zhiyu, ZHAO Shaojie, Zhao Tianjie, ZHENG Yue, Zhou Ji, LIU Chenzhou, YIN Xiaojun, ZHANG Zhiyu
The dataset of ground truth measurement synchronizing with the airborne microwave radiometers (L&K bands) mission was obtained in the Biandukou foci experimental area from 8:25 to 11:15 BJT on Mar. 21, 2008. Observation items included: (1) microwave radiometer observations; (2) the surface radiative temperature by the handheld infrared thermometer and the physical temperature by the thermocouple thermometer; (3) the frost depth by the chopstick and the ruler. The soil was considered frozen when it was hard and with ice crystal; (4) Snow depth by the ruler; (5) the gravimetric soil moisture (soil samples from 0-1cm, 1-3cm and 3-5cm) by the microwave drying method. The volumetric moisture can be calculated by the gravimetric moisture and bulk density. The data can be opened by Microsoft Office. The sample point coordinates were also included.
CHANG Sheng, Fang Qian, QU Ying, LIANG Xingtao, LIU Zhigang, PAN Jinmei, PENG Danqing, REN Huazhong, ZHANG Yongpan, ZHANG Zhiyu, ZHAO Shaojie, Zhao Tianjie, ZHENG Yue, Zhou Ji, CHE Tao, LIU Chenzhou, YIN Xiaojun, ZHANG Zhiyu
The dataset of ground truth measurement synchronizing with MODIS was obtained in the Linze grassland foci experimental area on Jun. 2, 2008. Measurements were carried out twice at intervals of 125m in four quadrates (2km×2km), which were H01-H08, H09-H16, H17-H24 and H25-H32 respectively. Simultaneous ground data were mainly the canopy temperature, the half-height temperature, the land surface radiative temperature and the soil temperature (0-5cm) by the probe thermometer. For soil moisture, the soil temperature, soil moisture, the loss tangent, soil conductivity, and the real part and the imaginary part of soil complex permittivity were acquired by the POGO soil sensor, and soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring inNo.1 quadrats (H01-H08), No.2 (H09-H16) and No.3 (H17-H24); and in No.4 quadrat 4 (H25-H32), soil moisture, soil conductivity, the soil temperature, the real part of soil complex permittivity were acquired by WET, soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring. Complementary measurements were carried out on Jun. 3, 2008. The soil temperature, soil moisture, the loss tangent, soil conductivity, the real part and the imaginary part of soil complex permittivity were acquired by the POGO soil sensor, and soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring in H41-H48, H49-H56 and H57-H64; and in H33-H40, soil moisture, soil conductivity, the soil temperature, and the real part of soil complex permittivity were acquired by WET, soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring. Data were archived in Excel format. See WATER: Dataset of setting of the sampling plots and stripes in the Linze station foci experimental area for more information.
CHAO Zhenhua, NIAN Yanyun, WANG Xufeng, LIANG Wenguang
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in No. 1 and 2 quadrates of the A'rou foci experimental area on Oct. 18, 2007 during the pre-observation period. The Envisat ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:17 BJT. Both the quadrates were divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. 25 sampling points were chosen, including centers and corners of each subsites. Simultaneous with the satellite overpass, numerous ground data were collected, soil volumetric moisture, soil conductivity, the soil temperature, and the real part of soil complex permittivity by the WET soil moisture sensor; the surface radiative temperature by the hand-held infrared thermometer; soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). Meanwhile, vegetation parameters as height, coverage and water content were also observed. Surface roughness was detailed in the "WATER: Surface roughness dataset in the A'rou foci experimental area". Those provide reliable ground data for retrieval and validation of soil moisture and freeze/thaw status from active remote sensing approaches.
BAI Yunjie, HAO Xiaohua, LI Hongyi, LI Xin, LI Zhe
The dataset of ground truth measurements synchronizing with the airborne WiDAS mission was obtained in No. 1, 2 and 3 quadrates of the A'rou foci experimental area on Jul. 7, 2008. The quadrates were divided into 4×4 subsites, with each one spanning a 30×30 m2 plot. Observation items included: (1) spectrum of stellera, whin and pasture by ASD FieldSpec (350～2 500 nm) from BNU, with 20% reference board. Raw data were binary files direct from ASD (by ViewSpecPro), which were recorded daily in detail, and pre-processed data on reflectance were in .txt format. (2) photosynthesis of stellera , whin and pasture by LI-6400. The data were archived in Excel format. (3) surface temperature by the handheld infrared thermometer. 25 corner points of each subsite were chosen and acquisition time, the soil temperature measured three times and the land cover types were archived. Six files were included, the stellera spectrum of diverse coverage, spectrum data for 60% and 65% coverage, stellera photos, photosynthesis, the infrared temperature synchronizing with the airplane, and WiDAS images (resolution: 1.25m, 7.5m and 10m).
GE Yingchun, LI Hongyi, Qian Jinbo, WANG Yang, YU Yingjie
The dataset of ground truth measurement synchronizing with MODIS was obtained in C1, G1 and B2 of the Biandukou foci experimental area on Mar. 12, 2008. Observation items included: (1) the surface temperature by the handheld infrared thermometer in C1, G1 and B2 from 11:30 to 12:15. The underlying surface was the deep plowed land, the rape stubble and the grassland. (2) the gravimetric soil moisture (soil samples from 0-1cm, 1-3cm, 3-5cm, 5-10cm and 10-20cm) by the microwave drying method. (3) the frost depth by the chopstick and the ruler. The soil was considered frozen when it was hard and with ice crystal. The land cover type photos were archived. Four data files were archived, MODIS data, C1 (the land cover type, the surface temperature and the vegetation parameters), G1 ( the surface temperature, the frost depth and the soil moisture) and B2 (the surface temperature, the frost depth and the soil moisture) data.
CHANG Sheng, Fang Qian, QU Ying, LIANG Xingtao, LIU Zhigang, PAN Jinmei, PENG Danqing, REN Huazhong, ZHANG Yongpan, ZHANG Zhiyu, ZHAO Shaojie, Zhao Tianjie, ZHENG Yue, Zhou Ji, LIU Chenzhou, YIN Xiaojun, ZHANG Zhiyu, CHE Tao
The dataset of Land Surface Temperature (LST) observations was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas. (1) The time-continuous surface radiative temperature by the automatic thermometer (FOV: 10°; six from BNU with emissivity 0.95; two from Institute of Remote Sensing Applications with emissivity 1.00, observing at nadir at an intervals of one second. The maize canopy, the bare land and the wheat canopy in Yingke oasis maize field, the wheat canopy in Yingke oasis wheat field, the maize canopy in Huazhaizi desert maize field, vegetation and the bare land in Huazhaizi desert No. 1 and 2 plots and three intensive plots (Huazhaizi desert No. 3 plot, the barley field and the maize field near the resort) were measured on May 20, 24, 28, 30 and 31, Jun. 1, 3, 4, 16, 29 and 30, Jul. 1, 7, 9 and 11, 2008. The dataset of ground truth measurement was synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner), OMIS-II, TM, ASTER, MODIS, Hyperion and CHRIS. Diurnal variation in the radiative temperature was recorded as well. Raw data, blackbody calibrated data and processed data were archived in Excel format. (2) the surface radiative temperature by the handheld infrared thermometer (FOV:1°; accuracy: 0.1°C) in Yingke oasis maize field and wheat field, Huazhaizi desert maize field, No. 1 and 2 plots, and the maize field at the resort on May 20, 28, 30 and 31, Jun. 1, 4, 16 and 29, Jul. 4, 7 and 11, 2008. Besides, the four component temperature was also measured in Yingke oasis maize field and wheat field, Huazhaizi desert maize field. Raw data and processed data on the surface radiative temperature were archived.
CHAI Yuan, CHEN Ling, KANG Guoting, QIAN Yonggang, REN Huazhong, REN Zhixing, WANG Haoxing, WANG Tianxing, YAN Guangkuo, SHU Lele, Liu Qiang, XIA Chuanfu, XIN Xiaozhou, ZHOU Chunyan, SHEN Xinyi, LI Xinhui, YANG Guijun, LI Xiaoyu, HUANG Bo
The dateset of TIR (Patent No.: ZL 02 2 37640.2) emissivity measurements was obtained in No. 3 quadrate of the A'rou foci experimental area on Mar. 14, 2008. The observation site was covered with dry pasture with height less than 5cm, in which the center point of each grid was measured twice and was named in the form of A3-9 (number 9 point in No. 3 quadrate of A'rou). Each measurement was carried out at 45° and followed strictly the order: Tsky, Tcha, Tsm and Tcm. Meanwhile, the surface temperature was also acquired by the handheld infrared thermometer and the thermal imager (FLIR ThermaCAM). [emissivity=1- (Tcm^4 – Tsm^4)/ (Tcha^4 – Tsky^4)]. Those provide reliable data for retrieval and study of the surface temperature, and energy and radiation balance.
CAO Yongpan, GU Juan, LI Hua
The dataset of ground truth measurements synchronizing with ASTER was obtained in the saline plot B, the alfalfa plot D and the barley plot E of the Linze grassland foci experimental area on May 28, 2008. 49 points at intervals of 60m in each plot (360m×360m) were selected and observation items included: (1) the land surface radiative temperature by the hand-held infrared thermometer from east to west in the saline plot B, the alfalfa plot D and the alfalfa plot E. Each point was numbered, such as D22-23, indicating from No. 22 to 23 in the alfalfa plot D. In the salineplot B, 5 measurements were carried out each 5m; in the alfalfa plot D and the barley plot E, measurements were at random. Calibration information was archived in the hand-held infrared thermometer calibration.xls. (2) soil gravimetric moisture, volumetric moisture, and soil bulk density after drying measured by the cutting ring and the mean soil temperature from 0-5cm measured by the probe thermometer in plot B; the soil temperature, soil moisture, the loss tangent, soil conductivity, the real part and the imaginary part of soil complex permittivity measured by the POGO soil sensor, and the mean soil temperature from 0-5cm measured by the probe thermometer in plot D; soil moisture, soil conductivity, the soil temperature, and the real part of soil complex permittivity were measured by WET, and the mean soil temperature from 0-5cm by the probe thermometer in plot E. Six Excel files on soil moisture and the land surface radiative temperature in plot B, D and E were archived. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
CAO Yongpan, CHAO Zhenhua, GE Chunmei, HAN Xujun, HAO Xiaohua, HUANG Chunlin, LIANG Ji, MA Mingguo, WANG Shuguo, WU Yueru, FENG Lei, YU Fan
The dataset of ground truth measurements synchronizing with Landsat TM was obtained in the Linze grassland and Linze station foci experimental area on Sep. 23, 2007 during the pre-observation periods, and one scene was captured well. These data can provide reliable ground data for retrieval and validation of land surface temperatures with EO-1 Hyperion remote sensing approaches. Observation items included: (1) the land surface radiative temperature by the hand-held infrared thermometer, which was calibrated; (2) GPS by GARMIN GPS 76; (3) atmospheric parameters at Daman Water Management office measured by CE318 (produced by CIMEL in France). The total optical depth, aerosol optical depth, Rayleigh scattering coefficient, column water vapor in 936 nm, particle size spectrum and phase function were then retrieved from these observations. The optical depth in 1020nm, 936nm, 870nm, 670nm and 440nm were all acquired by CE318. These data include the raw data in .k7 format and can be opened by ASTPWin software. ReadMe.txt is attached for detail. Processed data (after retrieval of the raw data) in Excel contain optical depth, rayleigh scattering, aerosol optical depth, the horizontal visibility, the near surface air temperature, the solar azimuth, zenith, solar distance correlation factors, and air column mass number. (4) ground-based land surface temperature measurements by the thermal imager in the Heihe gobi, west of Zhangye city.
CHE Tao, BAI Yunjie, DING Songchuang, GAO Song, HAN Xujun, HAO Xiaohua, LI Hongyi, LI Xin, LI Zhe, LIANG Ji, PAN Xiaoduo, QIN Chun, RAN Youhua, WANG Xufeng, WU Yueru, YAN Qiaodi, ZHANG Lingmei, FANG Li, LI Hua, Liu Qiang, Wen Jianguang, MA Hongwei, YAN Yeqing, YUAN Xiaolong
The dataset of ground truth measurement synchronizing with the airborne microwave radiometers (L&K bands) mission was obtained in the Linze station foci experimental area on May 25, 2008. Observation items included: (1) soil moisture (0-5cm) measured once by the cutting ring method in the corner points of the 40 subplots of the west-east desert transit zone strip , three times in the corner points of the nine subplots of the north-south desert transit zone, once by the cutting ring and once by ML2X Soil Moisture Tachometer in the center points of nine subplots of the farmland quadrates. The preprocessed soil volumetric moisture data were archived as Excel files. (2) the surface radiative temperature by three handheld infrared thermometer (5# and 6# from Cold and Arid Regions Environmental and Engineering Research Institute, and one from Institute of Geographic Sciences and Natural Resources, which were all calibrated) in the west-east and north-south desert transit zone strip (various times synchronizing with the airplane), and Wulidun farmland quadrates (repeated twice at intervals of 15m from east to west). There are 34 sample points in total and each was repeated three times synchronizing with the airplane. Photos were taken. Data were archived as Excel files. (3) maize BRDF once by ASD Spectroradiometer (350～2 500 nm) from BNU, the reference board (40% before Jun. 15 and 20% hereafter), two observation platforms of BNU make and one of Institute of Remote Sensing Applications make in Wulidun farmland. Raw spectral data were archived as binary files, which were recorded daily in detail, and pre-processed data on reflectance were archived as text files (.txt). See the metadata record “WATER: Dataset of setting of the sampling plots and stripes in the Linze station foci experimental area” for more information of the quadrate locations.
DING Songchuang, GAO Song, PAN Xiaoduo, Qian Jinbo, WANG Yang, ZHU Shijie, LI Jing, XIAO Zhiqiang
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