1. Data overview The soil temperature monitoring point of the typical soil profile in the small basin of cucurbitou was set in the middle and lower part of the red mud ditch, and its geographical coordinates were 99 ° 52 '25.3 "E, 38 ° 15' 37.97" N. Soil Temperature was observed using HOBO Pendant® Temperature/Light Data Logger 64k-ua-002-64 Temperature recorder. 2. data content Soil temperature monitoring in typical soil profile of hongnigou is divided into seven layers, with depth distribution of 20cm, 40cm, 60cm, 80cm, 120cm, 160cm and 200cm.The frequency of observation is 1 time /15 minutes.The time range of observation data is from September 7, 2012 to May 6, 2013.
SUN Ziyong, CHANG Qixin
Based on the field survey results of this project, the previous hydrogeological survey results and the prediction and judgment of desert depressions, we obtained more than 600 known water level points in badain jaran desert and its surrounding areas, and drew a first-order approximate contour map of the groundwater level in badan jaran desert by using the measured or predicted groundwater level data.This isometric chart fills a gap in the study of groundwater in badain jaran desert. The so-called first-order approximation is the distribution of the macroscopic groundwater level, which reaches a resolution of 1 km on the spatial scale, and it is assumed that the groundwater level in the shallow and deep layers is the same, and the groundwater in the quaternary and bedrock distribution areas remains continuous.The error level of the first-order approximate contour is ± 10 m, which mainly comes from the uncertainty of ground elevation data. This data set contains a vector diagram of the groundwater level contour line and a raster data file.
WANG Xusheng, HU Xiaonong
This dataset contains three basic remote sensing data of digital topography (DEM), TM remote sensing image and NDVI vegetation index of badan jilin desert. 1. DEM, digital terrain data, from the SRTM1 data set released by NASA in the United States, was cropped in the desert area.The resolution is 30 m.The data is stored in the DEM folder, and the dm.ovr file can be opened by ArcGIS. 2. TM image data.The composite data of Landsat TM/ETM + 543 band released by NASA were cropped in the desert lake group distribution area.The resolution is 30 m.From 1990 to 2010, one scene was selected in summer and one scene in autumn every five years to analyze the long-term changes of the lake.In 2002, there was a scene for each quarter to analyze the changes of the lake during the year.The data is stored in TM folder, TIFF format, can be opened by ArcGIS or ENVI software.The file naming rule is yyyymm.tif, where yyyy refers to the year and mm to the month. For example, 199009 refers to the time corresponding to the impact data of September 1990. 3. NDVI, vegetation index.The modis-ndvi product MOD13Q1, released by NASA, was cropped in desert areas.The NDVI data of every ten days of the growing season (June, July, August and September) from 2000 to 2012 are included. The spatial resolution is 250 m and the temporal resolution is 16 days.Stored in NDVI folder, TIFF format, can be opened by ArcGIS or ENVI software.Mosaic_tmp_yyyyddd.hdfout.250m_16_days_ndvi_roi.tif, Where yyyy represents the year and DDD represents the day of DDD of the year.
JIN Xiaomei, HU Xiaonong
The Land Surface Temperature in China STC dataset contains land surface temperature data for China (about 9.6 million square kilometers of land) during the period of 2003-2017, in Celsius, in monthly temporal and 5600 m spatial resolution. It is produced by combing MODIS daily data(MOD11C1 and MYD11C1), monthly data(MOD11C3 and MYD11C3) and meteorological station data to reconstruct real LST under cloud coverage in monthly LST images, and then a regression analysis model is constructed to further improve accuracy in six natural subregions with different climatic conditions.
WANG Xusheng, HU Xiaonong
Groundwater is the main water source of desert riparian plants, and also the most important environmental factor affecting the normal physiological status of plants. In this project, an observation field was set up in Populus euphratica forest near the Alxa Desert eco hydrological experimental research station from 2011 to 2013 By manually measuring the groundwater depth every month in the year, it can provide basic data support for the study on the transpiration water consumption mechanism of Populus euphratica, and also can be used for the estimation of ecological water demand in the study area.
SI Jianhua
Sketch map of 1:50000 geological map of hulugou small watershed in 2012, hulugou watershed is composed of Quaternary loose stratum and pre Cenozoic bedrock stratum. The pores of the bedrock stratum are mainly fissures and covered with thin residual slope deposits. The Pleistocene alluvial proluvial sand gravel layer (q3al + PL) above the piedmont plain is dominant. The loose formation in the front of the glacier is Holocene moraine gravel layer (q4gl), which is distributed under the modern cirque and forms lateral moraine and final moraine dike (ridge).
SUN Ziyong, CHANG Qixin
According to the monthly temperature observation data of each conventional meteorological station in Heihe River basin set up by China Meteorological Administration, the annual air freeze-thaw index of each meteorological station is calculated, and then the annual average value of 1960-2004 is obtained. Finally, based on the regression relationship between the multi-year mean value of air freeze-thaw index and altitude of each meteorological station, and with the aid of 1 km DEM data, the spatial distribution map of air freeze-thaw index in Heihe River Basin is constructed.
ZHANG Tingjun
The land use / land cover data set of Heihe River Basin in 2011 is the Remote Sensing Research Office of Institute of cold and drought of Chinese Academy of Sciences. Based on the remote sensing data of landsatm and ETM in 2011, combined with field investigation and verification, a 1:100000 land use / land cover image and vector database of Heihe River Basin is established. The data set mainly includes 1:100000 land use graph data and attribute data in the upper reaches of Heihe River Basin. The land cover data of 1:100000 (2011) in Heihe River Basin and the previous land cover are classified into six first-class categories (cultivated land, forest land, grassland, water area, urban and rural residents, industrial and mining land and unused land) and 25 second-class categories by the same hierarchical land cover classification system. The data type is vector polygon and stored in shape format.
WANG Jianhua
The land use / land cover data set of Heihe River Basin in 2011 is the Remote Sensing Research Office of Institute of cold and drought of Chinese Academy of Sciences. Based on the remote sensing data of landsatm and ETM in 2011, combined with field investigation and verification, a 1:100000 land use / land cover image and vector database of Heihe River Basin is established. The data set mainly includes 1:100000 land use graph data and attribute data in the lower reaches of Heihe River Basin. The land cover data of 1:100000 (2011) in Heihe River Basin and the previous land cover are classified into six first-class categories (cultivated land, forest land, grassland, water area, urban and rural residents, industrial and mining land and unused land) and 25 second-class categories by the same hierarchical land cover classification system. The data type is vector polygon and stored in shape format.
WANG Jianhua
The land use / land cover data set of Heihe River Basin in 2011 is the Remote Sensing Research Office of Institute of cold and drought of Chinese Academy of Sciences. Based on the remote sensing data of landsatm and ETM in 2011, combined with field investigation and verification, a 1:100000 land use / land cover image and vector database of Heihe River Basin is established. The data set mainly includes 1:100000 land use graph data and attribute data in the middle reaches of Heihe River Basin. The land cover data of 1:100000 (2011) in Heihe River Basin and the previous land cover are classified into six first-class categories (cultivated land, forest land, grassland, water area, urban and rural residents, industrial and mining land and unused land) and 25 second-class categories by the same hierarchical land cover classification system. The data type is vector polygon and stored in shape format. Land cover classification attributes: Level 1 type level 2 type attribute code spatial distribution location Cultivated land: plain dry land 123 is mainly distributed in basin, piedmont, river alluvial, proluvial or lacustrine plain (poor irrigation conditions due to water shortage). The upland and land 122 is mainly distributed in the hilly area, and generally, the plot is distributed on the gentle slope of the hill, as well as on the top of the ridge and the base. The dry land 121 is mainly distributed in the mountainous area, the hillside (gentle slope, hillside, steep slope platform, etc.) and the Piedmont belt below 4000 m above sea level. Woodland: there are woodland (Arbor) 21 mainly distributed in high mountains (below 4000 meters above sea level) or middle mountain slopes, valley slopes, mountain tops, plains, etc. Shrub land 22 is mainly distributed in the higher mountain area (below 4500m), most of which are hillside, valley and sandy land. Sparse forest land 23 is mainly distributed in mountainous areas, hills, plains and sandy land, Gobi (Loamy, sandy conglomerate) edge. Other forest lands 24 are mainly distributed around the oasis ridge, riverside, roadside and rural residential areas. Grassland: high cover grassland 31 is generally distributed in mountainous area (gentle slope), hilly area (steep slope), river beach, Gobi, sandy land, etc. The middle cover grassland 32 is mainly distributed in dry areas (low-lying land next door and land between Sandy Hills, etc.). Low cover grassland 33 mainly grows in dry areas (loess hills and sand edge). Water area: channel 41 is mainly distributed in plain, inter Sichuan cultivated land and inter mountain valley. Lake 42 is mainly distributed in low-lying areas. Reservoir pond 43 is mainly distributed in plain and valley between rivers, surrounded by residential land and cultivated land. Glaciers and permanent snow cover 44 are mainly distributed on the top of (over 4000) mountains. The beach land 46 is mainly distributed in the valley, piedmont, plain lowland, the edge of river lake basin and so on. Residential land: urban land 51 is mainly distributed in plain, mountain basin, slope and gully platform. Rural residential land 52 is mainly distributed in oasis, cultivated land and roadside, tableland, slope, etc. Industrial and mining land and traffic land 53 are generally distributed in the periphery of cities and towns, more developed traffic areas and industrial mining areas. Unused land: sand 61 is mostly distributed in the basin, both sides of the river, the river bay and the periphery of the mountain front Gobi. Gobi 62 is mainly distributed in the Piedmont belt with strong wind erosion and sediment transport. Salt alkali 63 is mainly distributed in relatively low and easy to accumulate water, dry lakes and lakeside. Swamp 64 is mainly distributed in relatively low and easy to accumulate water. Bare soil 65 is mainly distributed in the arid areas (mountain steep slopes, hills, Gobi), and the vegetation coverage is less than 5%. Bare rock 66 is mainly distributed in the extremely dry stone mountain area (windy, light rain). The other 67 are mainly distributed in the exposed rocks formed by freezing and thawing over 4000 meters, also known as alpine tundra. Projection parameters: Projection ALBERS Units METERS Spheroid Krasovsky Parameters: 25 00 0.000 /* 1st standard parallel 47 00 0.000 /* 2nd standard parallel 105 00 0.000 /* central meridian 0 0 0.000 /* latitude of projection's origin 0.00000 /* false easting (meters) 0.00000 /* false northing (meters)
WANG Jianhua
This data comes from "China's 1:100000 land use data". China's 1:100000 land use data is constructed in three years based on LANDSAT MSS, TM and ETM Remote sensing data by means of satellite remote sensing, organized by 19 research institutes affiliated to the Chinese Academy of Sciences under the national macro survey and dynamic research on remote sensing of resources and environment, a major application project of the eighth five year plan of the Chinese Academy of Sciences. Using a hierarchical land cover classification system, this data divides the whole country into six first-class categories (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining land, residential land and unused land), and 31 second-class categories. This is the most accurate land use data product in China, which has played an important role in the national land resource survey, hydrological and ecological research.
LIU Jiyuan, ZHUANG Dafang, WANG Jianhua, WU Shixin, ZHOU Wancun
This data comes from "China's 1:100000 land use data". China's 1:100000 land use data is constructed in three years based on LANDSAT MSS, TM and ETM Remote sensing data by means of satellite remote sensing, organized by 19 research institutes affiliated to the Chinese Academy of Sciences under the national macro survey and dynamic research on remote sensing of resources and environment, a major application project of the eighth five year plan of the Chinese Academy of Sciences. Using a hierarchical land cover classification system, this data divides the whole country into six first-class categories (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining land, residential land and unused land), and 31 second-class categories. This is the most accurate land use data product in China, which has played an important role in the national land resource survey, hydrological and ecological research.
LIU Jiyuan, ZHUANG Dafang, WANG Jianhua, WU Shixin, ZHOU Wancun
This data comes from "China's 1:100000 land use data". China's 1:100000 land use data is constructed in three years based on LANDSAT MSS, TM and ETM Remote sensing data by means of satellite remote sensing, organized by 19 research institutes affiliated to the Chinese Academy of Sciences under the national macro survey and dynamic research on remote sensing of resources and environment, a major application project of the eighth five year plan of the Chinese Academy of Sciences. Using a hierarchical land cover classification system, this data divides the whole country into six first-class categories (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining land, residential land and unused land), and 31 second-class categories. This is the most accurate land use data product in China, which has played an important role in the national land resource survey, hydrological and ecological research.
LIU Jiyuan, ZHUANG Dafang, WANG Jianhua, WU Shixin, ZHOU Wancun
1. Data overview The data set of the base camp integrated environmental observation system is a set of ENVIS (IMKO, Germany) which was installed at the base camp observation point by qilian station.It is stored automatically by ENVIS data mining system. 2. Data content This data set is the scale data from January 1, 2012 to December 31, 2012.Including air temperature 1.5m, humidity 1.5m, air temperature 2.5m, humidity 2.5m, soil moisture 0cm, precipitation, wind speed 1.5m, wind speed 2.5m, wind direction 1.5m, geothermal flux 5cm, total radiation, surface temperature, ground temperature 20cm, ground temperature 40cm, ground temperature 60cm, ground temperature 80cm, ground temperature 120cm, ground temperature 160cm, CO2, air pressure. 3. Space and time scope Geographical coordinates: longitude: 99° 53’e;Latitude: 38°16 'N;Height: 2980.2 m
SI Jianhua
From 2012 to 2013, the geomorphic surface near the Zhengyi gorge in the middle reaches of the Heihe River was investigated, mainly including the 4-level river terrace. The data are mainly obtained through field investigation, and analyzed and mapped indoors to obtain the distribution map of geomorphic surface at all levels near the middle reaches of Zhengyi gorge.
HU Xiaofei, PAN Baotian
The dataset contains all individual glacial storage (unit: km3) over the Qinghai-Tibetan Plateau in 1970s and 2000s. It is sourced from the resultant data of the paper entitled "Consolidating the Randolph Glacier Inventory and the Glacier Inventory of China over the Qinghai-Tibetan Plateau and Investigating Glacier Changes Since the mid-20th Century". The first draft of this paper has been completed and is planned to be submitted to Earth System Science Data journal. The baseline glacier inventories in 1970s and 2000s are the Randolph Glacier Inventory 4.0 dataset, and the Glacier Inventory of China, respectively. Based on the individual glacial boundaries extracted from the above-mentioned two datasets, the grid-based bedrock elevation dataset (https://www.ngdc.noaa.gov/mgg/global/global.html, DOI: 10.7289/v5c8276m), and the glacier surface elevation obtained by a slope-dependent method, the individual glacier volumes in 1970s and 2000s are then calculated. In addition, the calculated results of individual glacier volumes in this study have been compared and verified with the existent results of several glacier volumes, relevant remote sensing datasets, and the global glacier thickness dataset based on the average of multiple glacier model outputs (https://www.research-collection.ethz.ch/handle/20.500.11850/315707, doi:10.3929/ethz-b-000315707), and the errors in the calculations have also been quantified. The established dataset in this study is expected to provide the data basis for the future regional water resources estimation and glacier ablation-involved researches. Moreover, the acquisition of the data also provides a new idea for the future glacier storage estimation.
HU Xiaofei, PAN Baotian
The dataset is the vector map of the administrative boundary of the Tarim River Basin, with a scale of 250,000 and projection: latitude and longitude. The data includes spatial data and attribute data, mainly the name and administrative code of the county boundary of the Tarim River Basin.
National Basic Geographic Information Center
The data is the distribution map of 100,000 deserts in the Tarim River Basin. This data uses 2000 TM images as the data source to interpret, extract and revise, and uses remote sensing and geographic information system technology in combination with the mapping requirements of 1: 100,000 scale to carry out thematic mapping of deserts, sands and gravelly Gobi. Data attribute table: area (area), perimeter (perimeter), ashm_ (sequence code), class (desert code), ashm_id (desert code), of which desert code is as follows: flowing sand 2341010, semi-flowing sand 2341020, semi-fixed sand 2341030, Gobi desert 2342000, saline-alkali land 2343000
WANG Jianhua
The data is a dataset of rivers in the Tarim River Basin. It is revised according to topographic maps and TM remote sensing images. The scale is 250,000. The data includes spatial data and attribute data. The attribute data fields are: HYD_CODE (river code), Name (river name), SHAPE_leng ( River length).
National Basic Geographic Information Center
The data is the boundary distribution map of the Tarim River Basin with a scale of 250,000. Projection: latitude and longitude. This data include spatial data and attribute data of the Tarim River Basin sub-watershed. The attribute data fields are: Area (area), Perimeter (perimeter), WRRNM (watershed name), WRRCD ( watershed coding)
WU Lizong
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