(1) This data set contains a variety of heavy metal concentration data in multi-media, which is of great significance to explore the internal relationship between heavy metal pollution evaluation and heavy metal distribution in water; (2) The data source is to collect water, soil, crops and other samples from Huangshui River and its tributaries on the spot, send them to the laboratory for pretreatment, and complete the detection with relevant instruments; (3) The data set is of high quality and the sampling process is standardized. After collection, the samples are quickly stored in the - 4 ℃ refrigerator and sent to the laboratory for testing. The testing process is strictly carried out in accordance with relevant standards; (4) The data set can be mainly used for ecological risk and health risk assessment, spatial distribution analysis, source analysis, correlation analysis and so on.
ZHANG Fengsong
Road noise barriers (rnbs) are important urban infrastructure for building livable cities. However, the lack of large-scale and accurate geospatial data on rnbs hinders the rational urban planning, sustainable urban development and continuous improvement of urban environment. To solve this problem, this study proposes a geospatial artificial intelligence framework, which uses street view images to create vectorized RNB data sets in China. First, the road network of each city is intensively sampled based on OpenStreetMap as a geographical reference for downloading 6 million Baidu street view (BSV) images. In addition, a convolutional neural network containing image background information (ic-cnn) based on integrated learning strategy was also developed to detect RNB from BSV images. Subsequently, based on the identified RNB location, an RNB data set in the form of broken lines is generated, with a total length of 2667.02 kilometers and distributed in 222 cities. Finally, the quality of RNB data set is evaluated from two aspects: one is detection accuracy; Second, integrity and positioning accuracy. Based on a group of randomly selected samples containing 10000 BSV images, four quantitative indexes were calculated: the overall accuracy rate was 98.61%, the recall rate was 87.14%, the accuracy rate was 76.44%, and the F1 score was 81.44%. In addition, BSV images were used to conduct manual surveys on roads with a total length of 254 km in different cities to evaluate the mileage deviation and intersection ratio between the generated and surveyed rnbs: the root mean square error of mileage deviation was 0.08 km, and the intersection ratio was 88.08% ± 2.95%. The evaluation results show that the generated RNB data set is of high quality and can be used as an accurate and reliable data set for various large-scale urban studies.
CHEN Min
Photosynthetically active radiation (PAR) is fundamental physiological variable driving the process of material and energy exchange, and is indispensable for researches in ecological and agricultural fields. In this study, we produced a 35-year (1984-2018) high-resolution (3 h, 10 km) global grided PAR dataset with an effective physical-based PAR model. The main inputs were cloud optical depth from the latest International Satellite Cloud Climatology Project (ISCCP) H-series cloud products, the routine variables (water vapor, surface pressure and ozone) from the ERA5 reanalysis data, aerosol from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) products and albedo from Moderate Resolution Imaging Spectroradiometer (MODIS) product after 2000 and CLARRA-2 product before 2000. The grided PAR products were evaluated against surface observations measured at seven experimental stations of the SURFace RADiation budget network (SURFRAD), 42 experimental stations of the National Ecological Observatory Network (NEON), and 38 experimental stations of the Chinese Ecosystem Research Network (CERN). The instantaneous PAR was validated at the SURFRAD and NEON, and the mean bias errors (MBEs) and root mean square errors (RMSEs) are 5.6 W m-2 and 44.3 W m-2, and 5.9 W m-2 and 45.5 W m-2, respectively, and correlation coefficients (R) are both 0.94 at 10 km scale. When averaged to 30 km, the errors were obviously reduced with RMSEs decreasing to 36.3 W m-2 and 36.3 W m-2 and R both increasing to 0.96. The daily PAR was validated at the SURFRAD, NEON and CERN, and the RMSEs were 13.2 W m-2, 13.1 W m-2 and 19.6 W m-2, respectively at 10 km scale. The RMSEs were slightly reduced to 11.2 W m-2, 11.6 W m-2, and 18.6 W m-2 when upscaled to 30 km. Comparison with the other well-known global satellite-based PAR product of the Earth's Radiant Energy System (CERES) reveals that our PAR product was a more accurate dataset with higher resolution than the CRERS. Our grided PAR dataset would contribute to the ecological simulation and food yield assessment in the future.
TANG Wenjun
In August 2020, the forage supply and supplementary feeding of herdsmen in northern Tibet and Sanjiangyuan areas of Tibet were investigated. Northern Tibet includes 204 samples. The research areas include Dangxiong County of Lhasa City, seni District of Naqu City, Baqing County, Suo County, such as County, Jiali County, bango County, Ando County, NIMA County, Cuoqin County, Gaize County, Gar County, Ritu County, Pulan county and Zada county. The research indicators include contracted grassland area, grazing forbidden area, grass storage balance grassland area, number of livestock, etc. There are 224 survey samples of herdsmen in Sanjiangyuan area of Qinghai. The survey areas include Maqin County, Gande County, Maduo County, Jiuzhi County, Bama County, dari County of Golog Prefecture and paoqian County, Zaduo County, Yushu county and Chengduo County of Yushu prefecture. The research indicators include the quantity of purchased feed and self-produced feed raised by livestock.
FAN Yuzhi
The gridded desertification risk data of The Arabian Peninsula in 2021 was calculated based on the environmentally sensitive area index (ESAI) methodology. The ESAI approach incorporates soil, vegetation, climate and management quality and is one of the most widely used approaches for monitoring desertification risk. Based on the ESAI framework, fourteen indicators were chosen to consider four quality domains. Each quality index was calculated from several indicator parameters. The value of each parameter was categorized into several classes, the thresholds of which were determined according to previous studies. Then, sensitivity scores between 1 (lowest sensitivity) and 2 (highest sensitivity) were assigned to each class based on the importance of the class’ role in land sensitivity to desertification and the relationships of each class to the onset of the desertification process or irreversible degradation. A more comprehensive description of how the indicators are related to desertification risk and scores is provided in the studies of Kosmas (Kosmas et al., 2013; Kosmas et al., 1999). The main indicator datasets were acquired from the Harmonized World Soil Database of the Food and Agriculture Organization, Climate Change Initiative (CCI) land cover of the European Space Agency and NOAA’s Advanced Very High Resolution Radiometer (AVHRR) data. The raster datasets of all parameters were resampled to 500m and temporally assembled to the yearly values. Despite the difficulty of validating a composite index, two indirect validations of desertification risk were conducted according to the spatial and temporal comparison of ESAI values, including a quantitative analysis of the relationship between the ESAI and land use change between sparse vegetation and grasslands and a quantitative analysis of the relationship between the ESAI and net primary production (NPP). The verification results indicated that the desertification risk data is reliable in the Arabian Peninsula in 2021.
XU Wenqiang
This data set is based on the remote sensing monitoring data set of landuse status in China, Chinese Academy of Sciences, and the data of land use types of Qilian Mountain National Park in 1985 through cutting, splicing and other operations. Data production is the vector data generated by manual visual interpretation using Landsat TM / ETM Remote sensing images as the main data source. Landuse types include cropland, forest, shrub, grassland, wetland, water, tundra, impervious surface, bareland, glacier and permanent snow. We can analyze the historical landuse types in Qilian mountain area, and analyze the changes of land use types in Qilian mountain area combined with the current landuse type data.
NIAN Yanyun
1) Data content: the average zonal wind speed of 200 hPa and 850 hPa (reflecting the high and low-level westerly wind) and meridional wind speed of 850 hPa (reflecting the monsoon circulation) during the past millennium; 2) Data source: monthly data of the third phase of the international paleoclimate simulation and comparison program, processing method: multi-mode equal weight arithmetic average, climate average, 3) data application: used for the study of paleoclimate change and dynamic mechanism.
YAN Qing, JIANG Nanxuan, WANG Huijun
Lake surface water temperature (LSWT) at Xiashe station from 1967 to 2020; Lake ice depth and lake ice duration at Xiashe station from 1994 to 2020; Runoff at Buha station from 1956 to 2020; Lake level at Xiashe station from 1956 to 2020; Lake area from 1956 to 2020 estimated from the correlation constructed between lake area derived from Landsat images and lake level from gauge measurements in 2001−2020; Air temperature (T) at Gangcha station from 1958 to 2019; Precipitation (P) at Gangcha station from 1958 to 2019
ZHANG Guoqing
This data includes the land cover data of Central Asia, South Asia and Indochina Peninsula in the from 1992 to 2020 with a spatial resolution of 300mLand cover data includes 10 primary categories, which are combined from the secondary categories of the original data. The data source is the surface coverage product CCI-LC of ESA, where the spatial distribution of cropland, built-up land, and water for the land cover data from 1992 to 2020. Combined with the Tsinghua university global land cover data (FROM GLC, 30 m grid), NASA MODIS global land cover data (MCD12Q1, 500 m grid), the United States Geological Survey (USGS global land data (GFSAD30, 30 m), Japanese global forest data (PALSAR/PALSAR - 2, 25 m), the training sample dataset of land cover interpretation were built from the consistent areas of multiple products. The Google Earth Engine and random forest algorithm were used to correct the cropland, built-up land, and water of temporal CCI-LC data. Using the high resolution images in Google Earth at 2019 and 2020, the accuracy of change areas of cropland, built-up land, and water was validated by the stratified random sampling. A total of 3,600 land parcels were selected from 1,200 land parcels of the three land cover types, indicating that the accuracy of our corrected product increased in the range of 11% to 26% for the change areas compared to the CCI-LC product.
XU Erqi
1) Data content: this data is the carbon and nitrogen isotope data generated from the study of human bone collagen in Jiangxi tomb site, Jiyi Town, Wuding County, Yunnan Province. It can be used to preliminarily analyze the human diet structure of Jiangxi tomb site, Wuding county and reveal the life and career patterns of local ancient people. 2) Data source and processing method: provided by the environmental archaeology team of Lanzhou University and obtained by acid alkali acid experimental process and gas stable isotope mass spectrometer (Finnigan Deltaplus isotope ratio mass spectrometer). 3) Data quality: 9.38kb. 4) Data application achievements and prospects: the data are used to explore the research potential of stable isotopes of human bones at sites in revealing the development process of prehistoric career model in Yunnan.
1) Data content: the data are the ancient DNA data generated by studying the cultural layer of Klu lding site in Nyingchi region, Tibetan Plateau, including the hiseqx metagenomics data of 10 ancient DNA samples from 4 layers. It can be used to preliminarily analyze the changes of species composition recorded by ancient DNA in the sediments, and reveal the process of local agricultural development. 2) Data source and processing method: the research group has its ownership. the data were obtained by using pair-end library building and Illumina hiseqx sequencing platform. 3) Data quality: 20.3 MB, Q30 > 85%. 4) Application: The data will be used to explore the potential of the ancient DNA from archaeological sediments in revealing the development of ancient agriculture on the Tibetan Plateau.
YANG Xiaoyan
To describe the Qinghai Tibet Plateau and its surrounding areas We extracted total RNA from 15 Muscovy Duck brain, lung and liver tissues, 10 guinea fowl brain, heart and kidney tissues, 12 pig liver tissues, 8 pig muscle tissues and 45 dog brain, liver and spleen tissues, and used Illumina 2000 platform to carry out two terminal sequencing to obtain transcriptome Re sequenced data. This data set contains 1 data information sheet (Excel) and 90 transcriptome raw data (fastq). The data information sheet records the basic information such as sample collection time, collection place and sequencing time. It provides basic data for exploring the historical events of domestication, migration and expansion of main domestic animals in the pan third pole region, and further discusses the environmental adaptation mechanism of domesticated animals.
PENG Minsheng
To describe the Qinghai Tibet Plateau and its surrounding areas We extracted total DNA from 50 muscovy duck blood collected from Guangdong, Hainan, Zhejiang, Hunan and Guizhou provinces of China, carried out two-terminal sequencing using Illumina 2000 platform, and obtained 50 Muscovy Duck genome re sequencing data. This data set contains a data information table (Excel) and 50 genome raw data (fastq). The data information table records the basic information such as sample collection time, collection place and sequencing time. It provides basic data for exploring the historical events of Muscovy Duck domestication, migration and expansion in Pan third pole area, and further discusses the environmental adaptation mechanism of domesticated animals.
PENG Minsheng
This data set includes the PM2.5 mass concentration of atmospheric aerosol particles at Southeast Tibet station, Ali station, mostag station, Everest station and Namuco station (unit: mm) μ g/m3）。 Aerosol PM2.5 fine particles refer to particles with aerodynamic equivalent diameter less than or equal to 2.5 microns in the ambient air. It can be suspended in the air for a long time, which has an important impact on air quality and visibility. The higher its concentration in the air, the more serious the air pollution. The concentration characteristic data of PM2.5 is output at the frequency of obtaining a set of data every 5 minutes, which can realize the analysis of aerosol mass concentration at different time scales such as hour, day and night, season and interannual, which provides the analysis of changes and influencing factors of aerosol mass concentration at different locations in the Qinghai Tibet plateau at different time scales, as well as the evaluation of local air quality, It provides important data support. This data is an update of the published data set of PM2.5 concentration of aerosol particles at different stations on the Qinghai Tibet Plateau (2018 and 2019).
WU Guangjian
The Qinghai Tibet Plateau is one of the most challenging environments for human survival, known as the "third pole" of the earth. The average altitude is above 4000 meters, and the oxygen partial pressure at 4000 meters is only about 60% of sea level. High altitude hypoxia is a strong selective pressure for human survival. Exposure to high altitude hypoxia will increase the number of red blood cells (polycythemia) and the level of hematocrit (HCT). The genetic background of plateau Tibetans is single, and the long-term high-altitude environment has a positive selection effect on the genes related to plateau adaptation, resulting in stable linkage genetic differences in the related single nucleotide polymorphisms (SNPs) in different altitude gradients, which is suitable for studying the association between high-altitude adaptive phenotypes and genotypes. In this study, DNA microarray was used to compare the male whole genome microarray data of 150 Tibetan and non Tibetan East Asians in plateau. About 700000 loci (including nuclear genome, mitochondrial DNA and Y chromosome) were genotyped for each sample, and the differential SNPs, genes and signal pathways were analyzed, The molecular adaptive evolution characteristics of Tibetan men in plateau to adapt to high altitude hypoxic environment were detected. This data is helpful to analyze the genetic adaptability of Tibetan population from the perspective of nuclear genome. By comparing with the data of people around the plateau, we can comprehensively understand the adaptive evolution of plateau indigenous men. It provides basic genetic reference data for studying human and biological evolution, exploring the molecular differences between high and low altitude populations, the homologous relationship between populations in different geographical environments, and the role of hypoxia in gene selection.
KONG Qingpeng
This data set contains the data set of wild animal infrared stereo camera deployed in Hubao Park, Hunchun City, Yanbian Korean Autonomous Prefecture, Jilin Province. A total of 9 sets of wildlife infrared stereo cameras are deployed near Erdaogou in the tiger and leopard park. The stereo cameras are placed on trees and powered by batteries. The data acquisition time is from October 2019 to October 2020, with a total of 5.02g image data. The data is stored in the SD card inside the camera, part of which is transmitted through 700m network, and part of the data is stored in the internal memory card of the camera. Because there is no signal, the time of some images of the camera is January 1, 2000 as the starting time. The stereo camera uses infrared induction trigger to obtain wild animal images. The camera is in sleep for a long time. In this state, only the infrared sensor is in working state. When the sensor senses infrared thermal information, the stereo camera is aroused to take photos and collect. The size of the collected image sheet is 2592 × 1944。 1. Wild animals haunted at the installation site of Hunchun tiger and leopard park. When wild animals appear within the detection range of the stereo camera, acquisition and photographing are triggered once. 2. Data source: "development of terrestrial vertebrate monitoring equipment", 2016yfc0500104, completed by: Institute of semiconductors, Chinese Academy of Sciences, raw data, unprocessed. 3. The photo data is divided into a pair of effective data, including the left image and the right image. After correction, the left and right images can obtain the parallax map. According to the parallax map, the size information and distance information of the target of interest in the image can be obtained. Through the long-term analysis and research of the obtained animal size information. 4. This data can be used to record the population and body size of wild animals in a certain area, establish a real wild animal body size database, obtain the animal body size data information under different regions, ages and genders, and provide supporting data for wildlife research.
ZHOU Yan
This data set contains the data set of wildlife infrared stereo camera deployed in Qilian Mountain reserve, Zhangye City, Gansu Province. A total of 3 sets of stereo camera equipment are deployed near Sidalong in Qilian Mountain reserve. The coordinate positions are 38 ° 28 ′ 17 ″ n, 99 ° 53 ′ 53 ″ E and 3160m above sea level. The stereo camera is placed on the tree and behind the solar panel respectively, and the solar panel is used for power supply. The data acquisition time is August 2020, with a total of 82 images, including 42 pairs of left and right matching image pairs. The data acquisition method is to acquire the data parameters jointly with the UAV of Northwest Academy of Sciences of Chinese Academy of Sciences. Because the installation position is in the non signal area, other data are saved and not taken out from the internal memory card of the camera. The stereo camera uses infrared induction trigger to obtain wild animal images. The camera is in sleep for a long time. In this state, only the infrared sensor is in working state. When the sensor senses infrared thermal information, the stereo camera is aroused to take photos and collect. The size of the collected image sheet is 2592 × 1944, the data format is jpg. A pair of effective data includes the left and right images. After correction, the left and right images can obtain the parallax map. According to the parallax map, the size information and distance information of the target of interest in the image can be obtained. Through the long-term analysis and research of the obtained animal size information. 1. Wild animals haunted at the installation site of Hunchun tiger and leopard park. When wild animals appear within the detection range of the stereo camera, acquisition and photographing are triggered once. 2. Data source: "development of terrestrial vertebrate monitoring equipment", 2016yfc0500104, completed by: Institute of semiconductors, Chinese Academy of Sciences, raw data, unprocessed. 3. The photo data is divided into a pair of effective data, including the left image and the right image. After correction, the left and right images can obtain the parallax map. According to the parallax map, the size information and distance information of the target of interest in the image can be obtained. Through the long-term analysis and research of the obtained animal size information. 4. This data can be used to record the population and body size of wild animals in a certain area, establish a real wild animal body size database, obtain the animal body size data information under different regions, ages and genders, and provide supporting data for wildlife research.
ZHOU Yan
In order to master the species composition, floristic characteristics and host information of plateau agricultural and animal husbandry elephants and related natural enemy insects such as Coleoptera, Neuroptera and Diptera, establish a DNA bar code rapid identification system of plateau agricultural and animal husbandry natural enemy insects, evaluate the current situation of natural enemy resources, and put forward suggestions for the sustainable utilization of natural enemy insects. The sub project 2019qzkk05010606 carried out the investigation of natural enemy insect resources in key agricultural and pastoral areas, bulk crop related elephants, Coleoptera, Neuroptera and Diptera on the Qinghai Tibet Plateau, the construction of natural enemy insect species diversity database, and the evaluation of the current situation and sustainable utilization of natural enemy resources. During 2020, the Tibet Autonomous Region, the farming pastoral ecotone, the Farming Forestry ecotone, and the hinterland of farming and pastoral areas in Yunnan Province will carry out the investigation of key groups of natural enemy insects such as Coleoptera, Neuroptera and Diptera, collect samples, biological information and ecological environment information, systematically sort out the samples of natural enemy insects according to the standards and norms, and effectively preserve them, Carry out species morphological identification and obtain DNA bar code information, integrate species geographical distribution, host information, ecological pictures and other information, and build a natural enemy species diversity information database; Evaluate the current situation of natural enemy resources and put forward suggestions for sustainable utilization.
LIU Ning
In order to master the species composition, floristic characteristics and host information of plateau agricultural and animal husbandry elephants and related natural enemy insects such as Coleoptera, Neuroptera and Diptera, establish a DNA bar code rapid identification system of plateau agricultural and animal husbandry natural enemy insects, evaluate the current situation of natural enemy resources, and put forward suggestions for the sustainable utilization of natural enemy insects. The sub project 2019qzkk05010601 carried out the investigation of natural enemy insect resources in key agricultural and pastoral areas, bulk crop related elephants, Coleoptera, Neuroptera and Diptera on the Qinghai Tibet Plateau, the construction of natural enemy insect species diversity database, and the evaluation of the current situation and sustainable utilization of natural enemy resources. During 2020, the Tibet Autonomous Region, the farming pastoral ecotone, the Farming Forestry ecotone, and the hinterland of farming and pastoral areas in Yunnan Province will carry out the investigation of key groups of natural enemy insects such as Coleoptera, Neuroptera and Diptera, collect samples, biological information and ecological environment information, systematically sort out the samples of natural enemy insects according to the standards and norms, and effectively preserve them, Carry out species morphological identification and obtain DNA bar code information, integrate species geographical distribution, host information, ecological pictures and other information, and build a natural enemy species diversity information database; Evaluate the current situation of natural enemy resources and put forward suggestions for sustainable utilization.
QIAO Gexia
In order to analyze the animal diversity pattern of the Qinghai Tibet Plateau and establish the corresponding animal specimen database. The sub project 2019qzkk05010113 was concentrated in the West Tianshan Mountain of Xinjiang in 2021. A total of 200 specimens and tissue samples of local wild animals, such as common vole and Apodemus agrarius, were collected. The solid samples include 200 specimen information tables and 500 photos, such as animal individuals, skins and tissues. This data set includes 1 data set specification table, 1 specimen information table and 1 tissue sample information table. The sample information table contains basic sample information such as species, variety, detailed sampling place, sample type, collection time, collector and storage method, which is stored in the form of Excel. Photos, stored in JPG format.
JIANG Xuelong
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