The data set contains the rare animal survey data for the Sanjiangyuan area from 2016 to 2017, including the latitude and longitude of the survey site, the length of the sample line, animal discovery time, animal names, quantity, location of the occurrence, type of habitat, affiliated families, etc.
HU Linyong, ZHANG Tongzuo, ZHANG Tongzuo,
The dataset was produced based on MODIS data. Parameters and algorithm were revised to be suitable for the land cover type in the Three-River-Source Regions. By using the Markov de-cloud algorithm, SSM/I snow water equivalent data was fused to the result. Finally, high accuracy daily de-cloud snow cover data was produced. The data value is 0(no snow) or 1(snow). The spatial resolution is 500m, the time period is from 2000-2-24 to 2018-12-31. Data format is geotiff, Arcmap or python+GDAL were recommended to open and process the data.
HAO Xiaohua
Monthly meteorological data of Sanjiangyuan includes 32 national standard meteorological stations. There are 26 variables: average local pressure, extreme maximum local pressure, date of extreme maximum local pressure, extreme minimum local pressure, date of extreme minimum local pressure, average temperature, extreme maximum temperature, date of extreme maximum temperature, extreme minimum temperature and date of extreme minimum temperature, average temperature anomaly, average maximum temperature, average minimum temperature, sunshine hours, percentage of sunshine, average relative humidity, minimum relative humidity, date of occurrence of minimum relative humidity, precipitation, days of daily precipitation >=0.1mm, maximum daily precipitation, date of maximum daily precipitation, percentage of precipitation anomaly, average wind speed, maximum wind speed, date of maximum wind speed, maximum wind speed, wind direction of maximum wind speed, wind direction of maximum wind speed and occurrence date of maximum wind speed. The data format is txt, named by the site ID, and each file has 26 columns. The names and units of each column are explained in the SURF_CLI_CHN_MUL_MON_readme.txt file. site_id lat lon elv name_cn 52754 37.33 100.13 8301.50 Gangcha 52833 36.92 98.48 7950.00 Wulan 52836 36.30 98.10 3191.10 Dulan 52856 36.27 100.62 2835.00 Qiapuqia 52866 36.72 101.75 2295.20 Xining 52868 36.03 101.43 2237.10 Guizhou 52908 35.22 93.08 4612.20 Wudaoliang 52943 35.58 99.98 3323.20 Xinghai 52955 35.58 100.75 8120.00 Guinan 52974 35.52 102.02 2491.40 Tongren 56004 34.22 92.43 4533.10 Togton He 56018 32.90 95.30 4066.40 Zaduo 56021 34.13 95.78 4175.00 Qumalai 56029 33.02 97.02 3681.20 Yushu 56033 34.92 98.22 4272.30 Maduo 56034 33.80 97.13 4415.40 Qingshui River 56038 32.98 98.10 9200.00 Shiqu 56043 34.47 100.25 3719.00 Guoluo 56046 33.75 99.65 3967.50 Dari 56065 34.73 101.60 8500.00 Henan 56067 33.43 101.48 3628.50 Jiuzhi 56074 34.00 102.08 3471.40 Maqu 56080 35.00 102.90 2910.00 Hezuo 56106 31.88 93.78 4022.80 Suo County 56116 31.42 95.60 3873.10 Dingqing 56125 32.20 96.48 3643.70 Nangqian 56128 31.22 96.60 3810.00 Leiwuqi 56137 31.15 97.17 3306.00 Changdu 56151 32.93 100.75 8530.00 Banma 56152 32.28 100.33 8893.90 Seda
WANG Xufeng, National Meteorological Information Center
The data set includes the sample survey data of alpine grassland and alpine meadow in Maduo County in September 2016. The sample size is 50cm × 50cm. The investigation contents include coverage, species name, vegetation height, biomass (dry weight and fresh weight), longitude and latitude coordinates, slope, aspect, slope position, soil type, vegetation type, surface characteristics (litter, gravel, wind erosion, water erosion, saline alkali spot, etc.), utilization mode, utilization intensity, etc.
ZHANG Zhijun, LI Fei, Fei Li, Zhijun Zhang
Iceberg calving, one of the key process of Antarctic mass balance, has been regarded as an important variable in fine monitoring the changes of ice shelves. The authors used multi-source remote sensing data near early August of each year from 2005 to 2020, including ENVISAT ASAR (WSM) images from 2005 to 2011, Terra/Aqua MODIS 7-2-1 band composite images from 2012 to 2014, Landsat-8 OLI 4-3-2 band composite images from 2013 to 2020, and Sentinel-1 SAR (EW) images from 2015 to 2020, to generate annual circum-Antarctic image mosaics after pre-processing. Next, combining MEaSUREs ice velocity dataset, grounding line, ice thickness dataset (Bedmap 2 and Bedmachine), spatial calculation and map digitization techniques were applied to extract all annual calving events larger than 1 km² that occurred on the Antarctic ice shelves from August 2005 to August 2020. Also, their area, thickness, mass and calving recurrence cycle were calculated to derive the annual iceberg calving dataset of the Antarctic ice shelves (2005-2020). This dataset contains the distribution of 15-year annual calving events, along with the attributes of each individual calving event including calving year, length, area, average thickness, mass, and recurrence interval. This dataset can directly reflect the magnitude characteristics and distribution of Antarctic iceberg calving in different years, which fills the gap of fine monitoring dataset of iceberg calving and provides fundamental data for subsequent research on calving mechanism and mass balance of Antarctic ice shelf-ice sheet system.
QI Mengzhen, LIU Yan, CHENG Xiao, HUI Fengming, CHEN Zhuoqi
Sanjiangyuan National Park includes three parks: the source of the Yangtze River, the source of the Yellow River and the source of the Lancang River, with a total area of 123100 square kilometers, which is between 89 ° 50'57 "- 99 ° 14'57" E and 32 ° 22'36 "- 36 ° 47'53" n, accounting for 31.16% of the land area of Sanjiangyuan. This dataset is based on the digital map of Sanjiangyuan National Park in the master plan of Sanjiangyuan National Park. The data includes the boundaries of the Yangtze River source Park, the Yellow River source Park and the Lancang River Park. The data format is ShapeFile. ArcMap is recommended to open data.
WANG Xufeng
The data set is a record of glacier distribution in Hoh Xil region, including three tables: the distribution of modern glaciers in various mountain areas in Hoh Xil region, the distribution of modern glaciers in various river basins in Hoh Xil region, and the distribution of modern glaciers in different mountain height segments in Hoh Xil region. Hoh Xil, located in the hinterland of the Qinghai Tibet Plateau, has an average altitude of more than 5000m and a very cold climate. According to the catalogue of China's glaciers and the author's re statistics on the 1 / 100000 topographic map, 437 modern glaciers are developed in the whole region, covering an area of 1552.39 square kilometers, with ice reserves of 162.8349 cubic kilometers, becoming an important source of water supply for many rivers and lakes in the region. Through this data set, we can know more about the distribution of glaciers in this area.
LI Bingyuan
This data set is based on the evaluation of existing land cover data and the evidence theory，including a 1:100,000 land use map for the year 20 2000、a 1:1,000,000 vegetation map、a 1:1,000,000 swamp-wetland map, a glacier map and a Moderate-Resolution Imaging Spectroradiometer land cover map for China in 2001 (MODIS2001) were merged，Finally, the decision is made based on the principle of maximum trust, and a new 1KM land cover data of China in 2000 with IGBP classification system is produced. The new land cover data not only maintain the overall accuracy of China's land use data, but also supplement the information of vegetation types and vegetation seasons in China's vegetation map, update China's wetland map, add the latest information of China's glacier map, and make the classification system more general.
RAN Youhua, LI Xin
This dataset contains 18 years (2002-2020) global spatio-temporal consistent surface soil moisture . The resolution is 36 km at daily scale, and the data unit is m3 / m3. This dataset adopts the soil moisture neural network retrieval algorithm developed by Yao et al. (2017). This study transfers the merits of SMAP to AMSR-E/2 through using an Artificial Neural Network (ANN) in which SMAP standard SSM products serve as training targets with AMSR-E/2 brightness temperature (TB) as input. Finally, long term soil moisture data are output. The accuracy is about 5% volumetric water content. (evaluation accuracy of 14 dense ground network globally.)
YAO Panpan, LU Hui
The Qinghai Tibet Plateau is a sensitive region of global climate change. Land surface temperature (LST), as the main parameter of land surface energy balance, characterizes the degree of energy and water exchange between land and atmosphere, and is widely used in the research of meteorology, climate, hydrology, ecology and other fields. In order to study the land atmosphere interaction over the Qinghai Tibet Plateau, it is urgent to develop an all-weather land surface temperature data set with long time series and high spatial-temporal resolution. However, due to the frequent cloud coverage in this region, the use of existing satellite thermal infrared remote sensing land surface temperature data sets is greatly limited. Compared with the daily 1 km spatial resolution all-weather land surface temperature data set (2003-2018) V1 in Western China released in 2019, this data set (V2) adopts a new generation method, namely satellite thermal infrared remote sensing reanalysis data integration method (RTM) based on the new land surface temperature time decomposition model. The main input data of the method are Aqua MODIS LST products and GLDAS data, and the auxiliary data include vegetation index and surface albedo provided by satellite remote sensing. This method makes full use of the high frequency and low frequency components of land surface temperature and the spatial correlation of land surface temperature provided by satellite thermal infrared remote sensing and reanalysis data. The evaluation results show that the land surface temperature data set has good image quality and accuracy, which is not only completely seamless in space, but also highly consistent with MODIS LST products widely used in the current academic circles in amplitude and spatial distribution. When MODIS LST was used as the reference value, the mean deviation (MBE) of the data set in daytime and nighttime was -0.28 K and -0.29 K respectively, and the standard deviation (STD) of the deviation was 1.25 K and 1.36 K respectively. The test results based on the measured data of six stations in the Qinghai Tibet Plateau and Heihe River Basin show that under clear sky conditions, the data set is highly consistent with the measured LST during the day / night, with R2 of 0.93 ~ 0.97 / 0.93 ~ 0.98; MBE of -0.42 ~ 0.25 K / - 0.35 ~ 0.19 K; RMSE of 1.03 ~ 2.28 K / 1.05 ~ 2.05 K; under non clear sky conditions, the MBE of the data set during the day / night is -0.55 ~ 1.42 K / - 0.46 ~ 1.27 K. The RMSE was 2.24-3.87 K / 2.03-3.62 K. Compared with the V1 version of the data, the two kinds of all-weather land surface temperature show the characteristics of seamless (i.e. no missing value) in the spatial dimension, and in most areas, the spatial distribution and amplitude of the two kinds of all-weather land surface temperature are highly consistent with MODIS land surface temperature. However, in the region where the brightness temperature of AMSR-E orbital gap is missing, the V1 version of land surface temperature has a significant systematic underestimation. The mass of trims land surface temperature is close to that of V1 version outside AMSR-E orbital gap, while the mass of trims is more reliable inside the orbital gap. Therefore, it is recommended that users use V2 version. The time span of this data set is from 2000 to 2019, and it will be updated continuously; the temporal resolution is twice daily (corresponding to the two transit times of aqua MODIS in the day and night respectively); the spatial resolution is 1 km. In order to facilitate the majority of colleagues to carry out targeted research around the Qinghai Tibet Plateau and its adjacent areas, and reduce the workload of data download and processing, the coverage of this dataset is limited to Western China and its surrounding areas (72 ° e-104 ° e, 20 ° n-45 ° n) with the Qinghai Tibet Plateau as the core. Therefore, this dataset is abbreviated as trims lst-tp (thermal and reality integrating medium resolution spatial seam LST – Tibetan Plateau) for user's convenience.
ZHANG Xiaodong, ZHOU Ji, TANG Wenbin, DING Lirong, MA Jin
The data set records the transaction price index of agricultural products in the agricultural market of Qinghai Province, and the data is divided by the transaction price index of agricultural products in the agricultural market. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of two data tables Transaction price index of agricultural products in agricultural trade market, 1998.xls, The transaction price index of agricultural products in the agricultural trade market, 1999.xls. The data table structure is the same. For example, the transaction price index of agricultural products in the agricultural trade market in 1998 has 10 fields: Field 1: grain Field 2: fine grain Field 3: coarse grain Field 4: Grease Field 5: meat, poultry and eggs Field 6: aquatic products Field 7: fresh vegetables Field 8: dried vegetables Field 9: fresh fruit Field 10: dried fruit
Qinghai Provincial Bureau of Statistics
The data set records the volume and value table of main export commodities of Qinghai Province (Xining customs), and the data is divided by the name of main export commodities of Qinghai Province (Xining customs). The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of three data tables Volume and value of main export commodities of the whole province (Xining customs) (1.xls, 1999), Table of import volume and value of main commodities of the whole province (Xining customs) (2.xls, 1999), The total import and export value of the whole province (Xining customs) in 1999.xls. The data table structure is similar. For example, the main export volume and value table of the whole province (Xining customs) has four fields in 1999 Field 1: commodity name Field 2: unit of measurement Field 3: quantity Field 4: value of goods
Qinghai Provincial Bureau of Statistics
The data set records the main economic statistical indicators of Qinghai Province in each month, and the data is divided according to the main economic statistical indicators of Qinghai Province in each month. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of two data tables The main economic statistical indicators of the whole province in 1999.xls, The main economic statistics index of the whole province in each month is 2000.xls. The data table structure is the same. For example, there are eight fields in the 1999 data table of the main economic statistics indicators of the whole province Field 1: Indicators Field 2: Unit Field 3: January Field 4: February Field 5: March Field 6: April Field 7: May Field 8: June Field 9: July Field 10: August Field 11: September Field 12: October Field 13: November Field 14: December
Qinghai Provincial Bureau of Statistics
The data set records the basic situation of major scientific and technological achievements registration in Qinghai Province, and the data is divided according to the basic situation of major scientific and technological achievements registration in Qinghai Province. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 21 data tables Basic information of major scientific and technological achievements registration in the whole province, 1998.xls Basic information of major scientific and technological achievements registration in the whole province, 1999.xls Basic information of major scientific and technological achievements registration in the whole province, 2000.xls Basic information of major scientific and technological achievements registration in the whole province, 2001.xls Basic information of major scientific and technological achievements registration in the whole province, 2002.xls Basic information of major scientific and technological achievements registration in the whole province, 2003.xls Basic situation of major scientific and technological achievements registration in the whole province, 2004.xls Basic information of major scientific and technological achievements registration 2004-2005.xls Registration of major scientific and technological achievements in the province 2005-2006.xls Registration of major scientific and technological achievements in the province 2006-2007.xls Basic information of major scientific and technological achievements registration in the whole province, 2008.xls Basic situation of major scientific and technological achievements registration in the whole province, 2009.xls Basic information of major scientific and technological achievements registration in the province 2010.xls Basic situation of major scientific and technological achievements registration in the whole province, 2011.xls Basic information of major scientific and technological achievements registration in the whole province, 2012.xls Basic information of major scientific and technological achievements registration in the whole province, 2013.xls Basic situation of major scientific and technological achievements registration in the whole province, 2014.xls Basic information of major scientific and technological achievements registration in the whole province, 2015.xls Basic information of major scientific and technological achievements registration in the whole province, 2016.xls Basic information of major scientific and technological achievements registration in the whole province, 2017.xls Basic information of major scientific and technological achievements registration in the whole province, 2018.xls The data table structure is the same. For example, the basic information of major scientific and technological achievements registration in the province in 2001 has five fields Field 1: Category Field 2: Total Field 3: Research Institution Field 4: colleges and Universities Field 5: Enterprise
Qinghai Provincial Bureau of Statistics
The data set records the situation of village level health organizations in Qinghai Province, and the data are divided by administrative districts and counties. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of three data tables The situation of rural health organizations in the whole province, 1998.xls, The situation of rural health organizations in the whole province, 1999.xls, The situation of rural health organizations in the whole province was analyzed in 2000.xls. The data table structure is the same. For example, there are four fields in the 1998 data sheet of rural health organizations in the whole province Field 1: Project Field 2: 1998 Field 3: Project Field 4: 1999
Qinghai Provincial Bureau of Statistics
The data set records the average wages of employees in other units of Qinghai Province by industry and region, and the data is divided by the average wages of employees in other units by industry and region. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of 8 data tables Average wages of employees in other units by industry 1985-2001.xls Average wages of employees in other units by industry 1985-2002.xls Average wages of employees in other units by industry 2003.xls Average wages of employees in other units by industry 2004.xls Average wages of employees in other units by industry 2005.xls Average wages of employees in other units by industry and region 2006.xls Average wages of employees in other units by industry and region 2007.xls The average wages of employees in other units by industry and region in 2008.xls. The data table structure is the same. For example, there are 10 fields in the data table of average wages of employees in other units by industry and region in 2006 Field 1: industry category Field 2: province total Field 3: Xining City Field 4: Haidong region Field 5: Haibei Prefecture Field 6: huangnanzhou Field 7: Hainan Field 8: Golog Field 9: Yushu prefecture Field 10: Haixi
Qinghai Provincial Bureau of Statistics
The data set records the elevation of the main tourist attractions in Qinghai Province, and the data is divided according to the main tourist attractions in Qinghai Province. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. There are 16 data sets Elevation of main tourist attractions in the province, 2002.xls The elevation of the main tourist attractions in the province, 2003.xls Elevation of main tourist attractions in the province 2004.xls Elevation of main tourist attractions in the province 2006.xls Elevation of main tourist attractions in the province 2007.xls Elevation of main tourist attractions 2007.xls Elevation of main tourist attractions in 2008.xls Elevation of main tourist attractions in 2009.xls Elevation of main tourist attractions 2010.xls Elevation of main tourist attractions 2011.xls Elevation of main tourist attractions 2012.xls Elevation of main tourist attractions 2013.xls Elevation of main tourist attractions in 2015.xls Elevation of major tourist attractions in 2016.xls Elevation of major tourist attractions 2017.xls Elevation of major tourist attractions in 2019.xls The data table structure is the same. For example, the elevation data table of major tourist attractions in the province (2003) has three fields: Field 1: name of tourist attraction Field 2: altitude (m) Field 3: geographic location
Qinghai Provincial Bureau of Statistics
The data set records the main economic benefit indexes of Qinghai Province, and the data are divided according to the main economic benefit indexes. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of three data tables Main economic benefit index 1985-1998.xls, Main economic benefit index 1985-1999.xls, The main economic benefit index is 1985-2000.xls. The data table structure is the same. For example, there are five fields in the business climate survey product sales climate index 2000-2001 data table Field 1: Indicators Field 2: Unit Field 3: 1985 Field 4: 1990 Field 5: 1995
Qinghai Provincial Bureau of Statistics
The data set records the output of main industrial products in Qinghai Province, and the data is divided according to the output of main industrial products. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set contains 28 data tables Output of main industrial products in Main Years 1952-1998.xls Main products 1952-1999 Output of main industrial products in Main Years 1952-2000.xls Output of main industrial products in Main Years 1952-2001.xls Output of main industrial products in Main Years 1952-2002.xls Output of main industrial products in Main Years 1952-2003.xls Output of main industrial products in Main Years 1952-2004.xls Output of main industrial products in Main Years 1978-2006.xls Output of main industrial products in Main Years 1978-2007.xls Output of main industrial products in Main Years 1978-2008.xls Output of main industrial products in Main Years 1978-2005.xls Output of main industrial products in Main Years 1990-2009.xls Output of main industrial products in Main Years 1990-2010.xls Total production of major industrial products 1998.xls Total production of major industrial products, 1999.xls Total production of major industrial products 2000.xls Output of main industrial products 2000-2001.xls Output of main industrial products 2001-2002.xls Output of main industrial products 2002-2003.xls Output of main industrial products 2004.xls Output of major industrial products in major years 2006-2011.xls Output of main industrial products in Main Years 2008-2013.xls Output of main industrial products in Main Years 2008-2014.xls Output of major industrial products in major years 2010-2015.xls Output of major industrial products in major years 2010-2016.xls Output of major industrial products in major years 2012-2017.xls Output of major industrial products in major years 2013-2018.xls The output of main industrial products in main years is 2008-2012.xls, and the data table structure is the same. For example, there are three fields in the data table of output of major industrial products from 2000 to 2001 Field 1: product name Field 2: 2000 Field 3: 2001
Qinghai Provincial Bureau of Statistics
The data set records the situation of special care and social relief in Qinghai Province, and the data is divided according to the situation of special care and social relief in Qinghai Province. The data are collected from the statistical yearbook of Qinghai Province issued by the Bureau of statistics of Qinghai Province. The data set consists of three data tables Special care and social relief in the whole province, 1998.xls, Special care and social relief in the whole province, 1999.xls, The situation of special care and social relief in the whole province was analyzed in 2000.xls. The data table structure is the same. For example, there are five fields in the data table of the province's preferential care and social relief in 1998 Field 1: preferential treatment object Field 2: Unit Field 3: Total Field 4: social relief target Field 5: Unit
Qinghai Provincial Bureau of Statistics
