China's land cover data set includes 5 products: 1) glc2000_lucc_1km_China.asc, a Chinese subset of global land cover data based on SPOT4 remote sensing data developed by the GLC2000 project. The data name is GLC2000.GLC2000 China's regional land cover data is directly cropped from global cover data. For data description, please refer to http : //www-gvm.jrc.it/glc2000/defaultGLC2000.htm 2) igbp_lucc_1km_China.asc, a Chinese subset of global land cover data based on AVHRR remote sensing data supported by IGBP-DIS, the data name is IGBPDIS; IGBPDIS data was prepared using the USGS method, using April 1992 to March 1992 The AVHRR data developed global land cover data with a resolution of 1km. The classification system adopts a classification system developed by IGBP, which divides the world into 17 categories. Its development is based on continents. Applying AVHRR for 12 months to maximize synthetic NDVI data, 3) modis_lucc_1km_China_2001.asc, a subset of MODIS land cover data products in China, the data name is MODIS; MODIS China's regional land cover data is directly cropped from global cover data, and its data description please refer to http://edcdaac.usgs.gov/ modis / mod12q1v4.asp. 4. umd_lucc_1km_China.asc, a Chinese subset of global land cover data based on AVHRR data produced by the University of Maryland, the data name is UMd; the five bands of UMd based on AVHRR data and NDVI data are recombined to suggest a data matrix, using Methodology carried out global land cover classification. The goal is to create data that is more accurate than past data. The classification system largely adopts the classification scheme of IGBP. 5) westdc_lucc_1km_China.asc, China ’s 2000: 100,000 land cover data organized and implemented by the Chinese Academy of Sciences, combined with Yazashi conversion (the largest area method), and finally obtained a land use data product of 1km across the country, data name WESTDC. WESTDC China's regional land cover data is based on the results of a 1: 100,000 county-level land resource survey conducted by the Chinese Academy of Sciences. The land use data were merged and converted into a vector (the largest area method). The Chinese Academy of Sciences resource and environment classification system is adopted. 2: Data format: ArcView GIS ASCII 3: Mesh parameters: ncols 4857 nrows 4045 xllcorner -2650000 yllcorner 1876946 cellsize 1000 NODATA_value -9999 4: 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)
RAN Youhua
This dataset contains five types of boundaries. 1. TPBoundary_ 2500m: Based on ETOPO5 Global Surface Relief, ENVI+IDL was used to extract data at an elevation of 2500m within the longitude (65~105E) and latitude (20~45N) range in the Tibetan Plateau. 2. TPBoundary_ 3000m: Based on ETOPO5 Global Surface Relief, ENVI+IDL was used to extract data at an elevation of 3000m within the longitude (65~105E) and latitude (20~45N) range in the Tibetan Plateau. 3. TPBoundary_ HF (high_frequency): This boundary is defined according to 2 previous studies. Bingyuan Li (1987) had a systematic discussion on the principles for determining the extent of the Tibetan Plateau and the specific boundaries. From the perspective of the formation and basic characteristics of the Tibetan Plateau, he proposed the basic principles for determining the extent of the Tibetan Plateau based on the geomorphological features, the plateau surface and its altitude, while considering the integrity of the mountain. Yili Zhang (2002) determined the extent and boundaries of the Tibetan Plateau based on the new results of research in related fields and years of field practice. He combined information technology methods to precisely locate and quantitatively analyze the extent and boundary location of the Tibetan Plateau, and concluded that the Tibetan Plateau in China extends from the Pamir Plateau in the west to the Hengduan Mountains in the east, from the southern edge of the Himalayas in the south to the northern side of the Kunlun-Qilian Mountains in the north. On April 14, 2017, the Ministry of Civil Affairs of the People's Republic of China issued the Announcement on Adding Geographical Names for Public Use in the Southern Tibetan Region (First Batch), adding six geographical names in the southern Tibetan region, including Wo’gyainling, Mila Ri, Qoidêngarbo Ri, Mainquka, Bümo La, and Namkapub Ri. ４. TPBoundary_ New (2021): Along with the in-depth research on the Tibetan Plateau, the improvement of multidisciplinary research and understanding inside and outside the plateau, and the progress of geographic big data and Earth observation science and technology, the development of the 2021 version of the Tibetan Plateau boundary data by Yili Zhang and et al. was completed based on the comprehensive analysis of ASTER GDEM and Google Earth remote sensing images. The range boundary starts from the northern foot of the West Kunlun Mountain-Qilian Mountain Range in the north and reaches the southern foot of the Himalayas and other mountain ranges in the south, with a maximum width of 1,560 km from north to south; from the western edge of the Hindu Kush Mountains and the Pamir Plateau in the west to the eastern edge of the Hengduan Mountains and other mountain ranges in the east, with a maximum length of about 3,360 km from east to west; the latitude and longitude range is 25°59′30″N~40°1′0″N, 67°40′37″E~104°40′57″E, with a total area of 3,083,400km2 and an average altitude of about 4,320m. Administratively, the Tibetan Plateau is distributed in nine countries, including China, India, Pakistan, Tajikistan, Afghanistan, Nepal, Bhutan, Myanmar, and Kyrgyzstan. ５. TPBoundary_ Rectangle: The rectangle was drawn according to the range of Lon (63~105E) and Lat (20~45N). The data are in latitude and longitude projection WGS84. As the basic data, the boundary of the Tibetan Plateau can be used as a reference basis for various geological data and scientific research on the Tibetan Plateau.
ZHANG Yili
The Three-River-Source National Park with an area of 123,100 km2 and include three sub regions, they are source region of the Yangtze River in the national park, source region of Yellow River in the national park and source region of Lancang River in the national park. The national park is located between longitude 89°50'57" -- 99°14'57", latitude 32°22'36" -- 36°47'53". It accounts for 31.16% of the total area of Three-River-Source region. This data set is generated by digitizing the location map of Three-River-Source national park in the comprehensive planning of Three-River-Source national park. The data include the boundary for the national park. Data format is Shapefile. Arcmap is recommended to open the data.
WANG Xufeng
The Three-River-Source National Park with an area of 123,100 km2 and include three sub regions, they are source region of the Yangtze River in the national park, source region of Yellow River in the national park and source region of Lancang River in the national park. The national park is located between longitude 89°50'57" -- 99°14'57", latitude 32°22'36" -- 36°47'53". It accounts for 31.16% of the total area of Three-River-Source region. This data set is generated by digitizing the location map of Three-River-Source national park in the comprehensive planning of Three-River-Source national park. The data include the boundary for the national park. Data format is Shapefile. Arcmap is recommended to open the data.
WANG Xufeng
Heihe river basin is the second largest inland river basin in China. In the past 30 years, a relatively perfect drainage observation system has been established in heihe river basin, which has become an important inland river research base in China.River basin is an important natural research unit, but the boundary of heihe river basin is not unified. In order to facilitate the use of data by users, we collected and sorted out 5 kinds of heihe river basin boundaries commonly seen in the literature: 1) from 1985 to 1986, China began to conduct systematic research on the heihe river basin as a whole. On the basis of basic investigation and a large number of data mastered, the early heihe river basin map was drawn with an area of 138,900 km ^ 2.The whole basin is divided into three hydrologic balance zones, which are: the balance zone of heihe main stream system, the balance zone of beida river main stream system and the balance zone of ma ying - feng leshan front water system. 2) sub project national key scientific research project of the ninth five-year plan "in heihe river basin water resources reasonable use and the economic society and ecological environment coordinated development research", considering the integrity of the county-level administrative units, on the basis of the first basin boundary using the administrative boundary of basin boundary was revised, formed the "digital heihe" published information system (http://heihe.westgis.ac.cn) of the heihe river basin boundary, watershed area of 128700 km ^ 2.The division of hydrological unit inherits the original idea and is divided into three river systems, namely the eastern river system, the central river system and the western river system. 3) in the comprehensive control plan of heihe river basin of the ministry of water resources, the area of heihe river basin is determined as 142,900 km ^ 2, and the hydrologic unit is divided into two independent water systems in the central and western regions and the east, with an area of 27,000 km2 and 116,000 km ^ 2 respectively. 4) in 2002-2006 in the national integrated water resources planning, "the Yellow River" (piece of) integrated water resources planning working group in 2005, the establishment "the northwest rivers and water resources and its exploitation and utilization of investigation evaluation report, briefly, to the secondary and tertiary area as the unit of water resources, to complete a series of natural geography and social economy statistical tables, maps and other data.In this comprehensive plan, the area of heihe river basin is about 151,700 km ^ 2, and the plan does not give a more detailed sub-watershed division plan. 5) based on the high-precision digital elevation model (SRTM and ASTER GDEM), the boundary of heihe river basin was determined by using the GIS hydrologic analysis method.The boundary has been verified by remote sensing and field investigation, and the present situation of modern water resources utilization is considered in the process of basin boundary determination and sub-basin division.
WU Lizong, WANG Jianhua, NIAN Yanyun
This data set includes the information of 21 conventional meteorological observation stations in Heihe River Basin and its surrounding areas, of which Wutonggou and Quixote stations have been cancelled in the 1980s, and other stations have operated since the establishment of the station. Station name, longitude and latitude 1. Mazong mountain 97.1097 41.5104 2. Yumen town 97.5530 39.8364 3. Wutonggou 98.3248 40.4697 4. Jiuquan 98.4975 39.7036 5. Jinta 98.9058 39.9988 6. Dingxin 99.5117 40.3080 7. Gaotai 99.7907 39.3623 8. Linze 100.165 39.1385 9. Sunan 99.6178 38.8399 10. Yeniugou 99.5830 38.4167 11. Tole 98.0147 39.0327 12. Ejina Banner 101.088 41.9351 13. Guaizi Lake 102.283 41.3662 14. Zhangye 100.460 38.9124 15. Shandan 101.083 38.7746 16. Folk music 100.826 38.4376 17. Alxa Right Banner 101.429 39.1407 18. Yongchang 101.578 38.1771 19. Qilian 100.238 38.1929 20. Gangcha 100.111 37.2478 21. Menyuan 101.379 37.2513 22. Gekkot 99.7063 41.9183 23. Jiayuguan 98.2241 39.7975
National Meteorological Information Center
Nighttime light remote sensing has been an increasingly important proxy for human activities including socioeconomics and energy consumption. Defense Meteorological Satellite Program-Operational Linescan System from 1992 to 2013 and Suomi National Polar-Orbiting Partnership-Visible Infrared Imaging Radiometer Suite since 2012 are the most widely used datasets. Despite urgent needs for long-term products and pilot explorations in synthesizing them, the publicly available long-term products are limited. We propose a Night-Time Light convolutional Long Short-Term Memory (NTLSTM) network, and apply the network to produce annual Prolonged Artificial Nighttime-light DAtaset (PANDA) in China from 1984 to 2020. Model assessments between modelled and original images show that on average the Root Mean Squared-Error (RMSE) reaches 0.73, the coefficient of determination (R2) reaches 0.95, and the linear slope is 0.99 at pixel level, indicating a high confidential level of the data quality of the generated product. In urban areas, the modelled results can well capture temporal trends in newly built-up areas but slightly underestimate the intensity within old urban cores. Socioeconomic indicators (built-up areas, Gross Domestic Product, population) correlates better with the PANDA than with previous products in the literature, indicating its better potential in finding different controls of nighttime-light variances in different phases. Besides, the PANDA delineates different urban expansion types, outperforms other products in representing road networks, and provides potential nighttime-light sceneries in early years. PANDA provides the opportunity to better bridge the cooperation between human activity observations and socioeconomic or environmental fields
ZHANG Lixian, REN Zhehao, CHEN Bin, GONG Peng, FU Haohuan, XU Bing
China 1:100000 data of land use is a major application in the Chinese Academy of Sciences "five-year" project "the national resources and environment remote sensing macroscopic investigation and study of dynamic organized 19 Chinese Academy of Sciences institute of remote sensing science and technology team, by means of satellite remote sensing, in three years based on Landsat MSS, TM and ETM remote sensing data established China 1:100000 images and vector of land use database.The main contents include: China 1:100,000 land use data;China 1:100,000 land use graph data and attribute data. The data was directly clipped from China's 1:100,000 land-use data.A hierarchical land cover classification system was adopted for the land use data of heihe basin of 1:100,000, and the whole basin was divided into 6 primary categories (arable land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 26 secondary categories.The data type is vector polygon, which is stored in Shape format.There are two types of data projection: WGS84/ALBERS;Data coverage covers the new heihe watershed boundary (lack of outer Mongolia data). Land use classification attributes: The first class type and the second class type attributes encode the spatial distribution position Cultivated paddy field 113 is mainly distributed in alluvial plain, basin and valley Cultivated paddy field 112 distributed in hilly valley narrow valley platform or beach (with irrigation conditions) Cultivated paddy field 111 is mainly distributed in mountain valley narrow valley platform or beach (with better irrigation conditions) Arable land 124 is mainly distributed in mountainous areas, the slope is generally more than 25 degrees (belongs to the steep slope hanging land), should be returned to forest. Cultivated dry land 123 is mainly distributed in basins, piedmont belts, river alluvial, diluvial or lacustrine plains (water shortage and poor irrigation conditions). Cultivated dry land 122 is mainly distributed in hilly areas (shaanxi, gan, ning, qing).In general, the plot is distributed on gentle slopes and x and sockets of hills. Arable land 121 is mainly distributed in the mountainous area, with an elevation of 4000 meters below the slope (gentle slope, mountainside, steep slope platform, etc.) and mountain front belt. Woodlands have woodlands (trees) 21 mainly distributed in the mountains (below 4000 meters above sea level) or in the slope, valley two slopes, mountain tops, plains.In qinghai nanshan, qilian mountains are. Woodland shrub 22 is mainly distributed in the higher mountain areas (below 4500 m), most of the distribution of hillside and valley and sand. Forest dredging 23 mainly distributed in the mountains, hills, plains and sandy land, gobi (soil, gravel) edge. Other woodlands 24 are mainly distributed in the oasis ridge, river, roadside and rural residential areas around. Grassland 31 is generally distributed in mountainous areas (gentle slopes), hills (steep slopes) and interriver beaches, gobi desert, sandy hills, etc. The covered grassland 32 is mainly distributed in dry places (next door low-lying land and sandy hills, etc.). Grassland low cover grassland 33 mainly grows in drier places (loess hills and sandy edges). The river channel 41 is mainly distributed in the plain, the cultivated land between the rivers and the valleys in the mountains. Water lakes are mainly distributed in low-lying areas. The reservoirs are mainly distributed in the intermountain lowlands and intersandy hills in qinghai province. Water area glaciers and permanent snow 44 mainly distributed in the plain, the valley between the river, there are surrounding residents and arable land. Waters and beaches are mainly distributed on the top of (over 4000) mountains.
WANG Jianhua, LIU Jiyuan
The land cover classification product is the second phase product of the ESA Climate Change Initiative (CCI), with a spatial resolution of 300 meters and a temporal coverage of 1992-2015. The spatial coverage is latitude -90-90 degrees, longitude -180-180 degrees, and the coordinate system is the geographic coordinate WGS84. The classification of the surface coverage is based on the Land Cover Classification System (LCCS) of the Food and Agriculture Organization of the United Nations. When the data are used for scientific research purposes, the ESA CCI Land Cover project should be acknowledged. In addition, the published article should be send to contact@esalandcover-cci.org.
XU Xiyan
"Heihe River Basin Ecological hydrological comprehensive atlas" is supported by the key project of Heihe River Basin Ecological hydrological process integration research. It aims at data arrangement and service of Heihe River Basin Ecological hydrological process integration research. The atlas will provide researchers with a comprehensive and detailed background introduction and basic data set of Heihe River Basin. Heihe River Basin water system map is one of the hydrological and water resources part of the atlas, with a scale of 1:2500000, positive axis isometric conic projection and standard latitude of 25 47 n. Data sources: river data of Heihe River Basin, reservoir distribution data of Heihe River Basin, residential area data of Heihe River Basin in 2009, administrative boundary data of one million Heihe River Basin in 2008, Lake data of Heihe River Basin and other basic geographic data. The upper reaches of Heihe River Basin are located in Qilian County, Haibei Tibetan Autonomous Prefecture, Qinghai Province, and the northern foot of Qilian Mountain in Zhangye, Jiuquan City, Sunan and Subei counties of Gansu Province. The middle reaches are located in Shandan, Minle, Ganzhou, Linze, Gaotai, Sunan, Suzhou, Jiayuguan and Yumen counties of Gansu Province. The lower reaches are located in Jinta, Gansu Province, Ejina Banner and Alxa Right Banner of Inner Mongolia, involving three provinces (autonomous regions), 16 cities and counties (District, banner), 56 towns, 45 townships and 4 Sumu. Table 1 shows the information about the administrative divisions of Heihe River Basin.
WANG Jianhua, ZHAO Jun, WANG Xiaomin, FENG Bin
The data set was produced based on the SRTM DEM data collected by Space Shuttle Radar terrain mission in 2016, the reference data such as river, lake and other water system auxiliary data , using the arcgis hydrological model to analyze and extract the river network. There are 12 sub-basins over the Tibet Plateau, including AmuDayra、Brahmaputra、Ganges、Hexi、Indus、Inner、Mekong、Qaidam、Salween、Tarim、Yangtze、Yellow. The outer boundary is based on the 2500-metre contour line and national boundaries.
ZHANG Guoqing
The Shiyang River Basin Information System thematic data set is one of the results of the technical assistance project “Optimization of Desertification Control in Gansu Province” assisted by the Asian Development Bank, including 5 folders including document, investigation_point, maps, photo, and spatial. Each file The folder contains several files. The document folder includes the target design, data processing, thematic summary report, and projection information.The gpspoint folder includes files recorded in shapefile point format sampled by gps according to different purposes.The maps folder contains Chinese, english, and fonts files. Folder, the first two folders represent 14 Chinese and English maps stored in A4 format and pdf format, and fonts contain some special fonts: the photo folder contains field survey digital photos stored in bmp format: spatial The folder contains the dem folder of the digital elevation model, the gansu folder of the outline map of Gansu Province and the Hexi Corridor, the generate folder of the site data file shapefile, the grid folder of the raster data of various geographic features, and the remote sensing image. image folder, meteoHydro folder for original site text data, and vector folder for vector data for various geographic features. The data includes: 1. DEM folder: 100m dem, hillshade, divided into GRID and geotif formats 2. Gansu folder: Gansu border, Hexi border 3. Grid folder: NDVI (vegetation index), lndchange (land transfer matrix), landscape86 (land landscape map in 86 years), landscape2k (land landscape map in 2000), Desertiftype (desert type landscape map), Desersevrt (desert type map ), Annprecip 4. Meteohydro folder: Minqin, Wuwei, Yongchang meteorological data (1) daily daily observation items: Airpress (humidity), Precipitation (radiation), Sunlight (sunlight), Temperature (temperature) ), Wind (wind speed) (2) Months (monthly): Airpress (air pressure), Humidity (humidity), Rain (precipitation), Sunlight (sunlight), Temperature (temperature), Wind (wind speed) (3) tendays: Airpress, Humidity, Rain, Sunlight, Temperature, Wind (4) years (year by year): Precipitation, Temperature 5. Vectro folder: (1) Admwhole (county boundary map), (2) Lake (lake), (3) Hydrasta (hydrological site), (4) Basin (watershed boundary), (5) Landscape2000 (land use 200 (Year), (6) landscape86 (land use 1986), (7) Meteosta (meteorological station), (8) Lakep (reservoir point), (9) Place (residential point), (10) Rainfallcontour (railway), ( 11) Rainfallcontour (rainfall contour map), (12) Road (highway), (13) Stream (water system map), (14) Town (county name), (15) Township (county township boundary), (16) Vegetation (vegetation map) Data projection information: PROJCS ["Albers", GEOGCS ["GCS_Krasovsky_1940", DATUM ["Not_specified_based_on_Krassowsky_1940_ellipsoid", SPHEROID ["Krasovsky_1940", 6378245.0,298.3]], PRIMEM ["Greenwich", 0.0], UNIT ["Degree", 0.0174532925199433]], PROJECTION ["Albers_Conic_Equal_Area"], PARAMETER ["False_Easting", 0.0], PARAMETER ["False_Northing", 0.0], PARAMETER ["longitude_of_center", 105.0], PARAMETER ["Standard_Parallel_1", 25.0], PARAMETER ["Standard_Parallel_2", 47.0], PARAMETER ["latitude_of_center", 0.0], UNIT ["Meter", 1.0]] For detailed data description, please refer to the data file
LI Xin
The global typhoon path data set contains the data of 29 typhoon path points in the Northwest Pacific in 2018, including time, longitude and latitude, central air pressure, wind speed and wind force, future direction, future speed, wind force level and other indicators; the data comes from the typhoon network of the Central Meteorological Station (http://typhone.nmc.cn/web.html), using Python to grab the typhoon path data published on the web page, In addition, the captured Excel data table is sorted into ShapeFile form, and each path point is given wind power level according to the wind power rating standard of typhoon; It can be applied to the analysis of the characteristics and influence of the movement of typhoon path points, wind speed and wind force.
CHEN Yiting, YANG Hua, WU Jianjun, ZHOU Hongmin
The Landuse/Landcover data of the Heihe River Basin in 2000 ( newly compiled in 2012), was finished by the Remote Sensing Laboratory of Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, using satellite remote sensing, based on the LandsaTM and ETM remote sensing data around 2000, combing field investigation and verification, thus leading to the establishment of the Heihe River Basin 1:10. 10,000 land use/land cover imagery and vector database. The main contents are: 1:100,000 land use graphic data and attribute data in the Heihe River Basin. The Heihe River Basin 1:100,000 (2011) land cover data and the previous land cover data use the same layered land cover classification system, the whole basin is divided into six first-class categories (cultivated land, woodland, grassland, waters, urban and rural residents, industrial and mining land and unused land), 25 secondary classes; data types are vector polygons, stored as Shape format. Land cover classification attributes: Primary type, secondary type, attribute coding, spatial distribution position Cultivated land: Plain dry land, 123, is mainly distributed in basin, Piedmont zone, river alluvial, diluvial plain or lacustrine plain (lack of water, irrigation condition is poor). Hilly dry land, 122, is mainly distributed in Hilly areas. Generally speaking, land blocks distribute on gentle slopes, ridges and mats of hills. Mountainous dry land, 121, is mainly distributed in mountainous areas, with the elevation below 4000 meters (gentle slope, mountainside, steep slope platform, etc.) and the Piedmont zones. Woodland: There is woodland (arbor), 21, is mainly distributed in the mountains (below 4000 meters ) or on the slopes of the mountains, valleys, hills, plains and so on. Shrub land, 22, is mainly distributed in higher mountain areas (below 4500 meters), most of which distribute in hillsides, valleys and sandy land. Sparse forest land, 23, is mainly distributed in the mountains, hills, plains and sandy land, and on the edge of the Gobi (loam, gravel). Other woodlands, 24, are mainly distributed in the oasis field, around rivers, roadsides and rural settlements. Grassland: Highly covered grassland, 31, is mainly distributed in mountainous areas (slow slopes), hills (steep slopes) and inter-river beaches, Gobi, sand dunes, etc. Mid-covered grassland, 32, is mainly distributed in relatively dry areas (Gobi, low-lying land and sandy land,sand dunes, etc.). The low-cover grassland, 33, grows mainly in drier areas (on the loess hills and on the edge of the sand). Waters: Channel, 41 is mainly distributed in plains, inter-river cultivated land and inter-mountain valleys. Lake, 42, is mainly distributed in low-lying areas. Reservoir pit, 43, is mainly distributed in plains and valleys between rivers, surrounded by residential areas and cultivated land. Glacier and permanent snow cover, 44, mainly distribute at the top of (over 4000) alpine regions. Flood land, 46, is mainly distributed in the high and low hillside gullies, the piedmont, the plain lowlands, and the edge of the river and lake basins. Residents land: Urban land, 51, is mainly distributed in plains, mountain basins, slopes and valleys. Rural residential land, 52, are mainly distributed in oases, cultivated land and roadsides, on the tablelands and the slopes. Industrial land and traffic land, 53, are generally distributed in the periphery of towns, areas with fairly developed transportation and industrial mining areas. Unutilized land: Sandy land, 61, is mostly distributed in the basin, on both sides of the river, in the river bay and on the periphery of the Piedmont and Gobi. Gobi, 62, is mainly distributed in the Piedmont belt with strong wind erosion and sediment transport. Saline and alkaline land, 63, is mainly distributed in dry lakes, lakeside and areas relatively low with easy water accumulation. Swamp, 64, is mainly distributed in relatively low areas with easy water accumulation. Bare soil, 65, is mainly distributed in arid areas (steep hillsides, hills and gobi), with vegetation coverage less than 5%. Bare rock, 66, is mainly distributed in extremely arid rocky mountainous areas (windy and rainless). The other, 67 mainly distributes in bare rocks formed by freezing and thawing above 4000 meters, also known as alpine tundra.
WANG Jianhua
The dataset of land use and land cover investigation was obtained in the arid region hydrology and forest hydrology experiment areas. It included: (1) Land cover investigations in Linze grassland, Yingke oasis, Huazhaizi desert, Dayekou watershed and Zhangye city from May 27 to 31, 2008. GPS data, photos and detailed descriptions were recorded. (2) Land use and land cover investigations in Yingke oasis, Huazhaizi desert and Biandukou foci experimental areas on Jul. 7, 8, 10, 11, 12, 13, 14 and 15, 2008. Data were archived in shapefile, spreadsheet or JPGE formats.
BAI Yanchen, LIU Zhigang, FU Zhuo, LI Bo, LIN Haobo, SONG Danxia, SUN Zhichao, GONG Hao, ZHU Man
1 km land cover map of heihe river basin is ran youhua et al. (2009;2011) develop a subset of China's 1 km land cover map (MICLCover) incorporating multi-source local information.The MICLCover land cover map adopts the IGBP land cover classification system, based on the evidence theory, which integrates the 1:100,000 land use data of China in 2000, the vegetation pattern of China vegetation atlas (1:100,000), the 1:100,000 glacier distribution map of China, the 1:100,000 swamp wetland map of China and the land cover product of MODIS in 2001 (MOD12Q1).The verification results of MICLCover showed that the overall consistency of MICLCover and China's land use map reached 88.84% on the level of 7 categories. Among them, the consistency of cultivated land, city, wetland and water type reached more than 95%.Through visual comparison with the land cover data product of MODIS2001 and IGBPDISCover land cover map in three typical areas, MICLCover keeps the overall accuracy of China's land use map and increases the leaf attribute and leaf shape information of China's vegetation map, while reflecting more detailed local land cover details.Using the national forest resources survey data, the verification results in gansu, yunnan, zhejiang, heilongjiang and jilin provinces showed that the accuracy of forest types of MICLCover was significantly improved compared with that of MODIS land cover products.The forest type of MICLCover was verified with the forest resource survey data of qilian mountain national nature reserve administration of gansu province. The results showed that the accuracy of MICLCover forest type in this area was 82.94%. Anyhow, MICLCover land cover map while maintaining the overall precision of the Chinese land use data condition, supplement the vegetation map of China on vegetation types and vegetation season phase information, update the Chinese wetland figure, Chinese ice figure the latest information, the accuracy of China's land cover data is greatly improved, more general classification system, the data can provide higher precision for land surface process model of land cover information.
RAN Youhua, LI Xin
The data set include crop leaf stomatal conductance observed at four sample regions, that is the soil moisture control experimental field at Daman county, and the super station, and Shiqiao sample plots at Wuxing village in Zhangye city. 1) Objective Crop leaf stomatal conductance, a key biophysical parameter, was observed as model parameter or a priori knowledge for crop growth model, or evapotranspiration estimation. 2) Measuring instruments Leaf porometer. 3) Measuring site a. the soil moisture control experimental field at Daman county, Twelve soil water treatments are set. The crop leaf stomatal conductance for each treatment is measured on 17, 23 and 29 May, and 3, 9, 14 and 24 June, and 5 and 12 July. b. the Super Station The crop leaf stomatal conductance at the super station is measured on 22 and 28 May, 5, 11, 18, and 25 June, and 1, 8, 15, 22 and 31 July, 9, 15 and 22 August, and 3 and 11 September. c. the Shiqiao sample site The crop leaf stomatal conductance at the Shiqiao village is measured on 17, 22 and 28 May, 4, 11, 17 and 25 June, 1, 8, 15, 22, and 30 July, 8, 16 and 27 August, and 9 September. 4) Data processing The observational data was recorded in the sheets and reorganized in the EXCEL sheets. The time used in this dataset is in UTC+8 Time.
Xu Fengying, Wang Jing, Huang Yongsheng, LI Xin, MA Mingguo
The project “The impact of the frozen soil environment on the construction of the Qinghai-Tibet Railway and the environmental effects of the construction” is part of the “Environmental and Ecological Science in West China” programme supported by the National Natural Science Foundation of China. The person in charge of the project is Wei Ma, a researcher at the Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences. The project ran from January 2002 to December 2004. Data collected in this project included the following: Monitoring data of the active layer in the Beiluhe River Basin (1) Description of the active layer in the Beiluhe River Basin (2) Subsurface moisture data from the Beiluhe River Basin, 2002.9.28-2003.8.10 (Excel file) * Site 1 - Grassland moisture data * Site 2 – Removed turf moisture data * Site 3 - Natural turf moisture data * Site 4 - Gravel moisture data * Site 5 - Insulation moisture data (3) Subsurface temperature data from the Beiluhe River Basin, 0207-0408 Excel file * Temperature data for the ballast surface * Temperature data for insulation materials * Temperature data for a surface without vegetation * Temperature data for a grassland surface * Temperature data for a grit and pebble surface Data on the impact of construction on the ecological environment were obtained at Fenghuoshan, Tuotuohe, and Wudaoliang. Sample survey included plant type, abundance, community coverage, total coverage, aboveground biomass ratio and soil structure. The moisture content at different depths of the soil was detected using a time domain reflectometer (TDR). A set of soil samples was collected at a depth of 0-100 cm at each sample site. An EKKO100 ground-penetrating radar detector was used to continuously sample 1-1.5 km long sections parallel to the road to determine the upper limit depth of the frozen soil. 3. Predicted data: The temperature of the frozen soil at different depths and times was predicted in response to temperature increases of 1 degree and 2 degrees over the next 50 years based on initial surface temperatures of -0.5, -1.5, -2.5, -3.5, and -4.5 degrees. 4. The frozen soil parameters of the Qinghai-Tibet Railway were as follows: location, railway mileage, total mileage (km), frozen soil type mileage, mileage of zones with an average temperature conducive to permafrost, frozen soil with high temperatures and high ice contents, frozen soils with high temperatures and low ice contents, frozen soils with low temperatures and high ice contents, frozen soils with low temperatures and low ice contents, and melting area.
MA Wei, WU Qingbai
This data was derived from "1: 100,000 Land Use Data of China". Based on Landsat MSS, TM and ETM remote sensing data, 1: 100,000 Land Use Data of China was compiled within three years by a remote sensing scientific and technological team of 19 research institutes affiliated to the Chinese Academy of Sciences, which was organized by the “Remote Sensing Macroinvestigation and Dynamic Research on the National Resources and Environment", one of the major application programs in Chinese Academy of Sciences during the "Eighth Five-year Plan". This data adopts a hierarchical land cover classification system, which divides the country into 6 first-class categories (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 31 second-class categories. This is the most accurate land use data product in our country at present. It has already played an important role in national land resources survey, hydrology and ecological research.
LIU Jiyuan, ZHUANG Dafang, WANG Jianhua, ZHOU Wancun, WU Shixin
The data was directly clipped from China's 1:100,000 land-use data.China 1:100000 data of land use is a major application in the Chinese Academy of Sciences "five-year" project "the national resources and environment remote sensing macroscopic investigation and study of dynamic organized 19 Chinese Academy of Sciences institute of remote sensing science and technology team, by means of satellite remote sensing, in three years based on Landsat MSS, TM and ETM remote sensing data established China 1:100000 images and vector of land use database.A hierarchical land cover classification system was adopted for the land use data of heihe basin of 1:100,000, and the whole basin was divided into 6 primary categories (arable land, forest land, grassland, water area, urban and rural areas, industrial and mining areas, residential land and unused land) and 26 secondary categories.The data type is vector polygon, which is stored in Shape format.There are two types of data projection: WGS84/ALBERS;Data coverage covers the new heihe watershed boundary (lack of outer Mongolia data).
LIU Jiyuan, WANG Jianhua
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