Ⅰ. Overview This data set is based on Landsat MSS, TM and ETM Remote sensing data by means of satellite remote sensing. Using a hierarchical land cover classification system, the data divides the whole region into six first-class classifications (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining land, residential land and unused land), and 31 second-class classifications. Ⅱ. Data processing description The data set is based on Landsat MSS, TM and ETM Remote sensing data as the base map, the data set projection is set as Alberts equal product projection, the scale is set at 1:24,000 for human-computer interactive visual interpretation, and the data set storage form is ESRI coverage format. Ⅲ. Data content description The data set adopts a hierarchical land cover classification system, which is divided into 6 first-class classifications (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining land, residential land and unused land), and 31 second-class classifications. Ⅳ. Data use description The data can be mainly used in national land resources survey, climate change, hydrology and ecological research.
XUE Xian, DU Heqiang
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, ZHOU Wancun, WU Shixin
Land use and land cover map of Amu river Basin includes four periods: 1990, 2000, 2010 and 2015. The data produced by the key laboratory of remote sensing and GIS, Xinjiang institute of ecology and geography, Chinese Academy of Sciences, the spatial resolution of data is 30 m. Data production Supported by the Strategic Priority Research Program of Chinese Academy of Sciences, Grant No. XDA20030101. The land use map of Amu river basin is based on Landsat TM and ETM image data in 1990, 2000, 2010 and 2015. Firstly, with the help of eCognition software, the object-oriented classification is carried out. Secondly, the classification results are checked and corrected manually. Finally, the data validation methods are field validation and high-precision image validation.
XU Wenqiang
This data is from "China 1:100,000 land use data".China 1:100,000 land use data was constructed in three years based on Landsat MSS, TM and ETM remote sensing data by using satellite remote sensing as a means to organize remote sensing science and technology teams from 19 institutes affiliated to the Chinese academy of sciences (cas) in the "eighth five-year plan" major application project "national macro survey and dynamic research on remote sensing of resources and environment".The land use data of guizhou province adopts a hierarchical land cover classification system, which divides the country 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 31 secondary categories.It is the most accurate land use data product in China and has played an important role in national land resource survey, hydrological and ecological research.
LIU Jiyuan, ZHUANG Dafang, WANG Jianhua, WU Shixin, ZHOU Wancun
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 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
This data set is one of the results of the project "Determination of Cultivated Land Use Coefficient and Land Use Change Research in Zhangye City". It is a land use database in Zhangye City based on Landsat TM and ETM remote sensing data. The land use data adopts a hierarchical land cover classification system, which divides the land use types of Zhangye City into 6 first-class categories (cultivated land, forest land, grassland, water area, land for urban and rural industrial and mining residents and unused land) and 25 second-class categories. The data range includes Shandan, Minle, Linze, Gaotai, Sunan Yugu Autonomous County and Ganzhou District. The classification standard adopts the land use classification standard used by the Chinese Academy of Sciences since 1986. The data type is vector polygon and stored in Shape format. The data range covers Zhangye City.
HU Xiaoli, WANG Jianhua, LI Xin
This data is SWAT scenario simulation data in the middle and upper reaches of Heihe River Basin. Scenarios include historical trend scenario (HT), ecological protection scenario (EP), strict ecological protection scenario (SEP), economic development scenario (ED) and rapid economic development scenario (red). Firstly, the dyna_clue model is used to simulate the land use change under different scenarios, and then the simulated land use map under different scenarios is imported into the SWAT model to simulate the daily and monthly runoff scenario data of the upstream outlet (Yingluo gorge) and the middle outlet (Zhengyi gorge) of the Heihe River Basin (assuming other conditions are the same). The period is 2011-2030. The data format is excel.
NAN Zhuotong, ZHANG Ling
This data is from "China 1:100,000 land use data".China 1:100,000 land use data was constructed in three years based on Landsat MSS, TM and ETM remote sensing data by using satellite remote sensing as a means to organize remote sensing science and technology teams from 19 institutes affiliated to the Chinese academy of sciences (cas) in the "eighth five-year plan" major application project "national macro survey and dynamic research on remote sensing of resources and environment". In 1995, guizhou province adopted a hierarchical land cover classification system, which divided the country 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 31 secondary categories.It is the most accurate land use data product in China and has played an important role in national land resource survey, hydrological and ecological research.
LIU Jiyuan, ZHUANG Dafang, WANG Jianhua, ZHOU Wancun, WU Shixin
Part of the data of resources and environment in Zhangye City from 2001 to 2012, including: per capita cultivated land area, per capita forest land area, per capita grassland area, forest coverage, land productivity, unused land occupation rate
ZHANG Dawei
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 main contents include: 1:100000 land use graph data and attribute data 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. This data respects the opinion of the data author, and cannot share the whole basin data temporarily. Please indicate the research scope and exact purpose on the data application.
WANG Jianhua
The data set is obtained by UAV aerial photography during five field visits to the Qinghai Tibet Plateau in 2018-2019. The data size is 77.6 GB, including more than 11600 aerial photos. The aerial film was shot in five times, from July 19, 2018 to July 26, 2018, September 9, 2018 to September 16, 2018, April 24, 2019 to May 10, 2019, July 6, 2019 to July 20, 2019, September 1, 2019 to September 7, 2019. The shooting location mainly includes the roads and surrounding areas between major cities in Lhasa, shigaze, Naqu, Shannan, Linzhi, Changdu, Diqing, Ganzi, ABA, Gannan and Golog. The aerial photos clearly reflect the local land use / cover type, vegetation distribution, grassland degradation, vegetation coverage, river and lake distribution and other information. The aerial photos have longitude and latitude and altitude information, which can provide better verification information for the remote sensing interpretation of land use / cover, and also can be used for the estimation of vegetation coverage, and for the study of land use in the study area Good reference information is provided.
LV Changhe, LIU Yaqun
This dataset subsumes sustainable livestock carrying capacity in 2000, 2010, and 2018 and overgrazing rate in 1980, 1990, 2000, 2010, and 2017 at county level over Qinghai Tibet Plateau. Based on the NPP data simulated by VIP (vehicle interface process), an eco hydrological model with independent intellectual property of the institute of geographic sciences and nature resources research(IGSNRR), Chinese academy of Sciences(CAS), the grass yield data (1km resolution) is obtained. Grass yield is then calculated at county level, and corresponding sustainable livestock carring capacity is calculated according to the sustainable livestock capacity calculation standard of China(NY / T 635-2015). Overgrazing rate is calculated based on actual livestock carring capacity at county level.The dataset will provide reference for grassland restoration, management and utilization strategies.
MO Xingguo
The gridded desertification risk data in Central-Western Asia 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 1km 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 Central-Western Asia.
XU Wenqiang
This dataset contains cultivated land and impermeable surface products in Qilian Mountain key Area from 1990 to 2015 every 5 years. The dataset came from land cover products in Qilian Mountain key Area.
YANG Aixia
This data set is the data set of land resource elements in the Qinghai Tibet Plateau from 1990 to 2015. It records the change of land use proportion of 15 built-up areas of prefecture level units in Qinghai and Tibet every five years. The data is excel file, and the spatial resolution is the scale of prefecture level administrative unit. This data is based on the land use type data of the Qinghai Tibet Plateau, and is obtained by calculating the proportion of the built-up area in the area of each grade unit to the area of the grade unit. The data set can be used to study the spatial pattern, development process and evolution mechanism of the urbanization of the Qinghai Tibet Plateau, and provide data support for the study of the impact of the urbanization of the Qinghai Tibet Plateau on the ecological environment.
DU Yunyan, YI Jiawei
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
1) Data content: Vector data of urban built-up areas in 65 countries of the pan-third pole region from 1992 to 2015. 2) Data source and processing method: Based on the global land cover data of the 300-meter resolution of the ESA JCR from 1992 to 2015, we integrated the global urban land use data of Gong Peng, Liu Xiaoping and Chen Jun to obtained a correction data set. 3) Data quality description: The accuracy of data in 65 countries is about 75%, and there may be differences in data accuracy in different regions. 4) Data application results and prospects: It can be used for urbanization related research in 65 countries in the Pan-Third region, such as urban land expansion analysis and future scenario simulation.
LI Guangdong
Based on high-resolution satellite images of Google earth of theTibetan plateau, facility agricultural land in the whole region in 2018 was obtained through visual interpretation.The video shooting time was concentrated from November, 2017 to November, 2008.Among them, the area of facility agriculture based on image extraction in 2018 accounts for about 70.47% of the total area.Based on the image taken since November 2017, the proportion of the agricultural area of facilities for extraction is as high as 86.87%.In some areas, the time of image shooting is relatively early, but most of them are sparsely populated with little or no distribution of facility agriculture, which has little impact on the research results.This data is conducive to fully understanding the spatial distribution of facility agriculture in qinghai-tibet plateau region and to the adjustment of local facility agriculture spatial planning.
LV Changhe, WEI Hui
This data is the simulation data of land use changes using Dyna-CLUE model under multiple scenarios in Heihe River Basin. The time period is 1986-2030, 1986 is the actual reference data, and 1987-2030 is the simulation data. Scenarios include historical trend scenarios, ecological protection scenarios, strict ecological protection scenarios, economic development scenarios and rapid economic development scenarios. Dyna-CLUE model is used to simulate different scenarios. Data format is Arc ASCII format.
NAN Zhuotong
Contact Support
Northwest Institute of Eco-Environment and Resources, CAS
0931-4967287
poles@itpcas.ac.cn
Links
National Tibetan Plateau Data CenterFollow Us
A Big Earth Data Platform for Three Poles © 2018-2020 No.05000491 | All Rights Reserved
｜ 
No.11010502040845
Tech Support: westdc.cn
