Land use change in the midstream of Heihe River Basin

According to the statistical yearbook, different types of land use change areas in the middle reaches of China since liberation were collected and sorted out.

0 2020-06-11

The landuse map of Tianshui at 1:500,000 scale (1978)

This data is digitized from the "Tianshui Land Use Status Map" of the drawing. This map is a key scientific and technological research project of the "Seventh Five-Year Plan" of the country: "Three North" Shelterbelt Remote Sensing Comprehensive Survey, one of the series maps of Ganqingning Type Area. The information is as follows: * Chief Editor: Wang Yimou * Deputy Editors: Feng Yushun, You Xianxiang, Shen Yuancun * Editors: Wang Xian, Wang Jingquan, Qiu Mingxin, Quan Zhijie, Mou Xindai, Qu Chunning, Yao Fafen, Qian Tianjiu, Huang Autonomy, Mei Chengrui, Han Xichun, Li Yujiu, Hu Shuangxi * Responsible Editor: Huang Meihua * Manuscript: Mou Xin-shi, Cui Sai-hua, Wang Xian. He Shouhua * Compiling: He Shouhua, Wang Xian, Quan Zhijie, Cui Saihua, Long Yaping, Mu Xinshi, He Shouhua, Mao Xiaoli, Cui Saihua, Wang Changhan * Editors: Feng Yushun and Wang Yimou * Qing Hua: Feng Yushun, Zhang Jingqiu, Yang Ping * Cartography: Feng Yushun, Yao Fafen, Wang Jianhua, Zhao Yanhua, Li Weimin * Cartographic unit: compiled by Desert Research Office of Chinese Academy of Sciences * Publishing House: Xi 'an Map Publishing House * Scale: 1: 500000 * Publication time: not yet available 2. File Format and Naming Data is stored in ESRI Shapefile format, including the following layers: Tianshui landuse map (landuse), River, Road, point-like residential land and area-like residential land 3. Data Fields and Attributes Type number land resource class Land_type 88 Exposedrock 86 bare soil Bareground 85 sandy beach and dry ditch Sandy flat and dryvally 446 Artemisia ordosica, miscellaneous grass G1. Artemisia subdingata mixed herbs 445 fern, miscellaneous grass G1. pterideumaquilumvar. latiusculummixedherbs444 Polygonum viviparum, grass G1. G1.Polygonumriciparum,grasses 443 Huang Qiangwei, Spiraea shrub miscellaneous grass G1. Rosa Hugo NIS, Spiraea Canes Cens Scrub Mixed Weeds 442 honeysuckle, elaeagnus pungens shrub miscellaneous grass g1.lonicera japonica eluegas pungens shurb mixed herbs 441 Tiger Hazelnut, Shrub Miscellaneous Grass G1. Ostryopsis Daridiana Scrub Mixed Herbs ............. Please refer to the data document for details. 2. Projection information: Angular Unit: Degree (0.017453292519943295) Prime Meridian: Greenwich (0.000000000000000000) Datum: D_Beijing_1954 Spheroid: Krasovsky_1940 Semimajor Axis: 6378245.000000000000000000 Semiminor Axis: 6356863.018773047300000000 Inverse Flattening: 298.300000000000010000

0 2020-06-11

The presert state map of land use over Yinchuan (1:500,000)

This data is digitized from the "Yinchuan Land Use Status Map" of the drawing, which is a key scientific and technological research project in the "Seventh Five-Year Plan" of the country: "Three North" Shelter Forest Remote Sensing Comprehensive Survey, one of the series maps of Ganqingning Type Area, with the following information: * Chief Editor: Wang Yimou * Deputy Editors: Feng Yushun, You Xianxiang, Shen Yuancun * Editors: Wang Xian, Wang Jingquan, Qiu Mingxin, Quan Zhijie, Mou Xindai, Qu Chunning, Yao Fafen, Qian Tianjiu, Huang Autonomy, Mei Chengrui, Han Xichun, Li Yujiu, Hu Shuangxi * Responsible Editor: Huang Meihua * Editorial: Feng Yushun and Yao Fafen * Compilation: Yao Fafen, Li Zhenshan, Wang Xizhang, Zhu Che, Ma Bin, Yang Ping * Editors: Feng Yushun and Wang Yimou * Qing Hua: Wang Jianhua, Yao Fafen, Ma Bin, Li Zhenshan * Cartographic unit: compiled by Desert Research Office of Chinese Academy of Sciences * Publishing House: Xi 'an Map Publishing House * Scale: 1: 500000 * Publication time: not yet available 2. File Format and Naming Data is stored in ESRI Shapefile format, including the following layers: Desertification type map (desert), Yinchuan landuse map (landuse), railway, residential _ poly, residential, River, Road, Water_poly 3. Data Fields and Attributes Type number land_type Desert shape Paddy field Paddy field 12 Irrigated field 131 Plain non-irrigated field Valley non-irrigate field Slope non-irrigated field, 133 slope dryland 134 dryland Terrace non-irrigat field 14 Vegetable plot vegetable plot 15 Abandoned farmland Orchard orchard 31 Woodland ......... Specific attribute contents refer to data documents 2. Projection information: Angular Unit: Degree (0.017453292519943295) Prime Meridian: Greenwich (0.000000000000000000) Datum: D_Beijing_1954 Spheroid: Krasovsky_1940 Semimajor Axis: 6378245.000000000000000000 Semiminor Axis: 6356863.018773047300000000 Inverse Flattening: 298.300000000000010000

0 2020-06-11

The landuse map of Dunhuang at 1:500,000 scale

This data is the dunhuang land use status map digitized from the drawings. This map is one of the key scientific and technological research projects of the seventh five-year plan of China: comprehensive remote sensing survey of shelterbelt in the third north, and one of the series maps of the type area of gan qingning. The information is as follows: * chief editor: wang yimou, * deputy chief editor: feng yusun, you xianxiang, shenyuan village *, qing painting: wang jianhua, yao fafen, Yang ping * drawing: feng yu-sun, yao fa-fen, wang jianhua, zhao yanhua, li weimin * cartographic unit: desert laboratory, Chinese academy of sciences * publishing house: xi 'an map publishing house 2. File format and naming The data is stored in ESRI Shapefile format, including the following layers: Dunhuang land use status map, rivers, roads, lakes, railways, residential land, reservoirs, desertification 3. Data fields and properties Type code land resource class (Land_type) 12. Irrigated field 31 Woodland 311 Woodland 312 Joe irrigation mixed forest land (tree-shurb mixed) 321 Shrub land (Shrub) Sparse shrub 33 Sparse woods In winter and spring of 4111 Meadow grassland, Meadow grassland in the spring and winter) 4112 winter and spring of salinization meadow grassland, Saline meadow grassland in the spring and winter) 4112 winter and spring of salinization meadow grassland, Saline meadow grassland in the spring and winter) In winter and spring of 4113 salt meadow grassland (Salty soil meadow grassland in the spring and winter) 4122 gritty desert grassland autumn grass (Gravely desert - steppe grassland in autumn and winter) 4124 mountain desert grassland winter and spring pastures (Mountainous desert - steppe grassland in winter and spring) 4134 four seasons mountain desert grassland, Mountainous desert steppe in four seasons) Sandy desert steppe in autumn and winter Gravely desert steppe in autumn and winter Earthy desert steppe in four seasons Alpine steppe in four seasons 51 Urban and town land 52 Village land 73 Reservoir and pond 74 Reed marshes Tidal flat 81 Desert land 82 Saline-alkali land 83 Marshes 84 Sandy land Sandy flat and dry valley 86 Bare land 87 Gobi Gobi 88 Exposed rock Flat sandy land Compound dunes Undulatory sand-overlying land Dunes and barchan chain The sand ridge (Longitudinal dune) Check dune

0 2020-06-11

1:100,000 landuse dataset of Sichuan province (2000)

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.

0 2020-06-11

1:100,000 land use dataset of Sichuan province (1995)

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.

0 2020-06-11

The productivity data of land resources for the Belt and Road

The data of Land Resources Productivity for “B&R” includes: 1. Areas of cultivated land resources in regions and countries along the “B&R”; 2. Data on grain planting area and total grain output in regions and countries along the “B&R”; 3. Major crops (rice, wheat, corn) in regions and countries along the route Planting area and production data; 4. Areas of grassland resources in the region and along the country; 5. Number of livestock (bovine, sheep) in the region and along the country. Source: Cultivated land and population data from the World Bank database; food, crop, grassland, and livestock data are from FAO. Data application: According to the data provided, the basic characteristics analysis of land resources and the analysis of land resource output can be carried out in the Belt and Road region and the countries along the route, so that the land resource productivity evaluation analysis can be carried out.

0 2020-06-11

Land cover of core countries of the Belt and Road in 2015 (Version 1.0)

Based on 2015 ESA global land cover data (ESA GlobCover, 300 m grid), combined with the tsinghua university global land cover data (FROM GLC, 30 m grid)、NASA MODIS global land cover data (MCD12Q1, 300 m grid)、the United States Geological Survey (USGS global land data (GFSAD30, 30 m)、Japanese global forest data (PALSAR/PALSAR - 2, 25 m),we build the LUC classification system in the Belt and Road’s region and the rest of the data transformation rules of the classification system.We also build the land cover classification confidence function and the rules of fusing land classification to finish the Integration and modification of land cover products and finally complet the land use data in the Belt and Road’s region V1.0(64 + 1 countries, 2015, 1 km x 1 km grid, the first level classification).

0 2020-06-11

1:100,000 landuse dataset of Qinghai province (1980s)

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.

0 2020-06-11

1:100,000 land use dataset of Ningxia province (1980s)

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.

0 2020-06-11