1:100,000 land use dataset of Ningxia 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

1:100,000 landuse dataset of Qinghai 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 2020-06-10

1:100,000 land use dataset of Inner Mongolia Autonomous Region (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 2020-06-10

1:100,000 land use dataset of Tibet Autonomous Region (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 2020-06-10

1:100000 landuse dataset of Shaanxi 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 2020-06-10

1:100000 landuse dataset of Shaanxi 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 2020-06-10

1:100000 landuse dataset of Qinghai 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 2020-06-10

Data of interaction mechanism between major road projects and environment in western mountainous areas project

The interaction mechanism project between major road projects and the environment in western mountainous areas belongs to the major research plan of "Environment and Ecological Science in Western China" of the National Natural Science Foundation. The person in charge is Cui Peng researcher of Chengdu Mountain Disaster and Environment Research Institute, Ministry of Water Resources, Chinese Academy of Sciences. The project runs from January 2003 to December 2005. Data collected for this project: Engineering and Environmental Centrifugal Model Test Data (word Document): Consists of six groups of centrifugal model test data, namely: Test 1. Centrifugal Model Test of Soil Cutting High Slope (6 Groups) Test 2. Centrifugal Model Experiment of Backpressure for Slope Cutting and Filling (4 Groups) Test 3. Centrifugal Model Experimental Study on Anti-slide Piles and Pile-slab Walls (10 Groups) Test 4. Centrifugal Model Tests for Different Construction Timing of Slope (5 Groups) Test 5. Migration Effect Centrifugal Model Test (11 Groups) Test 6. Centrifugal Model Test of Water Effect on Temporary Slope (8 Groups) The purpose, theoretical basis, test design, test results and other information of each test are introduced in detail.

0 2020-06-09

The presert state map of landuse (Zhangye 1:500,000)

This data is digitized from the "Zhangye 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" Shelter Forest Remote Sensing Comprehensive Survey, and 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 1. File Format and Naming Data is stored in ESRI Shapefile format, including the following layers: Zhang Ye's landuse Map, River, Road, 2. Data Fields and Attributes Type number type face desert Paddy field 12 Irrigated field 13 dryland Non-irrigated field 131 Plain non-irrigated field Valley non-irrigated field Slope non-irrigated field, 133 slope dryland 134 dryland Terrace non-irrigated field ................. Please refer to the data document for details. 3. 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 2020-06-09

Irrigation ditch map in Zhangye city

Data Overview: Zhangye's channels are divided into five levels: dry, branch, bucket, agricultural and Mao channels, of which the agricultural channels are generally unlined. Mao channels are field projects, so the three levels of dry, branch and bucket channels and a small part of agricultural channels are mainly collected. The irrigation canal system data includes 2 main canals (involving multiple irrigation districts), 157 main canals (within a single irrigation district), 782 branch canals and 5315 dou canals, with a total length of 8, 745.0km. Data acquisition process: remote sensing interpretation and GPS field measurement are adopted for data acquisition of irrigation canal system. Direct GPS acquisition channel is the most effective method, but the workload of GPS acquisition channel is too large, and we only verify the measurement in some irrigation areas. The main method is to first collect the manual maps of irrigation districts drawn by each water pipe. Most of these maps have no location, only some irrigation districts such as Daman and Shangsan have been located based on topographic maps, and some irrigation districts in Gaotai County have used GPS to locate some channels. Referring to the schematic diagram of the irrigation district, channel spatial positioning is carried out based on Quikbird, ASTER, TM remote sensing images and 1: 50000 topographic maps. For the main canal and branch canal, due to the obvious linear features on remote sensing images and the general signs on topographic maps, it can be located more accurately. For Douqu, areas with high-resolution images can be located more accurately, while other areas can only be roughly located according to fuzzy linear features of images and prompt information of irrigation district staff, with low positioning accuracy. Each water management office simultaneously provides channel attribute data, which is one-to-one corresponding to spatial data. After the first draft of the channel distribution map is completed, it is submitted twice to the personnel familiar with the channel distribution of each water pipe for correction. The first time is mainly to eliminate duplication and leak, and the second time is mainly to correct the position and perfect the attribute data. Description of data content: The fields in the attribute table include code, district and county name, irrigation area name, channel whole process, channel name, channel type, location, total length, lined, design flow, design farmland, design forest and grass, real irrigation farmland, real irrigation forest and grass, water right area, and remarks. Code example: G06G02Z15D01, where the first letter represents the county name, the 2nd and 3rd numbers represent the county (district) number, the 4th to 6th characters represent the trunk canal code, the 7th to 9th characters represent the branch canal code, and the 10th to 12th characters represent the dou canal code.

0 2020-06-08