Landcover dataset of the Shulehe River Basin (2000)

The data is the Shule River Basin land cover dataset, which is derived from "China's 1: 100,000 Land Use Data Set" in 2000. It is based on Landsat MSS, TM and ETM remote sensing data within three years by satellite remote sensing. 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. The attribute fields include: Area, Perimeter, Code(Land code), Name (land type).

0 2020-06-08

Dataset of growing season average NDVI changing trends in Three River Source National Park (2000-2018)

Based on the average NDVI (spatial resolution 250m) of MODIS during the growing season from 2000 to 2018, the trend of NDVI was calculated by using Mann-Kendall trend detection method. Three parks of Three River Source National Park are calculated (CJYQ: Yangtze River Park; HHYYQ: Yellow River Park; LCJYQ: Lancang River Park). CJYQ_NDVI_trend_2000_2018_ok.tif: Changjiang Source Park NDVI trend. CJYQ_NDVI_trend_2000_2018_ok_significant.tif: Changjiang Source Park NDVI change trend, excluding the area that is not significant (p > 0.05). CJYYQ_gs_avg_NDVI_2000.tif: The average NDVI of the Yangtze River Source Park in 2000 growing season. Unit NDVI changes every year.

0 2020-05-29

Primary road network dataset of QinghaiLake River Basin (2000)

The data is a dataset of road distribution in Qinghai Lake basin, scale1: 250,000, projection: latitude and longitude, mainly including the spatial distribution and attribute data of main roads in Qinghai Lake basin, attribute fields: code (road code), name (road classification).

0 2020-04-07

The dataset of the lake distribution in Qinghai Lake basin (2000)

The dataset is the distribution map of lakes in Qinghai Lake Basin. The projection is latitude and longitude. The data includes the spatial distribution data and attribute data of the lake. The attribute fields of the lake are: NAME (lake name), CODE (lake code).

0 2020-04-04

Landuse/Landcover data of the QinghaiLake River Basin (2000)

The data is a land cover dataset of the Qinghai Lake Basin, which was derived from the "China 1: 100,000 Land Use Dataset" in 2000. It was constructed based on Landsat MSS, TM and ETM remote sensing data within three years using satellite remote sensing. This data uses a hierarchical land cover classification system, which divides the country into 6 first-class categories (arable land, forest land, grassland, waters, urban and rural areas, industrial and mining, residential land and unused land), and 31 second-class categories. The attribute fields include: Area, Perimeter, Code (Land Code), Name (Land Type).

0 2020-04-04

Data of distribution of desert for The QinghaiLake River Basin (2000)

The data is the distribution map of 100,000 deserts in Qinghai Lake Basin. This data uses 2000 TM image as the data source for interpretation, extraction and revision. Remote sensing and geographic information system technology are combined with the mapping requirements of a scale of 1: 100,000 to carry out thematic mapping of deserts, sands and gravelly Gobi. Data attribute table: area (area), perimeter (perimeter), ashm_ (sequence code), class (desert code) and ashm_id (desert code), of which the desert code is as follows: mobile sand 2341010, semi-mobile sand 2341020, semi-fixed sand 2341030, Gobi desert 2342000 and saline-alkali land 2343000.

0 2020-04-04

Landuse/landcover data of Tarim Rivers (2000)

The data is the land cover data set of Tarim River Basin, which comes from "China's 1:100000 land use data set" in 2000. It is constructed based on LANDSAT MSS, TM and ETM Remote Sensing Data in three years by means of satellite remote sensing. 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. The attribute fields are area, perimeter, code, and name.

0 2020-03-30

1:100,000 Landuse data in the Yellow River Upstream (2000)

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.

0 2020-03-28

Dataset of above ground biomass in Sanjiangyuan region (2000, 2010, 2015 )

The method of aboveground biomass of grassland is zonal classification model. The data years were 2000, 2010 and 2015, and the fresh vegetation weight was based on the first ten days of August. Above-ground biomass is defined as the total amount of organic matter of vegetation living above the ground in a unit area. Unit: g/m². This data set is calculated from a statistical model based on the MODIS vegetation index by the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences. The spatial resolution is 250 m x 250 m. The data set is an important data source for vegetation monitoring in Three River Source National Park. Projection information: Albers isoconic projection Central meridian: 105 degrees First secant: 25 degrees First secant: 47 degrees West deviation of coordinates: 4000000 meters

0 2019-09-15

Dataset of net primary productivity in Sanjiangyuan region (2000-2015)

Monthly meteorological data of Sanjiangyuan includes 32 national standard meteorological stations. There are 26 variables: average local pressure, extreme maximum local pressure, date of extreme maximum local pressure, extreme minimum local pressure, date of extreme minimum local pressure, average temperature, extreme maximum temperature, date of extreme maximum temperature, extreme minimum temperature and date of extreme minimum temperature, average temperature anomaly, average maximum temperature, average minimum temperature, sunshine hours, percentage of sunshine, average relative humidity, minimum relative humidity, date of occurrence of minimum relative humidity, precipitation, days of daily precipitation >=0.1mm, maximum daily precipitation, date of maximum daily precipitation, percentage of precipitation anomaly, average wind speed, maximum wind speed, date of maximum wind speed, maximum wind speed, wind direction of maximum wind speed, wind direction of maximum wind speed and occurrence date of maximum wind speed. The data format is txt, named by the site ID, and each file has 26 columns. The names and units of each column are explained in the SURF_CLI_CHN_MUL_MON_readme.txt file. Projection information: Albers isoconic projection Central meridian: 105 degrees First secant: 25 degrees First secant: 47 degrees West deviation of coordinates: 4000000 meters

0 2019-09-15