This data is the land cover data at 30m resolution of Southeast Asia in 2015. The data format of the data is NetCDF, and the variable name is "land cover type". The data was obtained by mosaicing and extracting the From-GLC data. Several land cover types, such as snow and ice that do not exist in Southeast Asia were eliminated.The legend were reintegrated to match the new data. The data provide information of 8 land cover types: cropland, forest, grassland, shrub, wetland, water, city and bare land. The overall accuracy of the data is 71% (Gong et al., 2019). The data can provide the land cover information of Southeast Asia for hydrological models and regional climate models.
LIU Junguo
1) Data content: the main ecological environment data retrieved from remote sensing in Pan third polar region, including PM2.5 concentration, forest coverage, Evi, land cover, and CO2; 2) data source and processing method: PM2.5 is from the atmospheric composition analysis group web site at Dalhousie University, and the forest coverage data is from MODIS Vegetation continuum Fields (VCF), CO2 data from ODIAC fossil fuel emission dataset, EVI data from MODIS vehicle index products, and land cover data from ESA CCI land cover. 65 pan third pole countries and regions are extracted, and others are not processed; 3) data quality description: the data time series from 2000 to 2015 is good; 4) data application achievements and prospects: it can be used for the analysis of ecological environment change.
LI Guangdong
The matching data of water and soil resources in the Qinghai Tibet Plateau, the potential evapotranspiration data calculated by Penman formula from the site meteorological data (2008-2016, national meteorological data sharing network), the evapotranspiration under the existing land use according to the influence coefficient of underlying surface, and the rainfall data obtained by interpolation from the site rainfall data in the meteorological data, are used to calculate the evapotranspiration under the existing land use according to the different land types of land use According to the difference, the matching coefficient of water and soil resources is obtained. The difference between the actual rainfall and the water demand under the existing land use conditions reflects the matching of water and soil resources. The larger the value is, the better the matching is. The spatial distribution of the matching of soil and water resources can pave the way for further understanding of the agricultural and animal husbandry resources in the Qinghai Tibet Plateau.
DONG Lingxiao
The dataset is the ground verification point dataset of land cover and vegetation type in the Source Region of the Yangtze River (in the south of Qinghai Province) which collected during August 2018. In the dataset, the homogeneous patches are considered as the main targets of this collection. They are easy to be recognized out and distinguished from other vegetation types. And these samples have high representativeness comparing with other land surface features. In each sample, the geographical references, longitude and latitude (degree, minute, second), time (24h) and elevation (0.1m) are recorded firstly according to GPS positioning. Vegetation types, constructive species, characteristics, land types and features, landmarks, etc. are recorded into the property table manually for checking in laboratory. At last, each sample place has been taken at least 1 photography. In this dataset, 90% or more samples have been taken 2 or more in field landscape photographs for land use type and vegetation classification examination. We have carefully examined the position accuracy of each sample in Google Earth. After 2 rounds of checking and examination, the accuracy and reliability of the property of each sample have been guaranteed.
WANG Xufeng
The dataset is the ground verification point dataset of land cover and vegetation type in the Source Region of Yellow River (in the north of Zaling Lake, Qinghai Province) which collected during August 2018. In the dataset, the homogeneous patches are considered as the main targets of this collection. They are easy to be recognized out and distinguished from other vegetation types. And these samples have high representativeness comparing with other land surface features. In each sample, the geographical references, longitude and latitude (degree, minute, second), time (24h) and elevation (0.1m) are recorded firstly according to GPS positioning. Vegetation types, constructive species, characteristics, land types and features, landmarks, etc. are recorded into the property table manually for checking in laboratory. At last, each sample place has been taken at least 1 photography. In this dataset, 90% or more samples have been taken 2 or more in field landscape photographs for land use type and vegetation classification examination. We have carefully examined the position accuracy of each sample in Google Earth. After 2 rounds of checking and examination, the accuracy and reliability of the property of each sample have been guaranteed.
WANG Xufeng
The dataset is the ground verification point dataset of land cover and vegetation type in the Hoh Xil (in the northwest of Qinghai Province) which collected during August 2018. In the dataset, the homogeneous patches are considered as the main targets of this collection. They are easy to be recognized out and distinguished from other vegetation types. And these samples have high representativeness comparing with other land surface features. In each sample, the geographical references, longitude and latitude (degree, minute, second), time (24h) and elevation (0.1m) are recorded firstly according to GPS positioning. Vegetation types, constructive species, characteristics, land types and features, landmarks, etc. are recorded into the property table manually for checking in laboratory. At last, each sample place has been taken at least 1 photography. In this dataset, 90% or more samples have been taken 2 or more in field landscape photographs for land use type and vegetation classification examination. We have carefully examined the position accuracy of each sample in Google Earth. After 2 rounds of checking and examination, the accuracy and reliability of the property of each sample have been guaranteed.
WANG Xufeng
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
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
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
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
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
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 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 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, WU Shixin, ZHOU Wancun
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, WU Shixin, ZHOU Wancun
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, WU Shixin, ZHOU Wancun
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.
WANG Jianhua, LIU Jiyuan, ZHUANG Dafang, ZHOU Wancun, WU Shixin
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.
WANG Jianhua, LIU Jiyuan, ZHUANG Dafang, ZHOU Wancun, WU Shixin
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.
WANG Jianhua, LIU Jiyuan, ZHUANG Dafang, ZHOU Wancun, WU Shixin
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.
WANG Jianhua, LIU Jiyuan, ZHUANG Dafang, ZHOU Wancun, WU Shixin
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