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Land Cover Classification Dataset in the Middle Reaches of the Heihe River Basin (2018)


BIAN Zenggan1WANG Wen1JIANG Yuan1
1 State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering,Hohai University,Nanjing 210098,China

DOI:10.3974/geodb.2020.03.09.V1

Published:May 2020

Visitors:2719       Data Files Downloaded:118      
Data Downloaded:160.56 MB      Citations:

Key Words:

Heihe River Basin,Land cover,classification,Journal of Geo-Information Science

Abstract:

Land Cover Classification Dataset in the Middle Reaches of the Heihe River Basin (2018) was developed by using NDVI, decision tree classification, object-oriented classification and the random forest classification and resampling based on GF-1 WFV images. In the first level of the dataset, seven land cover types were classified, they are: cropland, forest land, grassland, artificial surface, wetland, bare land and water. In the second level of the land cover classification system, there are seven land cover types. The dataset includes: (1) boundary data of the study area (.shp); (2) the classification data of land cover types in the middle reaches of the Heihe River Basin in 2018 (.tif, in 30 m). The dataset consists of 9 data files with data size of 56.2 MB (compressed to one single file with data size of 1.36 MB). The analysis paper based on the dataset was published at the Journal of Geo-Information Science, Vol.21, No.10, 2019.

Foundation Item:

Ministry of Science and Technology of P. R. China (2017YFC0405801-02); National Natural Science Foundation of China (41961134003)

Data Citation:

BIAN Zenggan, WANG Wen, JIANG Yuan.Land Cover Classification Dataset in the Middle Reaches of the Heihe River Basin (2018)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2020. https://doi.org/10.3974/geodb.2020.03.09.V1.

Data Product:

ID Data Name Data Size Operation
1 LandCover_HeiheBasin_2018.rar 1393.32KB
Co-Sponsors

Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences

The Geographical Society of China

Parteners

Committee on Data for Science and Technology (CODATA) Task Group on Preservation of and Access to Scientific and Technical Data in/for/with Developing Countries (PASTD)

Jomo Kenyatta University of Agriculture and Technology

Digital Linchao GeoMuseum