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Forest type cover data with 10m spatial resolution of China(2018)

Forest type cover data with 10m spatial resolution of China(2018)

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Date: 2021-10-22

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This dataset is the forest type cover data with 10m spatial resolution of China (2018). Combining Landsat and sentinel-2 remote sensing images as data sources, the spectral and spatiotemporal feature sets of different forest types have been established. Using Landsat and time series harmonic analysis to establish a time feature set. Based on the spectral-temporal feature set, supported by reference data, the random forest recursive feature elimination algorithm is used to study and establish the main features of different regions. According to the spectral-spatial-temporal feature sets of different regions, four machine learning algorithms are used to establish a forest type classification model. Then, using the determined best-fitting model, a forest type map with a spatial resolution of 10 in Southeast China in 2018 was generated. The data format is TIF, the spatial range is Southeast China, and the time is 2018.

Data format
Subject
Ocean
Data Level
Raw
Data time series
No
temperal
Modern times
spatial
Point
resolution
Low
Country ID
CN
Data Size
1GB
Contributor Name
Chengkai,WangJuanle, Yan Xinrong, Wu Yuxin
Contributor Email
ikcest-drr@lreis.ac.cn
Contributor Agency
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences
Creation time
Resplnst Name
RespInst Address
A11 Datun Road, Chaoyang District, Beijing
RespInst Postcode
100101
ResPerson Name
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences
ResPerson Email
ikcest-drr@lreis.ac.cn
ResPerson Telephone
010-64889048-8006
Update Frequency
Access Link
Version
Data Citation
Forest type cover data with 10m spatial resolution of China(2018). Disaster Risk Reduction Knowledge Service of International Knowledge Centre for Engineering Sciences and Technology (IKCEST) under the Auspices of UNESCO, 2021.9.28.
Last Modified
Organization
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences
Time Begin
2018
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