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The diagnostic dataset of damaged vegetation restoration based on phenology information

The diagnostic data of damaged vegetation restoration can reflect plant restoration status in time, and provide effective support for disaster recovery and reconstructions of affected vegetation. This dataset is produced by the spatial distribution of damaged vegetation and corresponding plant phenology data, which use the dynamic threshold method to monitor whether the damaged vegetation is restored or not. The dataset covers the whole of Hunan province, China, which includes 101 counties and the spatial resolution of which is 250 meters. What's more, the diagnostic result of vegetation restoration is from 2008 to 2015, the pixel value of which represents the recovery time. This dataset can be used in forest resource management and related scientific research.

Data format
Tif
Subject
Geography
Data Level
Product
Data time series
No
temperal
Modern times
spatial
Country
resolution
High
Country ID
CN
Data Size
1.01MB MB
Contributor Name
Wang Xuecheng
Contributor Email
wangxc.15s@igsnrr.ac.cn
Contributor Agency
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences
Creation time
2017.6.30
Resplnst Name
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences
RespInst Address
A11 Datun Road, Chaoyang District, Beijing
RespInst Postcode
100101
ResPerson Name
Service group of Disaster Risk Reduction Knowledge Service System of IKCEST
ResPerson Email
ikcest-drr@lreis.ac.cn
ResPerson Telephone
010-64889048-8006
Update Frequency
Irregular updates
Version
1
Data Citation
The diagnostic dataset of damaged vegetation restoration based on phenology information. Disaster Risk Reduction Knowledge Service of International Knowledge Centre for Engineering Sciences and Technology (IKCEST) under the Auspices of UNESCO, http://drr.ikcest.org/info/9f32d.
Last Modified
2017.6.30
Organization
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences.
Accessconstraints
Sharing Type: Open
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