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Detecting Forest Degradation in the Three-North Forest Shelterbelt in China from Multi-Scale Satellite Images
- Source :
- Remote Sensing, Volume 13, Issue 6, Pages: 1131, Remote Sensing, Vol 13, Iss 1131, p 1131 (2021)
- Publication Year :
- 2021
- Publisher :
- Multidisciplinary Digital Publishing Institute, 2021.
-
Abstract
- Detecting forest degradation from satellite observation data is of great significance in revealing the process of decreasing forest quality and giving a better understanding of regional or global carbon emissions and their feedbacks with climate changes. In this paper, a quick and applicable approach was developed for monitoring forest degradation in the Three-North Forest Shelterbelt in China from multi-scale remote sensing data. Firstly, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Ratio Vegetation Index (RVI), Leaf Area Index (LAI), Fraction of Photosynthetically Active Radiation (FPAR) and Net Primary Production (NPP) from remote sensing data were selected as the indicators to describe forest degradation. Then multi-scale forest degradation maps were obtained by adopting a new classification method using time series MODerate Resolution Imaging Spectroradiometer (MODIS) and Landsat Enhanced Thematic Mapper Plus (ETM+) images, and were validated with ground survey data. At last, the criteria and indicators for monitoring forest degradation from remote sensing data were discussed, and the uncertainly of the method was analyzed. Results of this paper indicated that multi-scale remote sensing data have great potential in detecting regional forest degradation.
- Subjects :
- validation
010504 meteorology & atmospheric sciences
multi-scale
Science
forest degradation
0211 other engineering and technologies
Primary production
02 engineering and technology
Enhanced vegetation index
01 natural sciences
Normalized Difference Vegetation Index
indicators
MODIS
Remote sensing (archaeology)
Photosynthetically active radiation
Thematic Mapper
General Earth and Planetary Sciences
Environmental science
Moderate-resolution imaging spectroradiometer
Leaf area index
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Remote sensing
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Database :
- OpenAIRE
- Journal :
- Remote Sensing
- Accession number :
- edsair.doi.dedup.....a571ee0e0806290e84b1f1761908a0b0
- Full Text :
- https://doi.org/10.3390/rs13061131