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Published on: August 8, 2017
[Advances in researches on hyperspectral remote sensing forestry information-extracting technology]
1The Key Laboratory for Silviculture and Conservation of the Ministry of Education, Beijing Forestry University, Beijing 100083, China. xiangfeidewujian@126.com
Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu
|November 22, 2011
Summary
Hyperspectral remote sensing is advancing forestry applications. This review covers tree species classification, parameter inversion, nutrient monitoring, crown density, and disaster detection using hyperspectral technology.
Area of Science:
- Forestry
- Remote Sensing
- Geospatial Science
Background:
- Hyperspectral remote sensing is a key technology in forestry.
- Significant research advances have been made globally in forestry information extraction using this technology.
Purpose of the Study:
- To review advancements in hyperspectral remote sensing for forestry.
- To summarize key research areas and identify challenges and future prospects.
Main Methods:
- Comprehensive literature review of hyperspectral remote sensing in forestry.
- Analysis of research on tree species classification, parameter inversion, nutrient monitoring, crown density, and disaster monitoring.
Main Results:
- Summarized five main research aspects: tree species classification, ecological parameter inversion, nutrient element monitoring, crown density extraction, and disaster monitoring.
- Identified unresolved problems and proposed solutions for hyperspectral technology in forestry applications.
Conclusions:
- Hyperspectral remote sensing offers significant potential for forestry applications.
- Future research should focus on addressing current limitations to fully leverage this technology.
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