Mapping tropical forest vegetation from Landsat TM images based on fusion of knowledge and geo-data

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• 作者：Cunjian Yang ; He Huang
• 关键词：Tropical forests ; Vegetation map ; Forest types ; Landsat TM images
• 刊名：Natural Hazards
• 出版年：2016
• 出版时间：November 2016
• 年：2016
• 卷：84
• 期：1-supp
• 页码：51-61
• 全文大小：839 KB
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Hydrogeology
  Geophysics and Geodesy
  Geotechnical Engineering
  Civil Engineering
  Environmental Management
  
• 出版者：Springer Netherlands
• ISSN：1573-0840
• 卷排序：84

文摘

Tropical forests play a crucial role in the function of our planet and in the maintenance of life. Tropical forest vegetation maps are very important for managing tropical forests. Mapping tropical forest vegetation only by spectral-based remote sensing techniques has proven to be problematic. The objective of the study is to develop a rule-based model to identify different forest types using Landsat TM images and GIS. In this paper, we developed the rule-based model to identify different forest types in Xishuangbanna, P.R. of China, using two temporal Landsat TM images and geo-data such as DEM, rainfall and temperature. The results show that the method put forward is useful and effective in tropical forest vegetation mapping, which can effectively integrate multi-knowledge and multi-resource data to identify the tropical forest vegetation types with higher accuracy.