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Proceedings Paper

Remote sensing detection model of damaged forest by tomicus piniperda in Yunnan Province, China
Author(s): Xieqiong Dong; Shuhe Zhao; Weijia Luo; Xuezhi Feng; Xiaopeng Yang; Hongping Liu; Hong Xu
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Paper Abstract

Remote sensing detection model of damaged forest by tomicus piniperda was studied. It analyzed different detection models using multiple types of remote sensing data, such as TM, CBERS-1, AVHRR and MODIS data. The spectral features of the above remote sensing data (March, 2001) were given. And two detection models were put forward according to the spectral changing characteristics. One was named Difference Rate (DR) model with NIR and VIR data, which applied for TM, CBERS-1, AVHRR and MODIS. If DR was bigger, the forest grew healthier. Based on the typical sample, the different guidelines distinguished healthy and damaged forests were obtained. The other model was named Disaster Index (DI) model with thermal and NIR data, only suitable for MODIS. The guidelines of healthy and damaged forest were determined too. Greater DI was, the forest was stricken more badly. In conclusion, it will help monitor and assess the vermin occurrence and impact by remote sensing detection model.

Paper Details

Date Published: 19 May 2006
PDF: 8 pages
Proc. SPIE 6199, Remote Sensing and Space Technology for Multidisciplinary Research and Applications, 61990C (19 May 2006); doi: 10.1117/12.673661
Show Author Affiliations
Xieqiong Dong, Ctr. for Agrometeorology and Remote Sensing Application of Yunnan (China)
Nanjing Univ. (China)
Shuhe Zhao, Nanjing Univ. (China)
Peking Univ. (China)
Weijia Luo, Nanjing Univ. (China)
Xuezhi Feng, Nanjing Univ. (China)
Xiaopeng Yang, Ctr. for Agrometeorology and Remote Sensing Application of Yunnan (China)
Hongping Liu, Yunnan Academy of Forestry (China)
Hong Xu, Ctr. for Agrometeorology and Remote Sensing Application of Yunnan (China)


Published in SPIE Proceedings Vol. 6199:
Remote Sensing and Space Technology for Multidisciplinary Research and Applications
Qingxi Tong; Xiuwan Chen; Allen Huang; Wei Gao, Editor(s)

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