DocumentCode :
2224929
Title :
Predicting the adaptability of sudden oak death in China using spatial information technology
Author :
Liu, Cheng ; Cao, Chunxiang ; Zhang, Jianlong ; Ma, Aiguo ; Chen, Wei ; Xu, Min ; Sakai, Tetsuro
Author_Institution :
State Key Lab. of Remote Sensing Sci., Inst. of Remote Sensing Applic., Beijing, China
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
7256
Lastpage :
7259
Abstract :
Sudden oak death which is caused by the pathogen phytophthora ramorum has killed thousands of oak trees in Europe and North America in recent decades and also threaten the forests in China. In this study, we choose 4 climate predictor variables to predict the adaptability of sudden oak death in China. First we assign the importance of each variable by using analytic hierarchy process(AHP), and then we build the membership function of each variable by using fuzzy mathematics method. With the climate data of 752 weather stations in China, we interpolate them in GIS to generate the variable layers and compute the final adaptability of sudden oak death by averaging the adaptability in each month of the pathogen´s general reproductive season. The result shows that sudden oak death can be suitable for a wide range in China, most of where are southeastern regions.
Keywords :
geographic information systems; vegetation; weather forecasting; China; Europe; North America; analytic hierarchy process; climate data; climate predictor variables; fuzzy mathematics method; geographic information systems; oak trees; pathogen general reproductive season; pathogen phytophthora ramorum; spatial information technology; sudden oak death; weather stations; Adaptation models; Biological system modeling; Computational modeling; Meteorology; Pathogens; Sudden oak death; adaptability; analytic hierarchy process; fuzzy mathematics method; spatial information technology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6351987
Filename :
6351987
Link To Document :
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