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[1]SHI Ming-hui,ZHAO Cui-wei,GUO Zhi-hua,et al.Assessment on Health of Natural Betula platyphylla Forest Based on GIS and BP Neural Networks[J].Research of Soil and Water Conservation,2011,18(04):237-240.

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Assessment on Health of Natural Betula platyphylla Forest Based on GIS and BP Neural Networks

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 18 Number of periods: 2011 04 Page number: 237-240 Column: Public date: 2011-08-20

Title:: Assessment on Health of Natural Betula platyphylla Forest Based on GIS and BP Neural Networks

Author(s):: SHI Ming-hui^1,2, ZHAO Cui-wei¹, GUO Zhi-hua², LIU Shi-rong³; 1. College of Geography and Environmental Science, Guizhou Normal University, Guiyang 550001, China;
2. Institute of Wetland Research, Chinese Academy of Forestry, Beijing 100091, China;
3. Chinese Academy of Forestry, Beijing 100091, China

Keywords:: GIS; improved BP neural network; natural Betula platyphylla forest; health assessment; Changbai mountains; Liangjiang forest farm

CLC:: S718.55⁺7;TP79

DOI:: -

Abstract:: On the bases of sample investigation and related ecosystem data collected by others, assessment on forest health of Liangjiang Forest Farm in Changbai Mountains was performed by the GIS platform and the improved BP neural network model. Improved BP neural network has great advantages in solving the complex forest ecosystem. Using Levenberg-Marquardt algorithm was effective than the traditional BP and some other improved methods, while it could converge much quickly and has high accuracy. Evaluation results show that the total area of 22.43% of Natural Betula platyphylla forest is very healthy, 49.93% of that is healthy, 19.06% of that is sub-healthy, while only 8.59% of which is unhealthy. The main purpose of this paper is to provide a solid theoretical support for forest health management and multifunctional use of forests.

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