Assessing Land Ecological Security Based on BP Neural Network: a Case Study of Hangzhou, China

被引:11
作者
You, Heyuan [1 ]
机构
[1] Zhejiang Univ Finance & Econ, Coll Business Adm, Hangzhou, Zhejiang, Peoples R China
基金
中国国家自然科学基金;
关键词
land ecological security; pressure-state-response framework; BP neural network; Hangzhou;
D O I
10.4304/jcp.8.6.1394-1400
中图分类号
TP39 [计算机的应用];
学科分类号
081203 [计算机应用技术]; 0835 [软件工程];
摘要
Due to the increasing stress on the land ecology, the land eco-security suffers damage. In this paper, the BP neural network and PSR framework were adopted to establish the model for assessment of land eco-security, and an empirical study of assessing land eco-security in Hangzhou was done. The results show that the city center district is at serious land eco-security risk; Xiaoshan district and Yuhang district are at high land eco-security risk; and others counties (cities) are at low risk or intermediate risk. In Hangzhou, although some measures are adopted to control the risk of land eco-security, the economic growth still has negative impact on the land ecology. The rapid industrialization and urbanization increase the risk of land eco-security. Therefore the policy constitutors should do something to strengthen the land ecology protection.
引用
收藏
页码:1394 / 1400
页数:7
相关论文
共 21 条
[1]
[Anonymous], 1997, ECOLOGICAL SECURITY
[2]
Using Landsat imagery to map forest change in southwest China in response to the national logging ban and ecotourism development [J].
Brandt, Jodi S. ;
Kuemmerle, Tobias ;
Li, Haomin ;
Ren, Guopeng ;
Zhu, Jianguo ;
Radeloff, Volker C. .
REMOTE SENSING OF ENVIRONMENT, 2012, 121 :358-369
[3]
An ecological basis for sustainable land use of Eastern Mauritanian wetlands [J].
Cooper, A. ;
Shine, T. ;
McCann, T. ;
Tidane, D. A. .
JOURNAL OF ARID ENVIRONMENTS, 2006, 67 (01) :116-141
[4]
Demuth H., 2003, NEURAL NETWORK TOOLB
[5]
Zuazo VHD, 2011, SUSTAIN AGR REV, V6, P107, DOI 10.1007/978-94-007-0186-1_5
[6]
Natural systems as models for the design of sustainable systems of land use [J].
Ewel, JJ .
AGROFORESTRY SYSTEMS, 1999, 45 (1-3) :1-21
[7]
He J., 2009, J COMPUTERS, V6, P569
[8]
HOWARD D, 2000, NEURAL NETWORK TOOLB
[9]
Lynch A. J. J., ENV MANAGEMENT, V47, P40
[10]
OECD, 1994, ENV INDICATORS OECD