Share Email Print
cover

Proceedings Paper

Monitoring the landscape change in the semi-arid areas: a case study in Yulin prefecture of Shaanxi, China
Author(s): J. Lei; J. Zhan; X. Deng; Zh. Guo
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Landscape is a dynamic phenomenon that almost continuously changes. General speaking, landscape change is a dynamic process affected by geophysical conditions as well as human activities. However, numerous activities by a large number of individuals are not concerted and contribute to the autonomous evolution of the landscape in a similar way as natural processes do. There is a well-established need to detect landscape change so that appropriate policies for the regional sustainable development can be developed. Landscape change detection is considered to be effectively repeated surveillance and needs especially strict protocols to identify the change categories and intensity. Methods for monitoring and analyzing landscape change - for example, remote sensing and GIS - are increasingly used in attempts to understand the consequences of such change. This paper developed a hierarchical approach that combines remote sensing technology, GIS, and sophisticated analytical techniques to quantify land cover change at several spatial scales. Through human-machine interactive interpretation, the interpretation precision was 92.00% in 1986 and 89.73% in 2000. Based on the interpretation results of TM images and take Yulin Prefecture as the case study area, the area of main landscape types was summarized respectively in 1986 and 2000. The landscape pattern changes in Yulin could be divided into ten types.

Paper Details

Date Published: 1 September 2005
PDF: 8 pages
Proc. SPIE 5884, Remote Sensing and Modeling of Ecosystems for Sustainability II, 58841M (1 September 2005); doi: 10.1117/12.618857
Show Author Affiliations
J. Lei, Xinjiang Institute of Ecology and Geography, CAS (China)
Institute of Geographical Sciences and Natural Resources Research, CAS (China)
J. Zhan, Institute of Geographical Sciences and Natural Resources Research, CAS (China)
Institute of Policy and Management, CAS (China)
X. Deng, Institute of Geographical Sciences and Natural Resources Research, CAS (China)
Ctr. for Chinese Agricultural Policy, CAS (China)
Zh. Guo, Institute of Geographical Sciences and Natural Resources Research, CAS (China)


Published in SPIE Proceedings Vol. 5884:
Remote Sensing and Modeling of Ecosystems for Sustainability II
Wei Gao; David R. Shaw, Editor(s)

© SPIE. Terms of Use
Back to Top