草业学报2012，Vol.21Issue(5)：229-236,8.
基于马尔柯夫模型的草原退化动态时空特征研究
A study on spatial-temporal characteristics of grassland degradation using the Markov model
摘要
Abstract
The spatial and temporal features of grassland cover conversion (GCC) serve as a useful input for un-derstanding the desertification process and degradation of grassland caused by anthropogenic activities and extreme natural events in general. Thematic Mapper data (TM 30 m) were used to detect and map degraded grassland features both spatially and temporally. Two data sets of TM 30 m data were collected from the years 2000 to 2010. Supervised classifications were developed for each of the GCC change detection of the three cases (degradation,desertification, and salinization). To address this situation, the field data were used to test the GCC detection of change results presented in this paper. The GCC change detection methods worked reasonably well and detection accuracy of deserted and salinized output was >90% although degraded output identified only 75% of the covered pixels within the ground observed perimeter polygons. The applications presented in this paper also evaluated the transition matrix between 2000 and 2010 of each of the three change detections, and predicted dynamic characteristics of grassland using the Markov model. The results showed that for the next decade, and even for a further ten years, the grassland will develop positively with a reduced trend of degradation and desertification. The research also indicated, it is credible to use remote sensing technology combined with the Markov model in analyzing the dynamic characteristics of grassland cover changes.关键词
马尔柯夫模型/草原退化/动态/时空特征Key words
Markov model/degradation/dynamic/temporal-spatial characteristic分类
农业科技引用本文复制引用
刘爱军,王保林,陈喜梅,杨胜利,郑淑华..基于马尔柯夫模型的草原退化动态时空特征研究[J].草业学报,2012,21(5):229-236,8.基金项目
农业行业科研专项(200903060),自治区自然科学基金(2130106)和林业行业科研专项(201204202)资助. （200903060）
