基于马尔柯夫模型的草原退化动态时空特征研究

草业学报 ›› 2012, Vol. 21 ›› Issue (5): 229-236.

基于马尔柯夫模型的草原退化动态时空特征研究

刘爱军^1,2,3*,王保林^2,3,陈喜梅³,杨胜利³,郑淑华³

1.北京林业大学,北京 100714;
2.内蒙古民族大学,内蒙古通辽 028043;
3.内蒙古草原勘察规划院,内蒙古呼和浩特 010051

收稿日期:2011-09-16 出版日期:2012-05-25 发布日期:2012-10-20
通讯作者: E-mail:liuaj_81@163.com
作者简介:刘爱军(1964-),女,内蒙古呼和浩特人,研究员,博士。E-mail:liuaj_81@163.com
基金资助:
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。

A study on spatial-temporal characteristics of grassland degradation using the Markov model

LIU Ai-jun^1,2,3, WANG Bao-lin^2,3, CHEN Xi-mei³, YANG Sheng-li³, ZHENG Shu-hua³

1.Beijing Forestry University, Beijing 100714,China;
2.Inner Mongolia Nationalities University, Tongliao 028043, China;
3.Inner Mongolia Institute of Grassland Survey and Planning, Hohhot 010051, China

Received:2011-09-16 Online:2012-05-25 Published:2012-10-20

摘要/Abstract

摘要： 草原植被覆盖动态时空特征是理解人类活动和自然因素影响下草原退化的关键。本研究利用2000和2010年TM影像,利用监督分类方法,对内蒙古草原退化、沙化和盐渍化时空分布特征探测和制图,同时对分类结果进行验证。检验结果表明,采用监督分类结合地面训练样本进行草原退化动态特征检测能提高分类精度,草原沙化和盐渍化分类精度分别都达到90%以上,退化草原分类精度为75%。在草原退化程度分类检测基础上,计算2000-2010年草原退化、沙化、盐渍化面积概率转移矩阵,并基于马尔柯夫模型,对未来20年间草原动态特征进行预测。研究结果表明,十年间,内蒙古草原的退化、沙化程度均呈减弱趋势。预测结果显示,在草原与生态保护建设工程持续稳定有效建设前提下,内蒙古草原呈现良性发展趋势,退化及沙化状况将持续得到改善。研究也指出,基于遥感技术与马尔柯夫模型有机结合分析草原退化动态特征是一种快速有效的途径。

Abstract: The spatial and temporal features of grassland cover conversion (GCC) serve as a useful input for understanding 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.

中图分类号:

S812

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.

LIU Ai-jun, WANG Bao-lin, CHEN Xi-mei, YANG Sheng-li, ZHENG Shu-hua. A study on spatial-temporal characteristics of grassland degradation using the Markov model[J]. Acta Prataculturae Sinica, 2012, 21(5): 229-236.

参考文献

[1] Turner II B L. Thoughts on linking the physical and human sciences in the study of global environmental change[J]. Research and Exploration, 1991, 7(2): 133-135.
[2] Turner II B L. Local faces, global flows: The role of land use and land cover in global environmental change[J]. Land Degradation and Development, 1994, 5(2): 71-78.
[3] 高渐飞, 苏孝良, 熊康宁, 等. 贵州岩溶地区的草地生态环境与草地畜牧业发展[J]. 草业学报, 2011, 20(4): 279-286.
[4] 李飞, 赵军, 赵传, 等. 中国西北干旱区潜在植被模拟与动态变化分析[J]. 草业学报, 2011, 20(4): 42-50.
[5] Cihlar J. Land cover mapping of large areas from satellites: status and research priorities[J]. Remote Sensing, 2000, 21(6,7): 1093-1114.
[6] 刘爱军, 韩建国. 利用遥感技术监测锡林郭勒天然草原利用强度方法初探[J]. 中国草地学报, 2007, 29(2): 201-206.
[7] 刘晓东, 刘荣堂, 刘爱军, 等. 三江源区草地覆盖遥感信息提取方法及动态研究[J]. 草地学报, 2010, 18(2): 154-159.
[8] 刘睿, 孙九林, 张金区, 等. 中国北方草地覆被的HJ星NDVI校正研究[J]. 草业学报, 2011, 20(1): 189-198.
[9] Weng Q H. Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling[J]. Journal of Environmental Management, 2002, 64(3): 273-284.
[10] 郑江坤, 余新晓, 贾国栋, 等. 密云水库集水区基于LUCC的生态服务价值动态演变[J]. 农业工程学报, 2010, 26(9): 315-320.
[11] Turner M G, Wear D N, Flamm R O. Land ownership and land-cover change in the southern Appalachian highlands and the Olympic peninsula[J]. Ecological Applications, 1996, 6(4): 1150-1172.
[12] Verburg P H, Chen, Y. Multiscale characterization of land-use patterns in China[J]. Ecosystems, 2000, (3): 369-385.
[13] 乌日汗, 温小荣, 赵海霞, 等. 基于RS和GIS的深圳特区绿地景观动态分析及预测[J]. 北京林业大学学报, 2010, (6): 42-47.
[14] 彭月, 魏虹, 朱韦. 基于马尔科夫模型的土地景观动态模拟预测研究——以重庆永川市为例[J]. 安徽农业科学, 2006, 34(23): 6172-6173.
[15] 边延辉, 张光辉, 包洪福, 等. 马尔柯夫模型在洪河湿地景观变化研究中的应用[J]. 东北农业大学学报, 2008, 39(3): 53-57.
[16] 陈贵廷, 吕世海, 吴新宏. 呼伦贝尔森林草原区水土流失动态变化[J]. 草地学报, 2009, 17(5): 608-613.
[17] 韩宇平, 阮本清, 周杰. 马尔柯夫链模型在区域干旱风险研究中的应用[J]. 内蒙古师范大学学报, 2003, 32(1): 65-70.
[18] 闫金凤, 陈曦, 方晖. 三工河流域土地转移空间分析[J]. 干旱区资源与环境, 2003, 17(5): 98-101.
[19] 李素英, 李晓兵, 王丹丹. 基于马尔柯夫模型的内蒙古锡林浩特典型草原退化格局预测[J]. 生态学杂志, 2007, 26(1): 78-82.
[20] 徐岚, 赵羿. 利用马尔柯夫过程预测东陵区土地利用格局的变化[J]. 应用生态学报, 1993, 4(3): 272-277.
[21] Bell E J. Markov analysis of land use change: an application of stochastic processes to remotely sensed data[J]. Socio-Econ Planning Science, 1974, (8): 311-316.
[22] Bell E J, Hinojosa R C. Markov analysis of land use change: continuous time and stationary processes[J]. Socio-Econ Planning Science, 1977, (11): 13-17.
[23] 吴波, 苏志珠, 杨晓晖, 等. 荒漠化监测与评价指标体系框架[J]. 林业科学研究, 2005, 18(4): 490-496.
[24] Townshend J R G. Global land cover classification by remote sensing: present capabilities and future possibilities[J]. Remote Sensing of Environment, 1991, (35): 243-255.
[25] Lloyd D. A phenological classification of terrestrial vegetation cover using shortwave vegetation index imagery[J]. Remote Sensing, 1990, 11(12): 2269-2279.