彰武县沙化信息提取及动态监测研究  

Research on extracting the information of desertification area and dynamic monitoring in Zhangwu County

作　　者：任东风[1] 齐欢 赵俊宇 REN Dongfeng;QI Huan;ZHAO Junyu(School of Surveying and Geography Science, Liaoning Technical University,Fuxin 123000,China;China Railway Construction Bridge Engineering Bureau Group Co.,Ltd,Changchun 130000,China)

机构地区：[1]辽宁工程技术大学测绘与地理科学学院,辽宁阜新123000 [2]中国铁建大桥工程局集团有限公司,吉林长春130000

出　　处：《测绘工程》2020年第6期49-55,共7页Engineering of Surveying and Mapping

基　　金：国家自然科学基金资助项目(41201208,0971124);博士基金资助项目(17-1093)。

摘　　要：以沙漠化问题突出的彰武县作为研究区,基于Landsat影像采用决策树分类模型提取2008年、2013年和2018年的沙化土地信息。运用转移矩阵和景观格局指数对分类结果综合分析,同时采用马尔科夫模型预测2023年土地沙化趋势。结果表明:2008—2018年彰武县非沙化土地面积大幅度增加;轻度沙化土地面积先增大后减少;中度和重度沙化土地面积显著下降,沙化程度明显减轻;预测2023年非沙化土地面积增长到2505.9704 km2,占总面积的69.21%,重度沙化土地面积几乎为0。To a more prominent problem of desertification in Zhangwu County for example,based on the Landsat remote sensing images,the desertification information of the study area in 2008,2013 and 2018 was extracted by using decision tree model.The classification results were synthetically analyzed by transfer matrix and landscape metrics,and the trend of land desertification was predicted by Markov model.The result showed that the area of non-desertification land increased greatly from 2008 to 2018.The area of slight desertification land firstly increased and then decreased.The moderate and severe desertification area decreased significantly,and the degree of desertification was greatly reduced.It predicted that the non-desertification land area would increase to 2505.9704 km2 in 2023,accounting for 69.21%of the total area.The severe desertification area would be almost 0,and the degree of desertification would be further reduced on the original basis.

关 键 词：彰武县 沙化信息 决策树分类模型 马尔科夫模型 景观格局分析 

分 类 号：P236[天文地球—摄影测量与遥感]