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引用本文:张晓祥,唐彦君,严长清,徐 盼,朱晨曦,戴煜暄.近30年来江苏海岸带土地利用/覆被变化研究[J].海洋科学,2014,38(9):90-95.
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近30年来江苏海岸带土地利用/覆被变化研究
张晓祥1,2, 唐彦君1, 严长清2,3, 徐 盼1, 朱晨曦2,3, 戴煜暄1
1.河海大学 地理信息科学与工程研究所;2.国土资源部海岸带开发与保护重点实验室;3.江苏省土地勘测规划院
摘要:
海岸带土地利用/覆被变化(LUCC)研究可用于量化反应环境变化和人类活动的影响, 为海岸带开发与利用提供决策参考依据。以江苏海岸带为研究对象, 选取1978~2007年5期Landsat MSS/TM 影像作为数据源, 建立遥感分类系统, 采用分层分类监督分类方法获取研究区5期序列LUCC 数据, 进而计算分析江苏海岸带近30年的土地利用/覆被变化的结构演变, 系统研究了近30年来的LUCC 的变化数量以及变化速率。研究结果表明: (1)从土地利用结构上看, 近30年来, 江苏海岸带土地利用类型以耕地、城镇建设用地、农村建设用地为主, 虽然耕地占比近年来有所减少, 但是仍然高达70%以上; (2)从土地利用变化来看, 江苏海岸带土地利用变化最为显著的是城镇建设用地, 无论是变化数量和变化速率都非常显著, 同时大量沿海新围垦土地多为建设用地。
关键词:  土地利用/覆被变化(LUCC)  海岸带  遥感影像  江苏
DOI:10.11759/hykx20121201001
分类号:
基金项目:国土资源部海岸带开发与保护重点实验室开放基金项目(2013CZEPK01)
The study of Jiangsu coastal land use/cover change based on series of remote sensing images in the last 30 years
Abstract:
Coastal land use/cover change (LUCC) research can be used for measuring the effects of environmental changes and human activities, which is helpful to the decision making of the coastal development and utilization. In this study, Jiangsu coastal area was chosen as the case study area to characterize the historical changes of land use and land cover. Based on Landsat MSS/TM images classification in Jiangsu coastal areas from 1978 to 2007, series of LUCC products were obtained by multi-level supervised classification and customized classification schema. Further, land use structure, as well as land use changes both in change amount and rate, were systematically calculated and analyzed. The results showed that: (1) From the perspective of the land use structure, the main land use types in Jiangsu coastal areas were croplands and construction lands. There has been a decrease in cropland in recent years, however, the ratio of croplands was as high as 70%. (2) From the perspective of the land use change, construction lands in cities and towns were significantly increased. At the same time, most of the new reclamation lands in the coastal areas were construction lands.
Key words:  land use/cover change  coastal area  remote sensing images  Jiangsu
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