萍乡市土地利用变化及生态环境质量评价  

Research on Land Use Change and Evaluation of Ecological Environment Quality of Pingxiang City

作　　者：万安国 王建强[2] 王东东 Wan Anguo;Wang Jianqiang;Wang Dongdong(Meteorological Bureau of Duchang County,Jiujiang 332600,China;Faculty of Geomatics,East China University of Technology,Nanchang 330013,China;Institute of Nuclear Industry of 290,Shaoguan 512029,China)

机构地区：[1]都昌县气象局,江西九江332600 [2]东华理工大学测绘工程学院,江西南昌330013 [3]核工业二九〇研究所,广东韶关512029

出　　处：《气象与减灾研究》2021年第1期58-66,共9页Meteorology and Disaster Reduction Research

基　　金：江西省自然科学基金项目(编号:20202BABL202046).

摘　　要：文中基于2002、2007、2013和2018年Landsat遥感数据,采用支持向量机法提取了萍乡市的土地利用信息,通过提取绿度指标、干度指标、湿度指标和热度指标,利用主成分分析法构建萍乡市遥感生态指数(RSEI),分析了2002-2018年萍乡市的土地利用变化及生态环境情况。结果表明:1)2002-2018年建设用地持续增多,水域、林地和耕地先减后增,总体呈减少态势;草地先增后减,总体呈增加态势;未利用地先减后增,总体呈增加态势。2)2002-2018年萍乡市的生态环境以“一般”和“良好”为主,各区县的生态环境存在很大的差异性。3)林地、草地和水域位置的生态环境相对偏好,而建设用地和未利用地位置的生态环境相对偏差。Based on Landsat remote sensing data in 2002,2007,2013 and 2018,this paper used Support Vector Machine method to extract land use information of Pingxiang city.Extracting greenness index,dryness index,wet index and heat index,meanwhile,it used principal component analysis to construct the RSEI of the study area,and analyzed the land use change and ecological environment of the study area from 2002 to 2018.The results showed that:1)Construction land continued to increase from 2002 to 2018;waters,woodland and arable land first decreased and then increased,showing an overall decreased trend;grassland increased first and then decreased,showing an overall increased trend;unused land first decreased and then increased,showing an overall increased trend.2)From 2002 to 2018,the ecological environment of the study area was always“normal”and“good”;the ecological environment of various districts and counties had great differences.3)The ecological environment of woodland,grassland and water area were relatively good,while the ecological environment of construction land,cultivated land and unused land were relatively poor.

关 键 词：土地利用信息 卫星遥感 生态环境 RSEI 评价指标 

分 类 号：TP79[自动化与计算机技术—检测技术与自动化装置]