摘要
利用遥感技术进行生态环境监测有利于快速了解生态环境的变化过程。以昆明市为研究区,以Landsat TM和OLI影像为数据源,采用主成分分析法,运用集成于绿度、湿度、干度和热度4个指标的遥感生态指数(remote sensing ecological index,RSEI),对昆明市2000-2018年生态环境质量进行了评价。结果表明:RSEI指数能较好地指示区域生态环境状况,研究区RSEI主要是受干度的影响,其次是湿度和绿度,热度对RSEI模型的影响最小;2000-2018年,昆明市RSEI 5年平均值为0.51,生态环境质量处于一般状态(0.4~0.6),生态环境质量呈现"上升-下降-上升-下降"的波动变化趋势。其中,2010年受干旱因素影响,生态环境质量较其他年份相对较低;昆明市生态环境质量西部优于东部,其中以西南角的生态环境质量最佳。
Using remote sensing technology to monitor ecological environment is a good way to quickly acquire the changes of ecological environment.Based on the data of Landsat TM and OLI images,we constructed a model of Remote Sensing Ecological Index(RSEI)with four indicators(greenness,humidity,dryness and heat)by using principal component analysis.This model was used to evaluate the ecological environment quality of Kunming during 2000-2018.The results showed that RSEI can well indicate the quality of regional ecological environment.RSEI was mainly affected by dryness,followed by humidity and greenness,with heat having the least influence.From 2000 to 2018,the five-year average of RSEI in Kunming was 0.51,and the ecological environment quality was in a general state(0.4-0.6).The quality of ecological environment showed a fluctuating trend of"rise-down-rise-down"over time.The quality of ecological environment was better in the western Kunming than in the eastern part,with the best in the southwest corner of Kunming.
作者
农兰萍
王金亮
NONG Lan-ping;WANG Jin-liang(College of Tourism and Geographic Sciences,Yunnan Normal University,Kunming 650500,China;Key Laboratory of Resources and Environmental Remote Sensing for Universities in Yunnan,Kunming 650500,China;Center for Geospatial Information Engineering and Technology of Yunnan Province,Kunming 650500,China)
出处
《生态学杂志》
CAS
CSCD
北大核心
2020年第6期2042-2050,共9页
Chinese Journal of Ecology
基金
国家重点研发计划政府间/港澳台重点专项项目“利用地理空间技术监测和评估土地利用/土地覆被变化对区域生态安全的影响”(2018YFE0184300)
欧盟文化执行署(EACEA)伊拉斯谟+国际高等教育能力建设项目“遥感教育与学习创新”(586037-EPP-1-2017-1-HU-EPPKA2-CBHE-JP)
国家自然基金项目(41561048)
云南省哲学社会科学重点项目(ZDZZD201506)
云南省中青年学术技术带头人(2008PY056)
云南省高校科技创新团队资助。
关键词
遥感生态指数
生态环境质量
变化监测
主成分分析
昆明市
remote sensing ecological index
ecological environment quality
change monitoring
principal component analysis
Kunming