基于遥感生态指数的京郊南部城市生态评价--以涿州市、固安县为例  

Ecological evaluation of cities in southern Beijing suburbs based on remote sensing ecological index:taking Zhuozhou City and Gu’an County as examples

作　　者：温小乐[1] 陈旭[1] 徐涵秋[1] WEN Xiaole;CHEN Xu;XU Hanqiu(College of Environment and Safety Engineering,Fuzhou University,Fuzhou,Fujian 350108,China)

机构地区：[1]福州大学环境与安全工程学院,福建福州350108

出　　处：《福州大学学报（自然科学版）》2022年第2期286-292,共7页Journal of Fuzhou University(Natural Science Edition)

基　　金：福建省自然科学基金资助项目(2019J01649)。

摘　　要：以毗邻北京南郊的涿州市、固安县为例,选取1997年Landsat5 TM影像、2009年Landsat5 TM和2017年Landsat8 OLI影像构建遥感生态指数(RSEI),对1997—2017年间涿州市和固安县的生态状况及其变化趋势进行分析评价.结果显示:研究区RSEI和Wet、NDSI关系相比于NDVI、LST相关性更高;在乡镇级别上,植被占比与区域RSEI呈指数关系.研究区RSEI均值由1997年的0.66下降至2017年的0.50,降幅达24%;生态改善的面积仅占总面积的15%,而生态下降的面积占到59%.研究区生态状况总体上呈现下降态势,环城镇中心地带和研究区南部生态下降明显.2009—2017年较1997—2009年生态下降趋势放缓.Taking Zhuozhou City and Gu’an County adjacent to the southern suburbs of Beijing as an example,the remote sensing ecological index(RSEI)was constructed by selecting Landsat5 TM images in 1997,Landsat5 TM images in 2009 and Landsat8 OLI images in 2017 to analyze and evaluate the ecological status and change trend of Zhuozhou and Gu’an County from 1997 to 2017.The results show that the correlation between remote sensing ecological index(RSEI),Wet and NDSI in the study area is higher than that between NDVI and LST.At the township level,there is an exponential relationship between vegetation proportion and regional remote sensing ecological index(RSEI).The average remote sensing ecological index(RSEI)in the study area decreased from 0.66 in 1997 to 0.50 in 2017,a decrease of 24%.Ecological improvement accounts for only 15%of the total area,while ecological decline accounts for 59%.The ecological condition of the study area declined on the whole,and the ecological condition of the central area around the town and the southern part of the study area declined significantly.The ecological decline in 2009 to 2017 was slower than that in 1997 to 2009.

关 键 词：生态评价 遥感生态指数 涿州市 固安县 

分 类 号：X821[环境科学与工程—环境工程] TP79[自动化与计算机技术—检测技术与自动化装置]