基于决策树的城市黑臭水体遥感分级  

Remote Sensing Classification of Urban Black-odor Water Based on Decision Tree

作　　者：李玲玲 李云梅[1,2] 吕恒 徐杰[1] 杨子谦[1] 毕顺 许佳峰 LI Ling-ling;LI Yun-mei;LüHeng;XU Jie;YANG Zi-qian;BI Shun;XU Jia-feng(Key Laboratory of Virtual Geographic Environment of Education Ministry,Nanjing Normal University,Nanjing 210023,China;Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application,Nanjing 210023,China)

机构地区：[1]南京师范大学虚拟地理环境教育部重点实验室,南京210023 [2]江苏省地理信息资源开发与利用协同创新中心,南京210023

出　　处：《环境科学》2020年第11期5060-5072,共13页Environmental Science

基　　金：国家重点研发计划项目(2017YFB0503902);国家水体污染控制与治理科技重大专项(2017ZX07302003)。

摘　　要：水体黑臭程度遥感监测是了解城市水质现状和综合评价城市水环境治理效果的重要手段.以南京、常州、无锡和扬州为研究区,共采集171个样点,同步测量水质参数和光学参数,分析黑臭水体与一般水体的水色和光学特征,构建决策树模型进行重度黑臭水体、轻度黑臭水体和非黑臭水体(记为一般水体)识别.结果表明:(1)根据色度可将水体分为1~6类水体,其中,类型1~4为黑臭水体,分别为灰黑色、深灰色、灰色和浅灰色水体,类型5和类型6水体为一般水体,分别为绿色系和黄色系水体;(2)类型1水体的非色素颗粒物和有色可溶性有机物含量高,但色素颗粒物的吸收并不占主导,类型2和5水体的吸收以色素颗粒物吸收占主导,类型3、4和6水体的吸收以非色素颗粒物吸收占主导;(3)根据六类水体的反射光谱差异用黑臭水体差值指数(difference of black-odorous water index,DBWI)、三波段面积水体指数(green-red-nir area water index,G-R-NIR AWI)、绿光波段反射率和归一化黑臭水体指数(normalized difference black-odorous water index,NDBWI)构建的水体分类识别决策树,能够有效识别出重、轻度黑臭水体和一般水体;(4)将决策树模型应用于2019年4月9日扬州的PlanetScope影像上,并利用10个同步过境点进行验证,整体识别精度达到80.00%,K值达到0.67.通过水色分类后的城市水体分级模型方法,可推广应用于类似的水体,为黑臭水体监管提供技术方法.Remote sensing monitoring of black-odor water is an important method for understanding the current status of urban water quality,and comprehensively evaluating the effect of urban water environment treatment.A total of 171 samples were collected in Nanjing,Changzhou,Wuxi,and Yangzhou cities and water quality parameters and optical parameters were measured simultaneously.Based on the analysis of the water color and optical characteristics of the black-odor water and non-black-odor water(denoted as general water),a decision tree was constructed to identify the severe,mild black-odor water,and general water as green and yellow water.The results found that:(1)According to the water color,the water bodies can be divided into six types.Among them,type 1 to 4 water bodies are black-odor water,which are gray black,dark gray,gray,and light gray water,respectively,and type 5 and 6 water bodies are general water,which are green and yellow water,respectively;(2)Type 1 water body contains high contents of non-pigmented particulate matter and colored dissolved organic matter(CDOM),however,the absorption of pigmented particulate matter is not dominant.Type 2 and 5 water bodies are dominated by pigmented particulate matter.Type 3,4,and 6 water bodies are dominated by non-pigmented particulate matter;(3)After water color classification,and according to the differences of the reflection spectrums of the six types of water bodies,the difference of black-odorous water index(DBWI),green-red-nir area water index(G-R-NIR AWI),the green band reflectance and the normalized difference black-odorous water index(NDBWI)were used to construct a decision tree to identify the severe,mild black-odor water,and general water;(4)The decision tree was applied to the PlanetScope satellite image of Yangzhou City on April 9,2019,and 10 synchronous sampling points were used for verification.The overall recognition accuracy reached 80.00%,and the K value reached 0.67.The urban water classification model,after water color classification,can be applied to

关 键 词：城市黑臭水体 遥感分级 决策树 光学特性 PlanetScope卫星影像 

分 类 号：X87[环境科学与工程—环境工程]