Remote sensing identification and validation of urban black and odorous water in Taiyuan city

Jiaqi LI; Jiaguo LI; Li ZHU; Qian SHEN; Huayang DAI; Yunfang ZHU

doi:10.11834/jrs.20197292

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Remote sensing identification and validation of urban black and odorous water in Taiyuan city
Vol. 23, Issue 4, Pages: 773-784(2019)
Received：07 August 2017，

Accepted：21 March 2018，

Published：2019-07
DOI： 10.11834/jrs.20197292
稿件说明：

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李佳琦, 李家国, 朱利, 申茜, 戴华阳, 朱云芳. 2019. 太原市黑臭水体遥感识别与地面验证. 遥感学报, 23(4): 773–784 DOI： 10.11834/jrs.20197292.

Li J Q, Li J G, Zhu L, Shen Q, Dai H Y and Zhu Y F. 2019. Remote sensing identification and validation of urban black and odorous water in Taiyuan city. Journal of Remote Sensing, 23(4): 773–784 DOI： 10.11834/jrs.20197292.

摘要

城市黑臭水体整治是城市水环境治理的一项重要工作。本文通过构建黑臭水体遥感识别模型，解决城市黑臭水体整治过程中黑臭水体的识别问题，实现城市黑臭水体空间分布快速定位与排查。通过分析黑臭水体形成机理和试验数据，从光谱特征上构建反映水体清洁程度的光谱指数(WCI)，从图像特征上构建水体颜色、次生环境、河道淤塞、岸边带垃圾堆放等解译标志，综合光谱指数和解译标志共同进行黑臭水体遥感识别。利用该方法对太原市建成区内黑臭水体空间分布进行排查识别，共得到疑似黑臭河段14条，长度为52.530 km。经验证，除去断流影响外，遥感识别黑臭水体点位精度为92.86%，遥感识别黑臭河段长度精度为78.19%。在精度验证基础之上，进一步分析了黑臭水体遥感识别光谱指数和各项解译标志在黑臭识别中所占的权重，其中光谱指数和水体颜色二者权重最大，分别占29.60%和27.10%，是构成遥感识别黑臭水体的主要特征标志。通过两时相影像识别结果比对表明，WCI指数能够明显反应黑臭水体变化特征。因此，利用本文方法进行城市黑臭水体遥感识别具有很高的精度，在城市水环境整治过程中具有重要的应用价值。

Abstract

Treatment of urban black and odorous water is important in the control of urban water environment. A remote sensing recognition model of black and odorous water bodies was constructed in this study to identify the affected water bodies for treatment

determine their location

and investigate their space distribution. On the basis of the analysis of formation mechanism of black and odorous water and test data

we constructed a spectrum index called water cleanliness index (WCI) from spectrum characteristics to reflect water cleanliness. We also established interpretation signs from image characteristics

such as water color

secondary environment

river silting

and riparian garbage stacking. Combination of the spectral index and interpretation signs could be used to identify black and odorous water bodies. The proposed method was used to identify the space distribution of black and odorous water bodies in the built-up area of Taiyuan. A total of 14 black and odorous river sections with a length of 52.530 km were obtained. The point accuracy of remote sensing identification of black and odorous water bodies was 92.86%

and the river accuracy of remote sensing identification of black and odorous water bodies was 78.19% without the effects of dried-up rivers. The weights of the spectral index and interpretation signs in the remote sensing identification of black and odorous water bodies were analyzed on the basis of the results of black and odorous river sections. The spectral index and water color had the largest weights among them with 29.60% and 27.10%

respectively. Both of them constituted the main characteristics of remote sensing identification of black and odorous water bodies. Comparison of the results of the two-phase remote sensing image recognition showed that WCI could significantly reflect the change characteristics of black and odorous water bodies. Therefore

this method has high precision in recognizing urban black and odorous water bodies by remote sensing and can be applied in the control of urban water environment.

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Keywords

references

Canfield Jr D E, Linda S B and Hodgson L M. 1984. Relations between color and some limnological characteristics of Florida lakes. Journal of the American Water Resources Association, 20(3): 323–329

曹红业. 2017. 中国典型城市黑臭水体光学特性分析及遥感识别模型研究. 成都: 西南交通大学

Cao H Y. 2017. Study on Analysis of Optical Properties and Remote Sensing Identifiable Models of Black and Malodorous Water in Typical Cities in China. Chengdu: Southwest Jiaotong University

董崧, 臧淑英, 吴长山, 李苗. 2017. SPOT-7遥感图像融合技术对比研究. 测绘与空间地理信息, 40(1): 75–78

Dong S, Zang S Y, Wu C S and Li M. 2017. Comparison of different image fusion methods using SPOT-7. Geomatics and Spatial Information Technology, 40(1): 75–78

Duan H T, Ma R H, Loiselle S A, Shen Q S, Yin H B and Zhang Y C. 2014. Optical characterization of black water blooms in eutrophic waters. Science of the Total Environment, 482-483: 174–183

中国科学院遥感与数字地球研究所. 2017. 遥感技术首次辅助城市黑臭水体整治工作取得进展[EB/OL].[2017-04-25]. http://www.radi.ac.cn/dtxw/kjyw/201704/t20170420_4777980.html

Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences. 2017. Remote sensing technology for the first time to assist the progress of urban black odor water remediation work[EB/OL].[2017-04-25]. http://www.radi.ac.cn/dtxw/kjyw/201704/t20170420_4777980.html

Kutovaya O A and Watson S B. 2014. Development and application of a molecular assay to detect and monitor geosmin-producing cyanobacteria and actinomycetes in the Great Lakes. Journal of Great Lakes Research, 40(2): 404–414

林培. 2015. 《城市黑臭水体整治工作指南》解读. 建设科技(8): 14–15, 21

Lin P. 2015. Interpretation of " urban black odor work guide”. Construction Science and Technology(8): 14–15, 21

马跃良, 王云鹏, 贾桂梅. 2003. 珠江广州河段水体污染的遥感监测应用研究. 重庆环境科学, 25(3): 13–16

Ma Y L, Wang Y P and Jia G M. 2003. Application of remote sensing in monitoring water pollution in Guangzhou Section of the Pearl River. Chongqing Environmental Science, 25(3): 13–16

中华人民共和国环境保护部, 国家质量监督检验检疫总局. 2002. 地表水环境质量标准[EB/OL].[2019-03-29]. http://kjs.mee.gov.cn/hjbhbz/bzwb/shjbh/shjzlbz/200206/t20020601_66497.shtml

Ministry of Environmental Protection of People’s Republic of China and General Administration of Quality Supervision, Inspection and Quarantine of the People’s Republic of China. 2002. Environmental quality standards for surface water[EB/OL].[2019-03-29]. http://kjs.mee.gov.cn/hjbhbz/bzwb/shjbh/shjzlbz/200206/t20020601_66497.shtml

中华人民共和国住房和城乡建设部, 中华人民共和国环境保护部. 2015. 住房城乡建设部环境保护部关于印发城市黑臭水体整治工作指南的通知[EB/OL].[2017-04-25]. http://www.mohurd.gov.cn/wjfb/201509/t20150911_224828.html

Ministry of Housing and Urban-Rural Development. 2015. Urban black odor water remediation work guide[EB/OL].[2017-04-25]. http://www.mohurd.gov.cn/wjfb/201509/t20150911_224828.html

Sugiura N, Utsumi M, Wei B, Iwami N, Okano K, Kawauchi Y and Maekawa T. 2004. Assessment for the complicated occurrence of nuisance odours from phytoplankton and environmental factors in a eutrophic lake. Lakes and Reservoirs: Science, Policy and Management for Sustainable Use, 9(3/4): 195–201

孙淑雲, 古小治, 张启超, 陈开宁. 2016. 水草腐烂引发的黑臭水体应急处置技术研究. 湖泊科学, 28(3): 485–493

Sun S Y, Gu X Z, Zhang Q C and Chen K N. 2016. Research on an emergency treatment technology for black-odor water caused by macrophytes decaying. Journal of Lake Sciences, 28(3): 485–493

Wang G F, Li X N, Fang Y and Huang R. 2014. Analysis on the formation condition of the algae-induced odorous black water agglomerate. Saudi Journal of Biological Sciences, 21(6): 597–604

王旭, 王永刚, 孙长虹, 潘涛. 2016. 城市黑臭水体形成机理与评价方法研究进展. 应用生态学报, 27(4): 1331–1340

Wang X, Wang Y G, Sun C H and Pan T. 2016. Formation mechanism and assessment method for urban black and odorous water body: a review. Chinese Journal of Applied Ecology, 27(4): 1331–1340

王云鹏, 闵育顺, 傅家谟, 盛国英. 2001. 水体污染的遥感方法及在珠江广州河段水污染监测中的应用. 遥感学报, 5(6): 460–465

Wang Y P, Min Y S, Fu J M and Sheng G Y. 2001. Remote sensing method of water pollution and application on water pollution monitoring in Guangzhou Section of Pearl River. Journal of Remote Sensing, 5(6): 460–465

温爽, 王桥, 李云梅, 朱利, 吕恒, 雷少华, 丁潇蕾, 苗松. 2018. 基于高分影像的城市黑臭水体遥感识别: 以南京为例. 环境科学, 39(1): 57–67

Wen S, Wang Q, Li Y M, Zhu L, Lü H, Lei S H, Ding X L and Miao S. 2018. Remote sensing identification of urban black-odor water bodies based on high-resolution images: a case study in Nanjing. Environmental Science, 39(1): 57–67

谢飞, 吴俊锋. 2016. 城市黑臭河流成因及治理技术研究. 污染防治技术, 29(1): 1–3, 15

Xie F and Wu J F. 2016. Cuses of malodorous black rivers in cities and the study on treatment technologies. Pollution Control Technology, 29(1): 1–3, 15

徐明德, 彭静, 师莉红. 2008. 汾河太原城区段水体黑臭评价. 科技情报开发与经济, 18(31): 128–129

Xu M D, Peng J and Shi L H. 2008. Evaluation on malodorous and black water body in taiyuan district section of Fenhe River. Sci-Tech Information Development and Economy, 18(31): 128–129

姚俊, 曾祥福, 益建芳. 2003. 遥感技术在上海苏州河水污染监测中的应用. 影像技术(2): 3–7, 12

Yao J, Zeng X F and Yi J F. 2003. Using remote sensing technology to monitor water pollution of Shanghai Suzhou River. Image technology(2): 3–7, 12

张兵, 李俊生, 王桥, 申茜. 2012. 内陆水体高光谱遥感. 北京: 科学出版社: 130-131

Zhang B, Li J S, Wang Q and Shen Q. 2012. Hyperspectral Remote Sensing of Inland Waters. Beijing: The Science Publishing Company: 130-131

周文瑞. 2006. 汾河太原城区段河流黑臭问题研究. 太原: 太原理工大学

Zhou W R. 2006. Study on Black and Stink Issue of Fen River in Taiyuan City Zone. Taiyuan: Taiyuan University of Technology

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