Précédent|Prochain

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

  • role： First author第一作者
  • Affiliation：

    Institute of Remote Sensing Application and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China

  • Email：lijiaqi_wrs@163.com
  • Introduction：李佳琦，1994年生，女，硕士研究生，研究方向为水环境遥感监测应用。E-mail：lijiaqi_wrs@163.com
LI Jiaqi12,  
  • role： Corresponding author通信作者
  • Affiliation：

    Institute of Remote Sensing Application and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

  • Email：jacoli@126.com
  • Introduction：李家国，1982年生，男，副研究员，研究方向为传感器辐射定标与校正、水环境遥感监测、遥感大数据快速处理。E-mail：jacoli@126.com
LI Jiaguo1*,  
  • Affiliation：

    Satellite Environment Center, Ministry of Environmental Protection, Beijing 100094, China

ZHU Li3,  
  • Affiliation：

    Institute of Remote Sensing Application and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

SHEN Qian1,  
  • Affiliation：

    College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China

DAI Huayang2,  
  • Affiliation：

    Institute of Remote Sensing Application and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China

    College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China

ZHU Yunfang12

résumé

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.

mots-clés

black and odorous water;remote sensing identification;water cleanliness index;interpretation symbol;Taiyuan city;WCI

References

  1. 1.
    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
  2. 2.
    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
  3. 3.
    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
  4. 4.
    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
  5. 5.
    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
  6. 6.
    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
  7. 7.
    Lin P. 2015. Interpretation of " urban black odor work guide”. Construction Science and Technology(8): 14–15, 21
  8. 8.
    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
  9. 9.
    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
  10. 10.
    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
  11. 11.
    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
  12. 12.
    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
  13. 13.
    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
  14. 14.
    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
  15. 15.
    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
  16. 16.
    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
  17. 17.
    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
  18. 18.
    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
  19. 19.
    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
  20. 20.
    Zhang B, Li J S, Wang Q and Shen Q. 2012. Hyperspectral Remote Sensing of Inland Waters. Beijing: The Science Publishing Company: 130-131
  21. 21.
    Zhou W R. 2006. Study on Black and Stink Issue of Fen River in Taiyuan City Zone. Taiyuan: Taiyuan University of Technology

Lire l'article complet

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website