Früher|Nächster

Remote sensing identification of urban black-odor water bodies in Shenyang city based on GF-2 image

  • role： First author第一作者
  • Affiliation：

    Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China

    Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China

  • Email：yao926983@163.com
  • Introduction：姚月，1993年生，女，硕士研究生，研究方向为水色遥感、水环境遥感监测。E-mail：yao926983@163.com
Yue YAO12,  
  • role： Corresponding author通信作者
  • Affiliation：

    Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China

  • Email：shenqian@radi.ac.cn
  • Introduction：申茜，1981年生，女，副研究员，研究方向为高光谱遥感、水色遥感。E-mail：shenqian@radi.ac.cn
Qian SHEN2*,  
  • Affiliation：

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

Li ZHU3,  
  • Affiliation：

    Chinese Research Academy of Environmental Sciences, Beijing 100012, China

Hongjie GAO4,  
  • Affiliation：

    Xinrong Land and Housing Investigation and Techniques Institute, Chongqing 400020, China

Hongye CAO5,  
  • Affiliation：

    Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China

    Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China

Hui HAN16,  
  • Affiliation：

    Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China

    Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China

Jianguo SUN16,  
  • Affiliation：

    Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China

Junsheng LI2

Resümee

The situation of urban black and odorous water in China is serious, but the monitoring of this water is just starting from remote sensing and many problems need to be solved. The research provides technical support for the effective regulation of urban black and odorous river. Taking the main rivers in the urban built-up area of Shenyang city as the research object, we carried out ground surveys from 2015—2016 years, and obtained 46 general water samples in Hun river and Pu river, and 50 black and odorous water samples in Huishanming channel, Mantang river, Xi river, the river near the Weishanhu road, and the river of north of Dingxiang Lake, including the water spectrum and water quality parameters. Through the analysis of spectral characteristics of the black-odor water and general water , we found that the urban black and odorous water reflectance spectra in green - red band is gentler than the general water, then we put forward an index of BOI (Black and Odorous water Index) based on the reflectivity spectrum of black and odorous water recognition model. By comparing the BOI index with the ratio index of red and green bands (Wen, et al., 2018), BOI index has better recognition accuracy. The results show that: (1) When BOI based on the remote sensing reflectance (Rrs) is less than the threshold of 0.065, which can be awarded as black and odorous water. (2) Due to the difficulties of accurate atmospheric correction in GF2 image, Rayleigh scattering correction reflectance (Rrc) can be used to replace Rrs. When BOI is less than 0.05, it can be discriminated as black and odorous water. And the simulation prove that when the aerosol optical thickness increases gradually, the spectral differences of black and odorous water and general water will decrease, so this method is applicable to the clear image with small aerosol optical thickness (such as AOT (550) ≤0.5). (3) BOI based on Rrc can be applied to GF2 image better, and has better recognition accuracy. The results that are extracted from the three images from 2015 to 2016 are showed that the black and odorous phenomenon of Mantang river and Xinkai river have been gradually improved, but Huishanming channel is still serious. In this paper, the identification algorithm of black and odorous water is mainly based on the spectral characteristics of Shenyang city, it has been validated only in Shenyang, and further verification in other cities. And it is necessary to consider the influence of various factors on the reflectivity of water body in the future.

Schlüsselwort

GF-2;urban black-odor water bodies;Black-Odor water Index;BOI;remote sensing recognition

References

  1. 1.
    Bai Y, He X Q, Pan D L, Zhu Q K and Gong F. 2009. The black water around the Changjiang (Yangtze) Estuary in the spring of 2003. Acta Oceanologica Sinica, 28(4): 23–31
  2. 2.
    Chen S J and Zhang C. 2002. Analysis on the black-odor of Songhua river in Harbin. Science and Technology Information(8): 69 (
  3. 3.
    China Centre for Resource Satellite Data and Application. 2014. GF-2[EB/OL]. (2014-10-15) [2017-04-05].
  4. 4.
    China Centre for Resource Satellite Data and Application. 2016. Calibration[EB/OL]. (2016-10-10) [2017-04-05].
  5. 5.
    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
  6. 6.
    Feng L, Hu C M, Han X X, Chen X L and Qi L. 2014. Long-term distribution patterns of chlorophyll-a concentration in China’s largest freshwater lake: meris full-resolution observations with a practical approach. Remote Sensing, 7(1): 275–299
  7. 7.
    Gordon H R. 1997. Atmospheric correction of ocean color imagery in the earth observing system era. Journal of Geophysical Research: Atmospheres, 102(D14): 17081–17106
  8. 8.
    Gordon H R and Wang M H. 1994. Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with seawifs: a preliminary algorithm. Applied Optics, 33(3): 443–452
  9. 9.
    Hu C M. 2009. A novel ocean color index to detect floating algae in the global oceans. Remote Sensing of Environment, 113(10): 2118–2129
  10. 10.
    Hu C M, Hackett K E, Callahan M K, Andréfouët S, Wheaton J L, Porter J W and Muller-Karger F E. 2003. The 2002 ocean color anomaly in the Florida Bight: a cause of local coral reef decline?. Geophysical Research Letters, 30(3): 51-1–51-4
  11. 11.
    Jia Y H, Liu Y, Zhao H and Jia L Y. 2007. The study and application of integrated pollution control technology in south canal in Shenyang. Jiangsu Environmental Science and Technology, 20(4): 27–30 (
  12. 12.
    Jin H X and Pan J. 2017. Urban black-odor water body remote sensing monitoring based on GF-2 satellite data fusion. Scientific and Technological Management of Land and Resources, 34(4): 107–117 (
  13. 13.
    Kutser T, Pierson D C, Kallio K Y, Reinart A and Sobek S. 2005. Mapping lake CDOM by satellite remote sensing. Remote Sensing of Environment, 94(4): 535–540
  14. 14.
    Kutser T, Tranvik L and Pierson D C. 2009. Variations in colored dissolved organic matter between boreal lakes studied by satellite remote sensing. Journal of Applied Remote Sensing, 3(1): 033538
  15. 15.
    Kutser T, Paavel B, Verpoorter C, Ligi M, Soomets T, Toming K and Casal G. 2016. Remote sensing of black lakes and using 810 nm reflectance peak for retrieving water quality parameters of optically complex waters. Remote Sensing, 8(6): 497
  16. 16.
    Li K M, Liu J, Jiang D and Liu B. 2005. Bioremediation and management of the Guliao River. Chinese Journal of Applied and Environmental Biology, 11(6): 742–746 (
  17. 17.
    Li X L, Zhang P C and Yu H C. 2003. Analysis on black color and odor of Weigong River in Shenyang. Environmental Protection Science, 29(5): 27–28 (
  18. 18.
    Ministry of Housing and Urban-Rural Development. 2015. Urban black odor water remediation work guide.
  19. 19.
    Ministry of Housing and Urban-Rural Development and Ministry of Environmental Protection. 2016. National urban black-odor water regulation platform.
  20. 20.
    Mobley C D. 1999. Estimation of the remote-sensing reflectance from above-surface measurements. Applied Optics, 38(36): 7442–7455
  21. 21.
    Pucciarelli S, Buonanno F, Pellegrini G, Pozzi S, Ballarini P and Miceli C. 2008. Biomonitoring of Lake Garda: identification of ciliate species and symbiotic algae responsible for the “black-spot” bloom during the summer of 2004. Environmental Research, 107(2): 194–200
  22. 22.
    Qi L, Hu C M, Duan H T, Cannizzaro J and Ma R H. 2014. A novel meris algorithm to derive cyanobacterial phycocyanin pigment concentrations in a eutrophic lake: theoretical basis and practical considerations. Remote Sensing of Environment, 154: 298–317
  23. 23.
    Rixen T, Baum A, Pohlmann T, Balzer W, Samiaji J and Jose C. 2008. The Siak, a tropical black water river in Central Sumatra on the verge of anoxia. Biogeochemistry, 90(2): 129–140
  24. 24.
    Rixen T, Baum A, Sepryani H, Pohlmann T, Jose C and Samiaji J. 2010. Dissolved oxygen and its response to eutrophication in a tropical black water river. Journal of Environmental Management, 91(8): 1730–1737
  25. 25.
    Rusch A, Töpken H, Böttcher M E and Höpner T. 1998. Recovery from black spots: results of a loading experiment in the Wadden Sea. Journal of Sea Research, 40(3–4): 205–219
  26. 26.
    Sun L, Yu H Y, Fu Q Y, Wang J, Tian X P and Mi X T. 2016. Aerosol optical depth retrieval and atmospheric correction application for GF-1 PMS supported by land surface reflectance data. Journal of Remote Sensing, 20(2): 216–228 (
  27. 27.
    Tang J W, Tiang G L, Wang X Y, Wang X M and Song Q J. 2004. The methods of water spectra measurement and analysis I: above-water method. Journal of Remote Sensing, 8(1): 37–44 (
  28. 28.
    The State Council. 2015. Action plan of water pollution prevention.
  29. 29.
    Vermote E F and Vermeulen A. 1999. Atmospheric Correction Algorithm: Spectral Reflectances (MOD09) Version 4.0. [s.l.]: NASA contract NAS5-96062.
  30. 30.
    Wang M H and Shi W. 2007. The NIR-SWIR combined atmospheric correction approach for MODIS ocean color data processing. Optics Express, 15(24): 15722–15733
  31. 31.
    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 (
  32. 32.
    Ying T L, Zhang G Y and Wu X X. 1997. The mechanism of blackening and stink and effects of resuspended sediments on Suzhou Creek water quality. Shanghai Environmental Sciences, 16(1): 23–26 (
  33. 33.
    Zhang M W, Tang J W, Dong Q, Duan H T and Shen Q. 2014. Atmospheric correction of HJ-1 CCD imagery over turbid lake waters. Optics Express, 22(7): 7906–7924
  34. 34.
    Zhang Y L, Shi K, Liu J J, Deng J M, Qin B Q, Zhu G W and Zhou Y Q. 2016. Meteorological and hydrological conditions driving the formation and disappearance of black blooms, an ecological disaster phenomena of eutrophication and algal blooms. Science of the Total Environment, 569–570: 1517–1529
  35. 35.
    Zhao S T, Lin J W, Wang Y G, Dong Y H, Li H B, Zhang P and Xie D Q. 2014. Evaluation and countermeasures to be taken to treat the polluted water of the middle and upper reaches of Shenyang Huishan Channel. Journal of Safety and Environment, 14(4): 267–271 (
  36. 36.
    Zou L, Zhang B, Li J S, Shen Q, Zhang F F and Wang G L. 2014. A study on retrieval algorithm of black water aggregation in Taihu Lake based on HJ-1 satellite images. IOP Conference Series: Earth and Environmental Science, 17(1): 012100

Lesen Sie die ganze Passage

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