Literature DB >> 29965666

[Remote Sensing Identification of Urban Black-Odor Water Bodies Based on High-Resolution Images:A Case Study in Nanjing].

Shuang Wen1, Qiao Wang2, Yun-Mei Li1, Li Zhu2, Heng Lü1, Shao-Hua Lei1, Xiao-Lei Ding1, Song Miao1.   

Abstract

The identification of urban black-odor water bodies plays an important role in monitoring and controlling black-odor water bodies. In 2016, a ground survey was conducted on the urban reach of Nanjing, and 55 samples from the West Shazhou River, Tuwei River, Xuanwu Lake, and Jinchuan River were obtained. The spectral characteristics of urban black-odor water bodies and other water bodies were analyzed. Recognition algorithms for GF-2 data were proposed in order to analyze the spatial distribution and environmental factors of urban black-odor water bodies. These algorithms were single-band thresholds based on reflectance of the green band, the difference between the blue band and green band, the ratio of the green band and red band, and the chromaticity value. The results indicate that:① compared with other types of water, the urban black-odor water has the smallest spectral slope in the range of 400-500 nm and lowest reflectivity, and the peaks and valleys are not prominent in the whole visible range; ② based on the verification, the accuracy of the ratio algorithm is the highest; and ③ using the ratio algorithm to calculate the GF-2 data of November 3, 2016, a total of 11 black river sections are identified. The entire length is 40.7 km, and the area is 0.749 km2.The black-odor water sections are distributed over a wide range but are not continuous, and they are concentrated in the densely populated areas. Domestic sewage, industrial waste water, and broken river channel are the main reasons.

Entities:  

Keywords:  GF-2; Nanjing; recognition algorithm; spectra characteristics; urban black-odor water bodies

Year:  2018        PMID: 29965666     DOI: 10.13227/j.hjkx.201703264

Source DB:  PubMed          Journal:  Huan Jing Ke Xue        ISSN: 0250-3301


  1 in total

1.  Comparative Study on Recognition Models of Black-Odorous Water in Hangzhou Based on GF-2 Satellite Data.

Authors:  Zhifeng Yu; Qiyu Huang; Xiaoxue Peng; Haijian Liu; Qin Ai; Bin Zhou; Xiaohong Yuan; Meihong Fang; Ben Wang
Journal:  Sensors (Basel)       Date:  2022-06-17       Impact factor: 3.847

  1 in total

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