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[Remote Sensing Classification of Urban Black-odor Water Based on Decision Tree].
Li, Ling-Ling; Li, Yun-Mei; LÜ, Heng; Xu, Jie; Yang, Zi-Qian; Bi, Shun; Xu, Jia-Feng.
Afiliação
  • Li LL; Key Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing 210023, China.
  • Li YM; Key Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing 210023, China.
  • LÜ H; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China.
  • Xu J; Key Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing 210023, China.
  • Yang ZQ; Key Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing 210023, China.
  • Bi S; Key Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing 210023, China.
  • Xu JF; Key Laboratory of Virtual Geographic Environment of Education Ministry, Nanjing Normal University, Nanjing 210023, China.
Huan Jing Ke Xue ; 41(11): 5060-5072, 2020 Nov 08.
Article em Zh | MEDLINE | ID: mdl-33124249
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:①According 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; ②Type 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; ③After 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; ④The 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 other similar water bodies, and provides a technical method for the supervision of black-odor water bodies.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Água / Tecnologia de Sensoriamento Remoto Tipo de estudo: Health_economic_evaluation / Prognostic_studies Idioma: Zh Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Água / Tecnologia de Sensoriamento Remoto Tipo de estudo: Health_economic_evaluation / Prognostic_studies Idioma: Zh Ano de publicação: 2020 Tipo de documento: Article