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Urban black and odorous water body mapping from Gaofen-2 images

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Abstract Remote sensing technology has shown its irreplaceable advantages in the identification of urban black and odorous water body. However, the universality of the remote sensing recognition algorithm for the black and odorous water body is not clear in different regions. Thus, two typical cities, Shenyang and Nanjing, were selected from northern and southern China as the study areas. Four forms of recognition models of the black and odorous water body are built based on Gaofen-2 images, including the single-band model, difference model, ratio model, and water quality parameter model. Combined with the remote sensing interpretation marks of black and odorous water body, the recognition precision of black and odorous water body is analyzed by the methods of the confusion matrix and Kappa coefficient. The results show that the overall accuracy of the normalized difference black-odorous water index (NDBWI) model is higher than 80% in the northern and southern cities of China, with good consistency of spatial distribution. The accuracy of the black and odorous water index model and G model is higher than 75% only in the special areas of Nanjing or Shenyang. The accuracy of other models is generally low. Research show that the NDBWI model has better universality in the identification of urban black and odorous water body, and it is suitable for promotion and application. The remote sensing interpretation marks of black and odorous water body have shown a good auxiliary identification function. The research provides a technical foundation for large-scale and rapid identification of urban black and odorous water body.
Title: Urban black and odorous water body mapping from Gaofen-2 images
Description:
Abstract Remote sensing technology has shown its irreplaceable advantages in the identification of urban black and odorous water body.
However, the universality of the remote sensing recognition algorithm for the black and odorous water body is not clear in different regions.
Thus, two typical cities, Shenyang and Nanjing, were selected from northern and southern China as the study areas.
Four forms of recognition models of the black and odorous water body are built based on Gaofen-2 images, including the single-band model, difference model, ratio model, and water quality parameter model.
Combined with the remote sensing interpretation marks of black and odorous water body, the recognition precision of black and odorous water body is analyzed by the methods of the confusion matrix and Kappa coefficient.
The results show that the overall accuracy of the normalized difference black-odorous water index (NDBWI) model is higher than 80% in the northern and southern cities of China, with good consistency of spatial distribution.
The accuracy of the black and odorous water index model and G model is higher than 75% only in the special areas of Nanjing or Shenyang.
The accuracy of other models is generally low.
Research show that the NDBWI model has better universality in the identification of urban black and odorous water body, and it is suitable for promotion and application.
The remote sensing interpretation marks of black and odorous water body have shown a good auxiliary identification function.
The research provides a technical foundation for large-scale and rapid identification of urban black and odorous water body.

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