TY - GEN
T1 - Water quality analysis of remote sensing images based on inversion model
AU - Wang, Jinzhe
AU - Zhang, Junping
AU - Li, Tong
AU - Wang, Xiao
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/31
Y1 - 2018/10/31
N2 - The spectrum of water is directly related to thein composition of the water, so water quality can be estimated by spectral reflectance. In this paper, the inversion model of water quality parameters for remote sensing images is established, based on which the status of water pollution is analyzed. Firstly, the spectral information of water in studied area is extracted from remote sensing images. Then, the relationship between spectral reflectance and water quality parameters is modeled. The model is evaluated by the fitting SSE (Sum of the Squared Errors), R-square, RMSE (the Root Mean Squared Errors) and Adjusted R-square. When R-square and Adjusted R-square are close to 1 and the SSE and RMSE are close to 0, inversion model is considered to be built up successfully. The experiments are conducted on 14 Landsat 8 OLI images in recent four years and the results show that the model method can realize the analysis and monitoring of the water quality. The R-square of the permanganate and dissolved oxygen were 0.96 and 0.80 respectively, which satisfied the requirements of the application.
AB - The spectrum of water is directly related to thein composition of the water, so water quality can be estimated by spectral reflectance. In this paper, the inversion model of water quality parameters for remote sensing images is established, based on which the status of water pollution is analyzed. Firstly, the spectral information of water in studied area is extracted from remote sensing images. Then, the relationship between spectral reflectance and water quality parameters is modeled. The model is evaluated by the fitting SSE (Sum of the Squared Errors), R-square, RMSE (the Root Mean Squared Errors) and Adjusted R-square. When R-square and Adjusted R-square are close to 1 and the SSE and RMSE are close to 0, inversion model is considered to be built up successfully. The experiments are conducted on 14 Landsat 8 OLI images in recent four years and the results show that the model method can realize the analysis and monitoring of the water quality. The R-square of the permanganate and dissolved oxygen were 0.96 and 0.80 respectively, which satisfied the requirements of the application.
KW - Inversion model
KW - Multi-temporal water quality monitoring
KW - Remote sensing
UR - https://www.scopus.com/pages/publications/85064213571
U2 - 10.1109/IGARSS.2018.8519442
DO - 10.1109/IGARSS.2018.8519442
M3 - 会议稿件
AN - SCOPUS:85064213571
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 4861
EP - 4864
BT - 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Y2 - 22 July 2018 through 27 July 2018
ER -