Inferring Water Quality in the Songhua River Basin Using Random Forest Regression Based on Satellite Imagery and Geoinformation DOI Creative Commons
Z. Yu, Hangnan Yu,

Lan Li

et al.

Hydrology, Journal Year: 2025, Volume and Issue: 12(3), P. 61 - 61

Published: March 17, 2025

Maintaining high water quality is essential not only for human survival but also social and ecological safety. In recent years, due to the influence of activities natural factors, has significantly deteriorated, effective monitoring urgently needed. Traditional requires substantial financial investment, whereas remote sensing random forest model reduces operational costs achieves a paradigm shift from discrete sampling points spatially continuous surveillance. The was adopted establish inversion three parameters (conductivity, total nitrogen (TN), phosphorus (TP)) during growing period (May September) 2020 2022 in Songhua River Basin (SRB), using Landsat 8 imagery China’s national section data. Model verification shows that R2 conductivity 0.67, followed by TN at 0.52 TP 0.47. results revealed downstream SRB (212.72 μS/cm) higher than upstream (161.62 μS/cm), with concentrations exhibiting similar increasing pattern. This study significant improving conservation health SRB.

Language: Английский

Inferring Water Quality in the Songhua River Basin Using Random Forest Regression Based on Satellite Imagery and Geoinformation DOI Creative Commons
Z. Yu, Hangnan Yu,

Lan Li

et al.

Hydrology, Journal Year: 2025, Volume and Issue: 12(3), P. 61 - 61

Published: March 17, 2025

Maintaining high water quality is essential not only for human survival but also social and ecological safety. In recent years, due to the influence of activities natural factors, has significantly deteriorated, effective monitoring urgently needed. Traditional requires substantial financial investment, whereas remote sensing random forest model reduces operational costs achieves a paradigm shift from discrete sampling points spatially continuous surveillance. The was adopted establish inversion three parameters (conductivity, total nitrogen (TN), phosphorus (TP)) during growing period (May September) 2020 2022 in Songhua River Basin (SRB), using Landsat 8 imagery China’s national section data. Model verification shows that R2 conductivity 0.67, followed by TN at 0.52 TP 0.47. results revealed downstream SRB (212.72 μS/cm) higher than upstream (161.62 μS/cm), with concentrations exhibiting similar increasing pattern. This study significant improving conservation health SRB.

Language: Английский

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