Effects of land use/cover on surface water pollution based on remote sensing and 3D-EEM fluorescence data in the Jinghe Oasis

Scientific Reports
Xiaoping Wang, Fei Zhang

Abstract

The key problem in the reasonable management of water is identifying the effective radius of surface water pollution. Remote sensing and three-dimensional fluorescence technologies were used to evaluate the effects of land use/cover on surface water pollution. The PARAFAC model and self-organizing map (SOM) neural network model were selected for this study. The results showed that four fluorescence components, microbial humic-like (C1), terrestrial humic-like organic (C2, C4), and protein-like organic (C3) substances, were successfully extracted by the PARAFAC factor analysis. Thirty water sampling points were selected to build 5 buffer zones. We found that the most significant relationships between land use and fluorescence components were within a 200 m buffer, and the maximum contributions to pollution were mainly from urban and salinized land sources. The clustering of land-use types and three-dimensional fluorescence peaks by the SOM neural network method demonstrated that the three-dimensional fluorescence peaks and land-use types could be grouped into 4 clusters. Principal factor analysis was selected to extract the two main fluorescence peaks from the four clustered fluorescence peaks; this study found that the relation...Continue Reading

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Citations

Mar 8, 2020·International Journal of Environmental Research and Public Health·Se-Rin Park, Sang-Woo Lee
May 1, 2019·Scientific Reports·Jyh-Jaan Steven HuangIan W Croudace
Aug 10, 2021·ACS Applied Materials & Interfaces·Jing ZhangFengwei Huo

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Methods Mentioned

BETA
fluorescence imaging
Fluorescence

Software Mentioned

Excel
ArcGIS10
Origin
ENVI
SOM
Environment for Visualizing Images ENVI
PARAFAC
MATLAB

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