Abstract

JIANGHONG, Mo; XINLING, Tian  and  WEI, Shen. Tracing the source of heavy metal pollution in water sources of tourist attractions based on GIS remote sensing. Earth Sci. Res. J. [online]. 2021, vol.25, n.2, pp.207-214.  Epub Oct 18, 2021. ISSN 1794-6190.  https://doi.org/10.15446/esrj.v25n2.84631.

To effectively prevent heavy metal pollution in water sources in tourist attractions, clarify the degree of control of heavy metal pollution sources, and improve the accuracy of tracing results, a GIS-based remote sensing method of heavy metal pollution in tourist attractions is proposed. Using GIS spatial analysis method, the DEM elevation data monitored by remote sensing is obtained, the watershed geographic information is compiled, and the GPS obtains the longitude and latitude coordinates to locate the source of heavy metal pollution. The plug-in application framework is designed, and the watershed geographic information and plug-in application framework are integrated to build the pollution tracing platform. According to the mixing direction of pollutants after entering the water source, the migration and diffusion coordinate system of heavy metal pollution in the water source is established. The spatial-temporal distribution function model of heavy metal pollutants in water sources is constructed through the migration, transformation, and concentration of heavy metal pollutants in water sources. The tracing results of heavy metal pollution in water sources of scenic spots are obtained. The results showed that the order of variation coefficient of heavy metal pollution elements was Cr > Cd > Cu > Ni > Zn > Pb. The spatial distribution of heavy metal pollution elements was extremely uneven. There was a certain positive correlation between Ni and Cr, and the correlation coefficient of Cu and Zn was 0.78. The positive correlation was very significant, and the homology was very strong. Moreover, the identification result of the proposed method is very close to the real value, which can accurately trace the source of heavy metal pollution in the water source of tourist attractions, with small tracing error and high accuracy of tracing result evaluation.

Keywords : GIS remote sensing technology; tourist attractions; heavy metal pollution; pollution tracing; coefficient of variation; correlation analysis.

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