Published

2021-07-19

Tracing the source of heavy metal pollution in water sources of Tourist Attractions Based on GIS remote sensing

Trazabilidad de la contaminación por metales pesados en fuentes de agua de atracciones turísticas a través del Sistema de Información Geográfica

DOI:

https://doi.org/10.15446/esrj.v25n2.84631

Keywords:

GIS remote sensing technology, tourist attractions, heavy metal pollution, pollution tracing, coefficient of variation, correlation analysis (en)
Tecnología de teledetección SIG, atracciones turísticas, contaminación por metales pesados, rastreo de contaminación, coeficiente de variación, Análisis de correlación (es)

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Authors

  • Jianghong Mo School of Tourism Management, Guilin Tourism University, Guilin 541006 China
  • Xinling Tian College of Tourism Management, Enshi Polytechnic, Enshi 445000 China
  • Wei Shen School of Business Administration, Zhongnan University of Economics and Low, Wuhan 430074 China

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.

Para prevenir eficazmente la contaminación por metales pesados en las fuentes de agua en las atracciones turísticas, aclarar el grado de control de las fuentes de contaminación por metales pesados y mejorar la precisión de los resultados de rastreo, se propone un método de detección remota basado en SIG de la contaminación por metales pesados en las atracciones turísticas. Utilizando el método de análisis espacial SIG, se obtienen los datos de elevación DEM monitoreados por teledetección, se compila la información geográfica de la cuenca y se obtienen las coordenadas de longitud y latitud mediante GPS para ubicar la fuente de contaminación por metales pesados. El marco de la aplicación de complemento está diseñado, y la información geográfica de la cuenca hidrográfica y el marco de la aplicación de complemento están integrados para construir la plataforma de rastreo de la contaminación. De acuerdo con la dirección de mezcla de los contaminantes después de ingresar a la fuente de agua, se establece el sistema de coordenadas de migración y difusión de la contaminación por metales pesados en la fuente de agua. A través de la migración, transformación y concentración de contaminantes de metales pesados en la fuente de agua, se construye el modelo de función de distribución espacio-temporal de los contaminantes de metales pesados en la fuente de agua y se obtienen los resultados de rastreo de la contaminación por metales pesados en la fuente de agua de los lugares escénicos. Los resultados mostraron que el orden del coeficiente de variación de los elementos contaminantes por metales pesados fue Cr> Cd> Cu> Ni> Zn> Pb. La distribución espacial de los elementos contaminantes por metales pesados fue extremadamente desigual. Hubo cierta correlación positiva entre Ni y Cr, y el coeficiente de correlación de Cu y Zn fue de 0,78. La correlación positiva fue muy significativa y la homología fue muy fuerte. Además, el resultado de la identificación del método propuesto está muy cerca del valor real, que puede rastrear con precisión la fuente de contaminación por metales pesados en la fuente de agua de las atracciones turísticas, con un pequeño error de rastreo y una alta precisión en la evaluación del resultado del rastreo.

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How to Cite

APA

Mo, J. ., Tian, X. . and Shen, W. . (2021). Tracing the source of heavy metal pollution in water sources of Tourist Attractions Based on GIS remote sensing. Earth Sciences Research Journal, 25(2), 207–214. https://doi.org/10.15446/esrj.v25n2.84631

ACM

[1]
Mo, J. , Tian, X. and Shen, W. 2021. Tracing the source of heavy metal pollution in water sources of Tourist Attractions Based on GIS remote sensing. Earth Sciences Research Journal. 25, 2 (Jul. 2021), 207–214. DOI:https://doi.org/10.15446/esrj.v25n2.84631.

ACS

(1)
Mo, J. .; Tian, X. .; Shen, W. . Tracing the source of heavy metal pollution in water sources of Tourist Attractions Based on GIS remote sensing. Earth sci. res. j. 2021, 25, 207-214.

ABNT

MO, J. .; TIAN, X. .; SHEN, W. . Tracing the source of heavy metal pollution in water sources of Tourist Attractions Based on GIS remote sensing. Earth Sciences Research Journal, [S. l.], v. 25, n. 2, p. 207–214, 2021. DOI: 10.15446/esrj.v25n2.84631. Disponível em: https://revistas.unal.edu.co/index.php/esrj/article/view/84631. Acesso em: 28 mar. 2025.

Chicago

Mo, Jianghong, Xinling Tian, and Wei Shen. 2021. “Tracing the source of heavy metal pollution in water sources of Tourist Attractions Based on GIS remote sensing”. Earth Sciences Research Journal 25 (2):207-14. https://doi.org/10.15446/esrj.v25n2.84631.

Harvard

Mo, J. ., Tian, X. . and Shen, W. . (2021) “Tracing the source of heavy metal pollution in water sources of Tourist Attractions Based on GIS remote sensing”, Earth Sciences Research Journal, 25(2), pp. 207–214. doi: 10.15446/esrj.v25n2.84631.

IEEE

[1]
J. . Mo, X. . Tian, and W. . Shen, “Tracing the source of heavy metal pollution in water sources of Tourist Attractions Based on GIS remote sensing”, Earth sci. res. j., vol. 25, no. 2, pp. 207–214, Jul. 2021.

MLA

Mo, J. ., X. . Tian, and W. . Shen. “Tracing the source of heavy metal pollution in water sources of Tourist Attractions Based on GIS remote sensing”. Earth Sciences Research Journal, vol. 25, no. 2, July 2021, pp. 207-14, doi:10.15446/esrj.v25n2.84631.

Turabian

Mo, Jianghong, Xinling Tian, and Wei Shen. “Tracing the source of heavy metal pollution in water sources of Tourist Attractions Based on GIS remote sensing”. Earth Sciences Research Journal 25, no. 2 (July 19, 2021): 207–214. Accessed March 28, 2025. https://revistas.unal.edu.co/index.php/esrj/article/view/84631.

Vancouver

1.
Mo J, Tian X, Shen W. Tracing the source of heavy metal pollution in water sources of Tourist Attractions Based on GIS remote sensing. Earth sci. res. j. [Internet]. 2021 Jul. 19 [cited 2025 Mar. 28];25(2):207-14. Available from: https://revistas.unal.edu.co/index.php/esrj/article/view/84631

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CrossRef citations3

1. Xiaojun Zheng, Ohidul Alam, Yiwen Zhou, Daolin Du, Guanlin Li, Weihong Zhu. (2024). Heavy metals detection and removal from contaminated water: A critical review of adsorption methods. Journal of Environmental Chemical Engineering, 12(6), p.114366. https://doi.org/10.1016/j.jece.2024.114366.

2. Zhang Jing, Liu Kun Yi, Guo Chen Lin, Zhang Jian-min, Xing Bing. (2023). Assessment of potential ecological risk based on the vertical characteristics of potential toxic elements in sediments from a high-density cage culture reservoir in China. Ecotoxicology and Environmental Safety, 262, p.115136. https://doi.org/10.1016/j.ecoenv.2023.115136.

3. Min Wang, Shumin Liu, Chenxu Wang, Jun Yang. (2023). Spatial distribution and influencing factors of high-quality tourist attractions in Shandong Province, China. PLOS ONE, 18(7), p.e0288472. https://doi.org/10.1371/journal.pone.0288472.

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