Published

2021-04-16

Dynamic monitoring algorithm of natural resources in scenic spots based on MODIS Remote Sensing technology

Algoritmo de monitoreo dinámico de recursos naturales en lugares escénicos con base en la tecnología de detección remota MODIS

DOI:

https://doi.org/10.15446/esrj.v25n1.93869

Keywords:

Scenic Spot, Remote Sensing Technology, Natural Resources, Dynamic Monitoring, MODIS Remote Sensing Data, Forest Resources (en)
Lugar escénico, Teledetección, Recursos naturales, Monitoreo dinámico, Datos de teledetección MODIS, Recursos forestales (es)

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Authors

  • Maolin Li School of Tourism Management, Guilin Tourism University, Guilin 541006, China

A dynamic monitoring algorithm of natural resources in scenic spots based on MODIS remote sensing technology is proposed to improve natural resources monitoring accuracy in scenic spots. The remote sensing images of scenic spots obtained by MODIS were preprocessed by TM image processing, atmospheric correction, and other technologies to get high-precision remote sensing images. The remote sensing images of scenic spots were segmented by the multi-scale segmentation method, and then the hierarchical supervision classification method was used. The change points of natural resources were extracted. The resource changes and independent variables of scenic spots were analyzed based on the least square method to realize the dynamic monitoring of natural resources in scenic locations. The experimental results show that the technique can accurately monitor the dynamic changes of forest resources and water resources in scenic spots, and the monitoring results have high accuracy.

Con el fin de mejorar la precisión del monitoreo de recursos naturales en lugares escénicos, se propone un algoritmo de monitoreo dinámico de recursos naturales con base en la tecnología de teledetección MODIS. Las imágenes de teledetección de lugares escénicos obtenidas por MODIS fueron preprocesadas con el método de imágenes TM, corrección atmosférica y otras tecnologías para obtener imágenes de teledetección de alta precisión. Las imágenes de teledetección se dividieron mediante el método de segmentación de múltiples escalas y se utilizó el método de clasificación de supervisión jerárquica. Se extrajeron los puntos de cambio de los recursos naturales y se analizaron los cambios de recursos y las variables independientes de los lugares escénicos con base en el método de mínimos cuadrados, para realizar el seguimiento dinámico de los recursos naturales en los lugares escénicos. Los resultados experimentales muestran que el método puede monitorear con precisión los cambios dinámicos de los recursos forestales y los recursos hídricos en lugares escénicos. Los resultados del monitoreo tienen una alta precisión.

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How to Cite

APA

Li, M. . (2021). Dynamic monitoring algorithm of natural resources in scenic spots based on MODIS Remote Sensing technology. Earth Sciences Research Journal, 25(1), 57–64. https://doi.org/10.15446/esrj.v25n1.93869

ACM

[1]
Li, M. 2021. Dynamic monitoring algorithm of natural resources in scenic spots based on MODIS Remote Sensing technology. Earth Sciences Research Journal. 25, 1 (Apr. 2021), 57–64. DOI:https://doi.org/10.15446/esrj.v25n1.93869.

ACS

(1)
Li, M. . Dynamic monitoring algorithm of natural resources in scenic spots based on MODIS Remote Sensing technology. Earth sci. res. j. 2021, 25, 57-64.

ABNT

LI, M. . Dynamic monitoring algorithm of natural resources in scenic spots based on MODIS Remote Sensing technology. Earth Sciences Research Journal, [S. l.], v. 25, n. 1, p. 57–64, 2021. DOI: 10.15446/esrj.v25n1.93869. Disponível em: https://revistas.unal.edu.co/index.php/esrj/article/view/93869. Acesso em: 10 mar. 2025.

Chicago

Li, Maolin. 2021. “Dynamic monitoring algorithm of natural resources in scenic spots based on MODIS Remote Sensing technology”. Earth Sciences Research Journal 25 (1):57-64. https://doi.org/10.15446/esrj.v25n1.93869.

Harvard

Li, M. . (2021) “Dynamic monitoring algorithm of natural resources in scenic spots based on MODIS Remote Sensing technology”, Earth Sciences Research Journal, 25(1), pp. 57–64. doi: 10.15446/esrj.v25n1.93869.

IEEE

[1]
M. . Li, “Dynamic monitoring algorithm of natural resources in scenic spots based on MODIS Remote Sensing technology”, Earth sci. res. j., vol. 25, no. 1, pp. 57–64, Apr. 2021.

MLA

Li, M. . “Dynamic monitoring algorithm of natural resources in scenic spots based on MODIS Remote Sensing technology”. Earth Sciences Research Journal, vol. 25, no. 1, Apr. 2021, pp. 57-64, doi:10.15446/esrj.v25n1.93869.

Turabian

Li, Maolin. “Dynamic monitoring algorithm of natural resources in scenic spots based on MODIS Remote Sensing technology”. Earth Sciences Research Journal 25, no. 1 (April 16, 2021): 57–64. Accessed March 10, 2025. https://revistas.unal.edu.co/index.php/esrj/article/view/93869.

Vancouver

1.
Li M. Dynamic monitoring algorithm of natural resources in scenic spots based on MODIS Remote Sensing technology. Earth sci. res. j. [Internet]. 2021 Apr. 16 [cited 2025 Mar. 10];25(1):57-64. Available from: https://revistas.unal.edu.co/index.php/esrj/article/view/93869

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CrossRef citations3

1. Wei He, Lianfa Li, Xilin Gao. (2024). Geocomplexity Statistical Indicator to Enhance Multiclass Semantic Segmentation of Remotely Sensed Data with Less Sampling Bias. Remote Sensing, 16(11), p.1987. https://doi.org/10.3390/rs16111987.

2. Yansong Luo, Fulong Chen, Sheng Gao, Meng Zhu, Wei Zhou, Abdelaziz Elfadaly. (2024). Archaeological cognition of the Eastern mausoleum of Qin state using integrated space-ground observation tools. Heritage Science, 12(1) https://doi.org/10.1186/s40494-024-01478-w.

3. Lianfa Li, Zhiping Zhu, Chengyi Wang. (2023). Multiscale Entropy-Based Surface Complexity Analysis for Land Cover Image Semantic Segmentation. Remote Sensing, 15(8), p.2192. https://doi.org/10.3390/rs15082192.

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