Monitoring Vegetation Cover in mining areas in the municipality of Ipixuna do Pará (PA)

Abstract. This study focuses on analyzing the spatiotemporal dynamics of mining areas in the municipality of Ipixuna do Pará, using Planet satellite images and the Google Earth Engine (GEE) platform to monitor vegetation cover during the periods of 2016, 2018, 2021, and 2023. Data obtained through remote sensing enabled the generation of products on the Earth's surface, allowing for a detailed analysis of land use and cover changes. Using the Minimum Distance - Euclidean (MMD) algorithm in GEE, it was possible to classify and quantify the delimited areas, creating temporal maps. The analysis revealed a significant decrease in vegetation area from 2016 (41.8%) to 2018 (38.1%), with a substantial increase in 2021 (74.6%) and stability in 2023 (74.8%). The area dedicated to agriculture remained stable from 2016 (54.3%) to 2018 (55.5%) but drastically reduced in 2021 (22.0%) and 2023 (21.9%). Mining areas showed variations with an increase in infrastructure in 2021 and a consistent reduction in exposed soil areas from 2016 to 2023. The analysis emphasizes the importance of continuous monitoring and effective environmental policies to mitigate the negative impacts of mining. The results indicate that using tools like GEE is crucial for understanding land use changes and implementing environmental management strategies.

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Publication Details

Journal
˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
Published
2024-11-07
DOI
https://doi.org/10.5194/isprs-archives-xlviii-3-2024-115-2024
Primary Topic
Geography and Environmental Studies
Type
article
Field-Weighted Citation Impact
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article

Monitoring Vegetation Cover in mining areas in the municipality of Ipixuna do Pará (PA)

Norma Ely Santos Beltrão, Ilale Ferreira Lima, Simônica Maria de Oliveira, Fernanda Ferreira Machado
˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
Geography and Environmental Studies
article

Monitoring Vegetation Cover in mining areas in the municipality of Ipixuna do Pará (PA)

Norma Ely Santos Beltrão, Ilale Ferreira Lima, Simônica Maria de Oliveira, Fernanda Ferreira Machado
article en

Abstract

Abstract. This study focuses on analyzing the spatiotemporal dynamics of mining areas in the municipality of Ipixuna do Pará, using Planet satellite images and the Google Earth Engine (GEE) platform to monitor vegetation cover during the periods of 2016, 2018, 2021, and 2023. Data obtained through remote sensing enabled the generation of products on the Earth's surface, allowing for a detailed analysis of land use and cover changes. Using the Minimum Distance - Euclidean (MMD) algorithm in GEE, it was possible to classify and quantify the delimited areas, creating temporal maps. The analysis revealed a significant decrease in vegetation area from 2016 (41.8%) to 2018 (38.1%), with a substantial increase in 2021 (74.6%) and stability in 2023 (74.8%). The area dedicated to agriculture remained stable from 2016 (54.3%) to 2018 (55.5%) but drastically reduced in 2021 (22.0%) and 2023 (21.9%). Mining areas showed variations with an increase in infrastructure in 2021 and a consistent reduction in exposed soil areas from 2016 to 2023. The analysis emphasizes the importance of continuous monitoring and effective environmental policies to mitigate the negative impacts of mining. The results indicate that using tools like GEE is crucial for understanding land use changes and implementing environmental management strategies.

˜The œinternational archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciencesVol. XLVIII-3-2024
Universidade do Estado do Pará (BR)
Life in Land
Openalex Percentile: Top 81%
Geography and Environmental Studies
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