Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Spatio‐Temporal Analysis of Total Suspended Solids (TSS) in Water Bodies and Mapping Mining Areas in Suriname and French Guiana

Version 1 : Received: 26 May 2024 / Approved: 27 May 2024 / Online: 27 May 2024 (13:22:35 CEST)

How to cite: Pereira, B. M.; Lobo, F. D. L. Spatio‐Temporal Analysis of Total Suspended Solids (TSS) in Water Bodies and Mapping Mining Areas in Suriname and French Guiana. Preprints 2024, 2024051744. https://doi.org/10.20944/preprints202405.1744.v1 Pereira, B. M.; Lobo, F. D. L. Spatio‐Temporal Analysis of Total Suspended Solids (TSS) in Water Bodies and Mapping Mining Areas in Suriname and French Guiana. Preprints 2024, 2024051744. https://doi.org/10.20944/preprints202405.1744.v1

Abstract

Artisanal and Small-scale Gold Mining (ASGM) has caused several environmental impacts, resulting in significant siltation of water bodies due to the deposition of sediments on river banks. Based on this perspective, this study aims to investigate the water bodies and regions most impacted by mining activities, especially in relation to the increase in the Total Suspended Solids (TSS) caused by ASGM, focusing on the territories of Suriname and French Guiana, over the period from 2017 to 2023, through the creation of an algorithm in Google Earth Engine. The research also aims to map and describe active mining in this region using the Classification and Regression Tree (CART) method, which achieved an overall accuracy of 82% and a kappa index of 0.77. The results reveal that from 2017 to 2024 there was an increase of 148.09 km² of mining, with an average increase in TSS of up to 167 mg/l in water bodies most affected by mining activities. Finally, the continued importance of using remote sensing technologies, such as GEE, together with innovative methodological approaches, to monitor and manage natural resources in a sustainable manner is highlighted.

Keywords

mining; total suspended solids; environmental monitoring; remote sensing; google engine; image classification

Subject

Environmental and Earth Sciences, Remote Sensing

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