Mapping deactivated mine areas in the amazon forest impacted by seasonal flooding: Assessing soil-hydrological processes and quality dynamics by remote sensing and geophysical techniques

Mining activities significantly impact the environment, calling for environmental restoration efforts. In this study, we quantified and mapped areas affected by seasonal floods by using a combination of geophysical, geotechnological, and digital tools for data acquisition. The objective was to assess the hydrological and pedological processes resulting from changes in water table dynamics. The study was conducted in the Brazilian Amazon Forest within the Jamari National Forest (FLONA), analyzing four mines: Serra da Onca, Santa Maria, Potosi, and 14 de Abril. We employed satellite imagery for acquiring hyperspectral bands in the Vis-NIR-SWIR range, georadar surveys for subsurface analysis, and digital field sensors for monitoring soil moisture, temperature, and fertility. Based on Normalized Difference Water Index (NDWI) and Normalized Difference Moisture Index (NDMI) data, we applied Sentinel-2 images using ESRI ArcGIS 10.4 to quantify flooded areas. Additionally, the soil profiles were examined, temperature and humidity sensors were installed for monitoring purposes, and we determined subsurface water dynamics, alterations in soil attributes, and limitations in soil fertility affecting plant growth in mined areas. The combined use of field data, georadar surveys, and satellite-derived indices is a valid approach to effectively quantify areas affected by seasonal floods and indicated maximum flooding levels across all mines, evidenced by radargrams displaying saturated soil areas at varying depths. Using remote sensing data and indices such as NDVI and NDMI facilitated the identification of areas affected by seasonal flooding. The volumetric water content significantly influenced soil temperature based on moisture levels and depth. Low soil fertility, identified through laboratory analysis and water saturation data, impeded vegetation establishment and development and favored redoximorphic soil processes. The integration of remote (satellite) and proximal (GPR) sensing techniques proved efficient for accurately quantifying changes in soil water dynamics.