Spatial estimation of soil organic carbon, total nitrogen, and soil water storage in reclaimed post-mining site based on remote sensing data

Abstract

The estimation of Soil Organic Carbon (SOC), Total Nitrogen (TN), and Soil Water Storage (SWS) is crucial in comprehending ecosystem services and environmental sustainability. It plays a crucial role in guiding sustainable restoration strategies and supporting the long-term health of post-mining sites. Remote sensing technology provides valuable tools for modelling and mapping soil properties in reclaimed post-mining sites efficiently and cost-effectively. This study aimed to utilize remote sensing data to estimate SOC, TN, and SWS in a reclaimed post-mining site. Field data was collected from 130 research plots to obtain reference data for SOC, TN, and SWS from the Sonica hard coal post-mine spoil heap. Remote sensing data were: airborne laser scanning (ALS) point clouds and Planets cope satellite imageries. Generalized Additive Models (GAM) were used to develop predictive models. Wall-to-wall predictions of analyzed variables were performed. The results identified topographic and remote sensing indicators that significantly influence SOC, TN, and SWS. Digital Terrain Model (DTM), aspect, and blue spectral band are variables that explain SOC storage, with a significant influence of DTM, ranging from −8 to 18 Mg ha−1. TN was explained by DTM, Canopy Height Model (CHM), blue and Near Infrared (NIR) spectral bands, and Normalized Difference Vegetation Index (NDVI), mainly influenced by NIR and NDVI, ranging from −1.1 to 0.8 and −0.9 to 1.4 Mg ha−1, respectively. The values of Topographic Wetness Index (TWI), aspect, CHM, blue and NIR spectral bands explained SWS, highlighting their importance in assessing soil water dynamics in post-mining landscapes, with TWI and CHM being particularly influential, ranging from −2 to 5.1 and −6 to 2 mm, respectively. However, caution is advised when predicting SOC and TN using remote sensing in post-mining sites due to geogenic carbon considerations.

Keywords

• ALS
• Digital terrain model
• Planthopper
• Reclamation
• Spoil heap