Vegetation growth status as an early warning indicator for the spontaneous combustion disaster of coal waste dump after reclamation: An unmanned aerial vehicle remote sensing approach

Abstract

Spontaneous combustion of coal waste dumps is a serious threat to the ecological environment and the safety of mining areas. Even after land reclamation and ecological restoration, such spontaneous combustion activities are still active. Achieving early warning of spontaneous combustion is necessary to protect the reclaimed ecosystem and reduce environmental pollution, but it has not yet been well studied. To this end, this study proposed a spatial analysis method to achieve early warning spontaneous combustion of coal waste dump after reclamation by integrating unmanned aerial vehicle (UAV) and vegetation (Medicago sativa/alfalfa) growth status. The experiment was implemented in two slope areas (Areas I and II) of a coal waste dump after reclamation in Shanxi province, China, which were under threat of spontaneous combustion. Three alfalfa growth parameters, aboveground biomass (AGB), plant water content (PWC), and plant height (PH) of the study area, were estimated from UAV imagery features and used to assess the spontaneous combustion risk. Then, soil deep temperature points (25 cm depth) distributed evenly in the study area were collected to determine the underground temperature situation. It was found that the UAV-derived rededge Chlorophyll index (CIrededge), canopy temperature depression (CTD), and canopy height model (CHM) achieved a better estimation of alfalfa AGB (R² = 0.81, RMSE = 99.2 g/m², and MAE = 74.9 g/m²), PWC (R² = 0.68, RMSE = 3.9%, and MAE = 3.2%), and PH (R² = 0.77, RMSE = 9.79 cm, and MAE = 7.68 cm) of the study area, respectively. We also observed that three alfalfa parameters were highly correlated with the soil deep temperature, but differed in degree (R² = 0.46-0.81). Furthermore, they were consistent with the soil deep temperature in spatial distribution and could reveal the change direction of underground temperature, which will help us to detect those potential spontaneous combustion areas. These results indicated that vegetation is a prior indicator to the changes in underground temperature of coal waste dump. We believed that UAV can be an effective environmental management tool for the initial assessment of spontaneous combustion risk of coal waste dump after reclamation.

Keywords: Coal waste dump; Remote sensing; Spontaneous combustion; Unmanned aerial vehicle; Vegetation growth.