Identification of successional trajectory over 30 Years and evaluation of reclamation effect in coal waste dumps of surface coal mine

Abstract

The ecological environment of the mining area has always been one of the focuses for its strong disturbance by human activities. The goals of this study were to ascertain the succession trajectory types of revegetation in the surface mining area and evaluate whether the revegetation in 3 coal-waste-dump sites with different reclamation methods were restored to the pre-disturbance status. We proposed an analysis method that combines machine learning method with traditional statistical analysis method by using the multi-temporal Landsat images and surveying data. The results showed that the trajectories of modified soil-adjusted vegetation index (MSAVI2) and normalized difference infrared index (NDII) of the south dump (D3) performed better than that of the north dump (D2) and the west dump (D1), which means the revegetation of D3 had reached or even exceeded its pre-mining level judging by those remote sensing indicators. In terms of bio-diversity, the reclamation effect of D3 had also improved significantly than other 2 dumps, especially in the Caragana microphylla planting area, while the species structure of the revegetation of D3 was also relatively simple and was susceptible to be disturbed. Besides, we also found that the contents of total nitrogen (TN), available potassium (AK) and soil organic matter (SOM) in the waste dumps were still lower than those of undisturbed grassland, at the same time soil properties content raised with the increase of planting density of Caragana microphylla. Study showed the time-series remote sensing trajectory analysis and field investigation analysis were complementary to each other and can reflect the mining influence and reclamation effect in a more comprehensive and effective way, which could be applied to gain further insight concerning ecosystems and other essential environmental features in similar disturbed area.