A “Status-Habitat-Potential” Model for the Evaluation of Plant Communities in Underwater Mining Areas via Time Series Remote Sensing Images and GEE

Abstract

Mining activities are the primary human-induced disturbances on plant communities in various ecosystems, and they also are important for implementing strategies of ecological protection and restoration based on them. The effects of underwater mining on plant communities in wetland ecosystems, however, are seldom demonstrated, and it is also difficult to accurately evaluate the state of plant communities’ condition, considering the dynamic and randomness of plant communities under multiple factors, including climate, mining, and other human activities. To address these issues, a “Status-Habitat-Potential” (SHP) model has been developed, with nine indicators from the status, habitat, and potential of plant communities, and the plant communities in the Nansi Lake mining area are evaluated to illustrate the effects of underwater mining. Time series remote sensing images from Sentinel-2 and Google Earth Engine are applied. Comparison analysis, Global Moran’s index, and hot and cold analysis are also used to demonstrate the spatial characteristics of the SHP index. Results show that the SHP index varies between 0 and 0.57 and shows a high aggregation pattern according to the Global Moran’s index (0.41), with high and low values aggregating in the center of the lake and living areas, respectively. The SHP index between subsidence and contrast areas shows no significant difference (at p < 0.05), indicating little effect of mining subsidence on plant communities directly. Overall, underwater mining would not cause as obvious effects on plant communities as underground mining, but human activities accompanied by mining activities will result in the loss of plant communities around lake shores and river channels. This study put forward a new model to evaluate plant communities in terms of their status, habitat, and potential, which could also be used to illustrate other long-term effects of disturbances on plant communities.

Keywords

• underwater mining
• subsidence
• plant evaluation
• time series remote sensing
• Google Earth Engine