Assessing vegetation recovery in reclaimed opencast mines of the Teruel coalfield (Spain) using Landsat time series and boosted regression trees.

Sci Total Environ

Institute of Environmental Assessment and Water Research (IDAEA, CSIC), 08034 Barcelona, Spain; Desertification Research Centre (CIDE, CSIC-UV-GV joint centre), 46113, Moncada, Spain. Electronic address:

Published: May 2020

AI Article Synopsis

  • Opencast mining significantly impacts the environment and society, and post-mining land reclamation aims to restore natural vegetation and ecosystem functions.
  • Effective reclamation strategies are necessary, but evaluating their success involves extensive fieldwork, prompting research into a semi-automatic method using satellite data and machine learning to assess vegetation development in reclaimed areas.
  • The study focused on the Teruel coalfield in Spain, identifying critical factors for vegetation growth, such as water availability, soil retention, and proximity to seed sources, while highlighting the adverse effects of drought on reclamation efforts.

Article Abstract

Opencast mining is an activity that caters to many economic sectors; however, it has a large impact on society and the environment. After mining, the major concern is to restore the previous land cover, which was generally a natural vegetation cover. Establishing permanent vegetation cover can restore landscape connectivity and previous ecosystem functions, enhance aesthetic values and prevent off-side effects associated with post-mining landscapes. Opencast mining reclamation deals with these issues with several strategies that aim to develop a vegetation cover after mining activity has stopped. However, not all reclamation actions are effective, and assessing their efficiency by monitoring vegetation development at reclaimed sites is a time-consuming task because it usually involves extensive field work. In this study, we present a semi-automatic approach based on analysing satellite data (Landsat) time series and using a machine learning technique to identify suitable conditions for vegetation development at reclaimed opencast mines. We analysed the Teruel coalfield (Aragón, central-eastern Spain). This area is a representative Mediterranean-Continental region that is of particular interest due the diversity of reclamation actions that have been applied and the increase in drier conditions during the last decades. Conditions were described with topography derived variables, technical reclamation features and drought-occurrence variables as potential explanatory factors. The implemented approach allowed us to identify the main abiotic filters for vegetation of this geographic region: the water availability and soil retention (both controlled by the topographic slope), and the proximity to seed sources. The analysis evidenced the negative influence of drought occurrence on vegetation development, and different responses were found depending on the timescale at which drought is calculated. Our results indicate that the reclamation landform model is the main key factor influencing vegetation development. A model such as the smooth berm-slope increases water availability and controls soil erosion, and hence, improves vegetation development. In addition, we found that further than 500-600 m from the mine, the effect of seed source declines dramatically. Therefore, all these issues should be considered in future reclamation designs in a Mediterranean-Continental environment. Our methodology could be adapted to other geographic regions where spatial environmental data are available.

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Source
http://dx.doi.org/10.1016/j.scitotenv.2020.137250DOI Listing

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