Remote Sensing Monitoring and Evaluation of Vegetation Restoration in Grassland Mining Areas—A Case Study of the Shengli Mining Area in Xilinhot City, China

Abstract

Coal production will cause serious damage to regional vegetation, especially in ecologically fragile grasslands. It is the consensus of all major countries to conduct vegetation restoration and management monitoring in areas damaged by coal production. This paper compares the adaptability of different data sources and different vegetation indices to grassland mining areas and proposes a normalized environmental vegetation index (NEVI) suitable for vegetation monitoring in grassland mining areas. Based on the Landsat and Sentinel data from 2005 to 2019, this paper uses NEVI to monitor the vegetation destruction and restoration of the Shengli mining area. The main result is that the vegetation restoration work in the Shengli mining area started in 2007 and was gradually carried out in subsequent years. The restoration effect of vegetation is significantly better in the east than in the west. The NEVI of the vegetation in the east can reach, or exceed, the level of natural vegetation in the same period. The restoration of vegetation degradation in some areas requires strengthening of management and maintenance measures.

Crop Mapping in the Sanjiang Plain Using an Improved Object-Oriented Method Based on Google Earth Engine and Combined Growth Period Attributes

“…Therefore, we selected May to October as the study period and considered every 10 days as a growth stage; that is, there were a total of 18 growth stages. In addition, aside from the original wavebands, the visible, NIR, and SWIR bands of the Sentinel-2 L2A product were used to calculate [41,42] normalized difference water index (NDWI) [43,44], normalized difference vegetation index (NDVI) [45], modified normalized difference water index (MNDWI) [46], and enhanced water index (EWI) [47], as shown in Figure 2 and Table 3. Among these, NDVI shows favorable sensitivity for monitoring the temporal and spatial variation of vegetation [48], which has been widely used in rice monitoring; NDWI is helpful for dividing the boundary between vegetation and water [44]; MNDWI is easily used to distinguish between shadow and water [46]; and EWI also introduces a nearinfrared band and short-wave infrared band, which can effectively distinguish residents, soil, and water [47].…”

Comparison of EO4Agri Recommendations With In-Depth Literature Review

“…Remote sensing is also a method used to monitor reclamation vegetation in grassland mining areas, as studied by [11] in their review. Due to the large size of the mining areas and the difficulties of transportation, this method is very advantageous.…”

“…Since Sentinel data have the advantages of a short revisit period and high spatial resolution, surface vegetation monitoring based on Sentinel data has become a popular research topic. Many researchers have been interested in it and have developed indices adapted to it [12] proposed an NSSI vegetation index adapted to Sentinel data [11] proposed the NDVI705 vegetation index based on the red band of the Sentinel data and used it to study vegetation recovery after the Cyprus fire, [13] used Sentinel data to compute a variety of vegetation indices and used them to invert the surface salinity)…”

Comparison of the Vegetation Index of Reclamation Mining Areas Calculated by Multi-Source Remote Sensing Data

“…One of the most important steps in reclamation is vegetation restoration. By using effective monitoring techniques within mining areas, vegetation conditions can be reclaimed by enhancing restoration planning and implementation [5,6]. Relying only on traditional ground sampling experiments to monitor vegetation condition requires tremendous manpower and financial resources, which is not realistic.…”

“…Relying only on traditional ground sampling experiments to monitor vegetation condition requires tremendous manpower and financial resources, which is not realistic. Compared with traditional methods, remote sensing monitoring can accomplish large-scale vegetation monitoring and provide effective and timely vegetation information [6][7][8][9][10][11][12][13].…”