Assessment of a semi-automatic spatial analysis method to identify and map sinkholes in the Carste Lagoa Santa environmental protection unit, Brazil

Abstract

Satellite imaging combined with geoprocessing routines is a promising alternative to establish a viable mapping model of specific landscape features and soil use, with high precision, fast results, and low operational costs. The present study examines the employment of a digital elevation model (DEM) combined with geoprocessing techniques for identifying closed depressions in karst landscapes with the objective of mapping potential sinkholes and uvalas within the limits of the Carste Lagoa Santa Environmental Protection Unit, located in the state of Minas Gerais, Brazil. The proposed method consists of using geoprocessing routines combined with DEMs, topographic analysis, individual points of elevation, and mathematical operations between rasters. To accomplish that, SRTM (Shuttle Radar Topographic Mission) data/images were used to extract contour lines and individual elevation points to identify depressions, delimit their edges, and obtain morphometric data referring to the area, perimeter, and their circularity index. The results were satisfactory, allowing the detection of 1076 depressions within the study area. The results were also analyzed for special morphological cases and circularity patterns and compared with a previous study. Field campaigns allowed the partial validation of the method, which proved to be a viable alternative for preliminary and extensive scale mapping of these important karst recharge features.