Mapping off-road tracks and animal paths in protected areas using high-resolution GeoEye-1 panchromatic satellite imagery

Off-road driving activities are common in many protected areas. This study aimed at applying a curvelet-based approach for the automatic extraction, mapping and separation of off-road tracks and animal paths in Masai Mara National Reserve, Kenya, using high-resolution GeoEye-1 panchromatic satellite imagery (50 cm). A novel hybrid remote sensing-GIS method comprising three main blocks is proposed: (1) extracting the high-contrast curvilinear feature from curvelet magnitudes derived from the finer scale of curvelet coefficient; (2) extracting the low-contrast curvilinear feature from coarser scale curvelets and refine the shape by deformable active contour (Snake), and (3) categorizing the extracted curvilinear feature into vehicle tracks and animal paths by a fuzzy logic inference system. Results from quantification of extraction and categorization performance of the trails were 77.5% for completeness, 89.2% for correctness, and 4.5% for redundancy, with an overall accuracy of 79.5%. Using grid matching, we find a high correlation between off-road vehicle tracks and animal paths in the area (r = 0.75, p < 0.05) indicating co-occurrence of these two types of trails. The proposed approach provides a basis for large-scale mapping and monitoring of off-road tracks and animal paths in the African savanna from space.