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

• Published in: International journal of remote sensing 2024-08, Vol.45 (16), p.5425-5442
• Main Authors: Chemura, Abel, Lu, Shaoqing, Skidmore, Andrew K., Duporge, Isla, Lee, Stephen J., Yu, Zhaoyang, Ngene, Shadrack, Wang, Tiejun
• Format: Article
• Language: English
• Subjects: African savannas; All terrain vehicles; Feature extraction; Formability; Fuzzy logic; Geographical information systems; High resolution; human impact; Image resolution; Mapping; Off road vehicles; Protected areas; Redundancy; Remote sensing; Roads; Satellite imagery; Shape; tourism; Tracks (paths); wildlife habitat
• ISSN: 0143-1161; 1366-5901
• DOI: 10.1080/01431161.2024.2377230

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