Gully mapping using geographic object-based image analysis: A case study at catchment scale in the Brazilian Cerrado

Abstract

Water erosion is one of the main factors of soil degradation, causing several environmental damages. The most severe stage of water erosion culminates in the emergence of gullies, which increases soil loss and sediment production. The Cerrado biome, a global diversity hotspot, has been affected by gullies in many regions of Brazil. This study investigates the use of Geographic Object-Based Image Analysis (GEOBIA) to detect large gullies from RapidEye and SRTM data in anthropized Brazilian Cerrado. For the first time, a two-sided 50% overlap criteria was used to assess gully segmentation by applying Segmentation Evaluation Index (SEI). The results were checked against manually digitized reference data. The results of gully mapping indicated a user's accuracy of 69.78% in area 1 and 90.24% in area 2; a producer's accuracy of 52.10% in area 1 and 55.42% in area 2. The model can be considered robust since it was possible to detect gullies and generate few false positives in a heterogeneous scene, even using medium resolution data. This approach has the potential of application on a regional scale and can provide valuable information for land use management.