Object-based gully feature extraction using high spatial resolution imagery

Gully erosion is responsible for a substantial amount of soil loss and is generally considered an indicator of desertification. Hence, mapping these gully features provides essential information needed on sediment production, identification of vulnerable areas for gully formation, land degradation, and environmental and socio-economical effects. This paper investigates the use of object-oriented image analysis (OOA) to extract gully erosion features from satellite imagery, using a combination of topographic, spectral, shape (geometric) and contextual information obtained from IKONOS and GEOEYE-1 data. A rule-set was developed and tested for a semi-arid to sub-humid region in Morocco. The percentage of gully system area indicated negligible overestimations between the reference area and the OOA area in two sub-watersheds (0.03% and 1.77%). We also observed that finer gully-related edges within the complex gully systems were better identified semi-automatically than was possible by manual digitization, suggesting higher detection accuracy. OOA-based gully mapping is quicker and more objective than traditional methods, and is thus better suited to provide essential information for land managers to support their decision making processes, and for the erosion research community.

► OOA could be used to map gullies semi-automatically.
► Gully systems better identified semi-automatically than manual digitization.
► This method is robust and knowledge driven.
► The method is generic and the test for its transferability was also successful.
► It is a step forward and clearly shows advancement from the existing methods.