Detection of Gully-Affected Areas by Applying Object-Based Image Analysis (OBIA) in the Region of Taroudannt, Morocco

Abstract

This study aims at the detection of gully-affected areas by applying object-based image analysis in the region of Taroudannt, Morocco, which is highly affected by gully erosion while simultaneously representing a major region of agro-industry with a high demand of arable land. As high-resolution optical satellite data are readily available from various sensors and with a much better temporal resolution than 3D terrain data, an area-wide mapping approach to extract gully-affected areas using only optical satellite imagery was developed. The methodology additionally incorporates expert knowledge and freely-available vector data in a cyclic object-based image analysis approach. This connects the two fields of geomorphology and remote sensing. The classification results show the successful implementation of the developed approach and allow conclusions on the current distribution of gullies. The results of the classification were checked against manually delineated reference data incorporating expert knowledge based on several field campaigns in the area, resulting in an overall classification accuracy of 62%. The error of omission accounts for 38% and the error of commission for 16%, respectively. Additionally, a manual assessment was carried out to assess the quality of the applied classification algorithm. The limited error of omission contributes with 23% to the overall error of omission and the limited error of commission contributes with 98% to the overall error of commission. This assessment improves the results and confirms the high quality of the developed approach for area-wide mapping of gully-affected areas in larger regions. In the field of landform Remote Sens. 2014, 6 8288 mapping, the overall quality of the classification results is often assessed with more than one method to incorporate all aspects adequately.

Detection of Catchment-Scale Gully-Affected Areas Using Unmanned Aerial Vehicle (UAV) on the Chinese Loess Plateau

“…This study mainly aims to detect gully-affected area, which can be regarded as a specific type of landform [84]. Some studies focused on extracting specific types of gullies [85].…”

Gully Erosion Mapping and Monitoring at Multiple Scales Based on Multi-Source Remote Sensing Data of the Sancha River Catchment, Northeast China

“…Since the incident angle of sunlight varies relatively from the landform surface, shadow cast is visible in high resolution optical satellite images for most gullies. The shadow of the Sun-diverted gully walls presents a spectral contrast between the surroundings and the sunlit opposite gully walls [43]. For example, Gully-2 is more discernible than Gully-1 due to the shadowing.…”

“…However, achieving the satisfactory result was time consuming and required a certain expertise. According to previous studies, with respect to high spatial resolution satellite images (such as Pleiades-1A), although the visual interpretation of gully erosion with field verification achieved much higher accuracies [8,46], (semi-)automatic mapping of gullies at a regional scale or larger scales showed great potential for obtaining a general statement of the distribution of gullies to a wider extent [43,47,48].…”

Integrated Use of GCM, RS, and GIS for the Assessment of Hillslope and Gully Erosion in the Mushi River Sub-Catchment, Northeast China

“…Application of remote sensing to extract the gully volume should be given further consideration. With respect to high spatial resolution satellite images (Pleiades-1A), although the visual interpretation method with field verification obtained satisfactory results in mapping gullies, (semi-)automatic mapping of gullies at a regional scale will be a future research direction [53,80,81].…”