Detection of Gully-Affected Areas by Applying Object-Based Image Analysis (OBIA) in the Region of Taroudannt, Morocco
Detection of Gully-Affected Areas by Applying Object-Based Image Analysis (OBIA) in the Region of Taroudannt, Morocco
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DOI：
10.3390/rs6098287
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发表时间：
2014-09
期刊：
影响因子：
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通讯作者：
S. d'Oleire-Oltmanns;I. Marzolff;D. Tiede;T. Blaschke
中科院分区：
文献类型：
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作者：
S. d'Oleire-Oltmanns;I. Marzolff;D. Tiede;T. Blaschke
这项研究的目的是在摩洛哥塔鲁丹特地区应用基于对象的图像分析来检测受冲沟影响的地区，该地区受冲沟侵蚀的影响很大，同时代表着一个对耕地需求很高的主要农工业地区。由于高分辨率光学卫星数据很容易从各种传感器获得，并且具有比3D地形数据好得多的时间分辨率，因此开发了一种仅使用光学卫星图像就能提取受沟壑影响地区的区域制图方法。该方法还将专家知识和免费可用的矢量数据合并到基于对象的循环图像分析方法中。这连接了地貌学和遥感两个领域。分类结果表明，所开发的方法是成功的实施，并允许对当前的沟壑分布作出结论。将分类结果与基于该地区几个实地活动的包含专家知识的人工划定的参考数据进行了核对，结果总体分类准确率为62%。遗漏误差占38%，佣金误差占16%。此外，还进行了人工评估，以评估应用的分类算法的质量。不作为的限度误差占不作为的总体误差的23%，实施的限度误差占犯罪的总体误差的98%。这项评估改进了结果，证实了所开发的在较大区域内绘制受沟壑影响地区的全区地图的高质量方法。在地貌制图领域，分类结果的整体质量往往是用一种以上的方法来评估的，以充分结合所有方面。
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 mapping, the overall quality of the classification results is often assessed with more than one method to incorporate all aspects adequately.