Abstract
Automatic procedures for landform extraction is a growing research field but extensive quantitative studies of the prediction accuracy of Automatic Landform Classification (ACL) based on a direct comparison with geomorphological maps are rather limited. In this work, we test the accuracy of an algorithm of automatic landform classification on a large sector of the Ionian coast of the southern Italian belt through a quantitative comparison with a detailed geomorphological map. Automatic landform classification was performed by using an algorithm based on the individuation of basic landform classes named geomorphons. Spatial overlay between the main mapped landforms deriving from traditional geomorphological analysis and the automatic landform classification results highlighted a satisfactory percentage of accuracy (higher than 70%) of the geomorphon-based method for the coastal plain area and drainage network. The percentage of accuracy decreased by about 20–30% for marine and fluvial terraces, while the overall accuracy of the ACL map is 69%. Our results suggest that geomorphon-based classification could represent a basic and robust tool to recognize the main geomorphological elements of landscape at a large scale, which can be useful for the advanced steps of geomorphological mapping such as genetic interpretation of landforms and detailed delineation of complex and composite geomorphic elements.
Highlights
Automatic Classification of Landform (ACL) is a growing research field and different algorithms and procedures have been incorporated into GIS software with the aim to provide suitable procedures of automatic or unsupervised landform extraction or classification
The results of automatic classification are generally considered satisfactory, extensive quantitative studies of prediction accuracy of Automatic Landform Classification (ACL) based on a direct comparison with geomorphological maps are rather limited
Several works highlight that extensive quantitative studies of prediction accuracy of ACL based on a direct comparison with geomorphological maps are rather limited
Summary
Automatic Classification of Landform (ACL) is a growing research field and different algorithms and procedures have been incorporated into GIS software with the aim to provide suitable procedures of automatic or unsupervised landform extraction or classification. Several works have taken advantage of automated landform classification for the reconstruction of issues related to the complex relationships between the spatial distribution of landforms and landscape evolution [7,8,9], seismotectonics [10], geoarchaeology [6,11], geodiversity [12], and urban planning [13]. Such studies have demonstrated the usefulness of automatic procedures of landform extraction, traditional geomorphological analysis cannot be disregarded for the accurate preparation of detailed landform maps.
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