Effect of raster resolution and polygon-conversion algorithm on landslide susceptibility mapping. (October 2016)

• Record Type: Journal Article
• Authors: Arnone, E.; Francipane, A.; Scarbaci, A.; Puglisi, C.; Noto, L.V.
• Is Part Of: Environmental modelling & software. Volume 84(2016:Oct.)
• Page Start: 467
• Page End: 481
• Publication Date: 2016-10
• Subjects: Grid-cell size -- Vector-to-raster conversion -- Resampling -- Landslide susceptibility mapping -- Artificial neural network; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2016.07.016
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The choice of the proper resolution in landslide susceptibility mapping is a worth considering issue. If, on the one hand, a coarse spatial resolution may describe the terrain morphologic properties with low accuracy, on the other hand, at very fine resolutions, some of the DEM-derived morphometric factors may hold an excess of details. Moreover, the landslide inventory maps are represented throughout geospatial vector data structure, therefore a conversion procedure vector-to-raster is required. This work investigates the effects of raster resolution on the susceptibility mapping in conjunction with the use of different algorithms of vector-raster conversion. The Artificial Neural Network technique is used to carry out such analyses on two Sicilian basins. Seven resolutions and three conversion algorithms are investigated. Results indicate that the finest resolutions do not lead to the highest model performances, whereas the algorithm of conversion data may significantly affect the ANN training procedure at coarse resolutions. Highlights: Landslide susceptibility maps using ANN. Effects of raster resolution and vector-to-raster conversion algorithms. The finest resolutions do not necessarily lead to the highest model performances. The algorithm of conversion data may significantly affect the ANN training.