Effect of raster resolution and polygon-conversion algorithm on landslide susceptibility mapping

被引:112
作者
Arnone, E. [1 ]
Francipane, A. [1 ]
Scarbaci, A. [2 ]
Puglisi, C. [3 ]
Noto, L. V. [1 ]
机构
[1] Univ Palermo, Dipartimento Ingn Civile, Ambientale, Aerosp,Mat, Palermo, Italy
[2] Hydrolog Serv, Reading, Berks, England
[3] Agenzia Nazl Italiana Nuove Tecnol Energia & Svil, Rome, Italy
关键词
Grid-cell size; Vector-to-raster conversion; Resampling; Landslide susceptibility mapping; Artificial neural network; RAINFALL-TRIGGERED LANDSLIDES; ARTIFICIAL NEURAL-NETWORKS; DEM RESOLUTION; DISTRIBUTED APPROACH; LOGISTIC-REGRESSION; SPATIAL-RESOLUTION; MODEL; SCALE; HAZARD; UNCERTAINTY;
D O I
10.1016/j.envsoft.2016.07.016
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:467 / 481
页数:15
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