An assessment on the use of Terra ASTER L3A data in landslide susceptibility mapping


NEFESLİOĞLU H. A., San B. T., GÖKÇEOĞLU C., Duman T. Y.

INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, vol.14, no.1, pp.40-60, 2012 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 14 Issue: 1
  • Publication Date: 2012
  • Doi Number: 10.1016/j.jag.2011.08.005
  • Journal Name: INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.40-60
  • Keywords: Terra ASTER L3A data, DEM, Topographic attributes, Landslide susceptibility, Kelemen catchment area (Western Black Sea region Turkey), 3 GORGES AREA, SPACEBORNE THERMAL EMISSION, REFLECTION RADIOMETER ASTER, ARTIFICIAL NEURAL-NETWORKS, BLACK-SEA REGION, LOGISTIC-REGRESSION, HAZARD ASSESSMENT, DEMPSTER-SHAFER, HEAVY RAINFALL, NW TURKEY
  • Akdeniz University Affiliated: Yes

Abstract

The main purpose of the present study is to evaluate the potential use of Terra ASTER data-the L3A DEM and its derivatives in landslide susceptibility mapping. For the purpose, an appropriate application site from the Western Black Sea region of Turkey-the Kelemen catchment area was selected. During the analyses, a two-stage comparative evaluation was carried out. In the first stage, the differences between the DEMs obtained from Terra ASTER L3A data and the conventional topographic data; and their first and second derivatives were investigated. Subsequently, different susceptibility maps were produced by using the DEMs and the topographic attributes obtained from both source of data in addition to the spectral information acquired from satellite sensor. According to the results of the comparative evaluations, a strong correlation between Terra ASTER L3A DEM and the conventional topographic data was obtained. However, depending on the increment of the degree of the derivative, an evident decrease in the spatial correlations was observed. On the contrary, the final model performance, prediction capacity, and the spatial performance statistics for the landslide susceptibility maps produced by using both source of data were found as very high and close to each other. (C) 2011 Elsevier B.V. All rights reserved.