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GIS-based frequency ratio and index of entropy models for landslide susceptibility assessment in the Caspian forest, northern Iran
Jaafari, A.; Najafi, A.; Pourghasemi, H. R.; Rezaeian, J. & Sattarian, A.
Abstract
This study presents a landslide susceptibility
assessment for the Caspian forest using frequency ratio
and index of entropy models within geographical information
system. First, the landslide locations were identified
in the study area from interpretation of aerial
photographs and multiple field surveys. 72 cases (70 %)
out of 103 detected landslides were randomly selected for
modeling, and the remaining 31 (30 %) cases were used
for the model validation. The landslide-conditioning factors,
including slope degree, slope aspect, altitude,
lithology, rainfall, distance to faults, distance to streams,
plan curvature, topographic wetness index, stream power
index, sediment transport index, normalized difference
vegetation index (NDVI), forest plant community, crown
density, and timber volume, were extracted from the
spatial database. Using these factors, landslide susceptibility
and weights of each factor were analyzed by frequency
ratio and index of entropy models. Results showed
that the high and very high susceptibility classes cover
nearly 50 % of the study area. For verification, the
receiver operating characteristic (ROC) curves were
drawn and the areas under the curve (AUC) calculated.
The verification results revealed that the index of entropy
model (AUC = 75.59 %) is slightly better in prediction
than frequency ratio model (AUC = 72.68 %). The
interpretation of the susceptibility map indicated that
NDVI, altitude, and rainfall play major roles in landslide
occurrence and distribution in the study area. The landslide
susceptibility maps produced from this study could
assist planners and engineers for reorganizing and planning
of future road construction and timber harvesting
operations.
Keywords
Forest road construction; Mountainous terrain; Slope stability; Susceptibility modeling
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