SPATIALLY AWARE LANDSLIDE SUSCEPTIBILITY PREDICTION USING A GEOGRAPHICAL RANDOM FOREST APPROACH

SPATIALLY AWARE LANDSLIDE SUSCEPTIBILITY PREDICTION USING A GEOGRAPHICAL RANDOM FOREST APPROACH

Landslide susceptibility prediction practices have been increasingly reliant on non-geographically-oriented (i.e., aspatial) machine learning algorithms. While these approaches have exhibited increasing success, they have often faced criticism for their limited consideration of spatial autocorrelati...

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Bibliographic Details
Main Authors:	A. Teke, T. Kavzoglu
Format:	Article
Language:	English
Published:	Copernicus Publications 2024-03-01
Series:	The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:	https://isprs-archives.copernicus.org/articles/XLVIII-4-W9-2024/363/2024/isprs-archives-XLVIII-4-W9-2024-363-2024.pdf

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