Share Email Print

Proceedings Paper

Change detection of man-induced landslide causal factors
Author(s): Cristina Tarantino; Palma N. Blonda; Guido Pasquariello
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

In the framework of the EU project titled: Landslide Early Warning Integrated project (LEWIS) optical RS data have been periodically processed to detect surface features changes which can be correlated with the development of slope instability mechanisms. The attention is focused on man's activity induced surface features changes, such as deforestation and ploughing, which affects slope equilibrium conditions by decreasing the effective slope shear strength and increasing the slope shear stress, respectively. Fourteen optical Landsat TM images (two per year), has been analysed on the Caramanico test site in Regione Abruzzo, Southern Italy. The main objective of the work was to verify the advantages and limitations of conventional space-borne RS data for the prevention of landslide events. The data were analysed by supervised classifier based on neural network techniques. Four classes and their transitions were considered in the analysis. Supervised techniques were preferred to unsupervised techniques because the former can provide useful information not only on the place were a transition occurred, but also on the specific classes involved in the transition between two dates. The results seem to show that in years 1987-2000 the following surface class changes, potentially related to landslide phenomena, occurred: i) a strong decrease of arboreous land in agricultural land and an increase of barren land, mainly in the area interested by landslides events; ii) an increase of artificial structures, mainly stemming from a transformation of cultivated areas.

Paper Details

Date Published: 10 November 2004
PDF: 5 pages
Proc. SPIE 5573, Image and Signal Processing for Remote Sensing X, (10 November 2004); doi: 10.1117/12.565811
Show Author Affiliations
Cristina Tarantino, Istituto di Studi di Sistemi Intelligenti per l'Automazione, CNR (Italy)
Palma N. Blonda, Istituto di Studi di Sistemi Intelligenti per l'Automazione, CNR (Italy)
Guido Pasquariello, Istituto di Studi di Sistemi Intelligenti per l'Automazione, CNR (Italy)

Published in SPIE Proceedings Vol. 5573:
Image and Signal Processing for Remote Sensing X
Lorenzo Bruzzone, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?