NDLI: Application of change detection techniques for monitoring man-induced landslide causal factors

Content Provider	IEEE Xplore Digital Library
Author	Tarantino, C. Blonda, P. Pasquariello, G.
Copyright Year	2004
Description	Author affiliation: Ist. di Studi sui Sistemi Intelligenti per l'Automazione, CNR Consiglio Nazionale delle Ricerche, Bari (Tarantino, C.; Blonda, P.; Pasquariello, G.)
Abstract	Slope instability studies seem to recognize and group a number of potential superficial slide-producing agents which might be directly detected and monitored from Earth Observation (EO) data. The attention of this work is focused on man's activity induced surface changes, such as deforestation, urban expansion, artificial structures construction. An historical set of fourteen multi-temporal optical Landsat TM images have been considered. The main objective of the work is to verify the advantages and limitations of conventional space-borne RS data to provide change maps on areas including unstable slopes. A supervised change detection technique is preferred to an unsupervised technique since the former can provide a change image containing useful information not only on the place were a transition occurred, but also on the specific classes involved in the transitions between two dates. The change image is used to extract class-conditional transition probabilities and evaluate class-specific trends of change. Four classes and their transitions have been considered in the analysis: (1) arboreous land, (2) agricultural land, (3) barren land, (4) artificial structures. The percentage values of the total number of changed pixels for each map pair is also correlated with known landslides events occurred in the considered period. A correlation value of 0.8 is obtained. This paper discusses the results obtained on a test site located in Regione Abruzzo, Southern Italy, affected by slope instability phenomena
Starting Page	1103
Ending Page	1106
File Size	369636
Page Count	4
File Format	PDF
ISBN	0780387422
DOI	10.1109/IGARSS.2004.1368605
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-09-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Monitoring Terrain factors Hazards Earth Satellites Neural networks Geology Remote sensing Data mining Testing
Content Type	Text
Resource Type	Article

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