LANDSLIDE EVOLUTION PATTERN REVEALED BY MULTI-TEMPORAL DSMS OBTAINED FROM HISTORICAL AERIAL IMAGES
Abstract. Landslides are a widespread natural hazard that cause damages to people and to the built up environment. Accurate knowledge of landslide distribution is crucial to develop planning strategies, prevention and resilient communities worldwide. One of the most diffuse way of reporting landslides distribution in a territory is by preparing landslide inventory maps. Such a task is mostly accomplished by expert photo-interpretation of historical aerial photographs, which are an invaluable source of information because they portray the landscape when the anthropic pressure was lower than the present day, providing an observation of the landscape closer to the natural conditions. Despite such a common use of aerial photographs, they are poorly exploited to obtain quantitative measures to support landslide mapping activities. In this paper we present a comparison of two photogrammetric approaches to measure elevation changes in a 50-years period for an area densely affected by landslides in Southern Italy. The obtained results allowed to revisit the original expert mapping proving that such a method is a useful tool to support geomorphological mapping and to improve the overall accuracy of landslide inventories.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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LANDSLIDE EVOLUTION PATTERN REVEALED BY MULTI-TEMPORAL DSMS OBTAINED FROM HISTORICAL AERIAL IMAGES ; volume:XLIII-B2-2022 ; year:2022 ; pages:1085-1092 ; extent:8
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; XLIII-B2-2022 (2022), 1085-1092 (gesamt 8)
- Urheber
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Santangelo, M.
Zhang, L.
Rupnik, E.
Deseilligny, M. P.
Cardinali, M.
- DOI
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10.5194/isprs-archives-XLIII-B2-2022-1085-2022
- URN
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urn:nbn:de:101:1-2022060206263950126394
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:34 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Santangelo, M.
- Zhang, L.
- Rupnik, E.
- Deseilligny, M. P.
- Cardinali, M.
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