Articles | Volume 18, issue 1
https://doi.org/10.5194/nhess-18-405-2018
https://doi.org/10.5194/nhess-18-405-2018
Research article
 | 
30 Jan 2018
Research article |  | 30 Jan 2018

Criteria for the optimal selection of remote sensing optical images to map event landslides

Federica Fiorucci, Daniele Giordan, Michele Santangelo, Furio Dutto, Mauro Rossi, and Fausto Guzzetti

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Allasia, P., Manconi, A., Giordan, D., Baldo, M., and Lollino, G.: ADVICE: a new approach for near-real-time monitoring of surface displacements in landslide hazard scenarios, Sensors, 13, 8285–8302, https://doi.org/10.3390/s130708285, 2013. 
Antonini, G., Ardizzone, F., Cardinali, M., Galli, M., Guzzetti, F., and Reichenbach, P.: Surface deposits and landslide inventory map of the area affected by the 1997 Umbria-Marche earthquakes, Boll. Soc. Geol. Ital., 121, 843–853, 2002. 
Ardizzone, F., Cardinali, M., Carrara, A., Guzzetti, F., and Reichenbach, P.: Impact of mapping errors on the reliability of landslide hazard maps, Nat. Hazards Earth Syst. Sci., 2, 3–14, https://doi.org/10.5194/nhess-2-3-2002, 2002. 
Ardizzone, F., Cardinali, M., Galli, M., Guzzetti, F., and Reichenbach, P.: Identification and mapping of recent rainfall-induced landslides using elevation data collected by airborne Lidar, Nat. Hazards Earth Syst. Sci., 7, 637–650, https://doi.org/10.5194/nhess-7-637-2007, 2007. 
Ardizzone, F., Fiorucci, F., Santangelo, M., Cardinali, M., Mondini, A.C., Rossi, M., Reichenbach, P., and Guzzetti, F.: Very-high resolution stereoscopic satellite images for landslide mapping, edited by: Margottini, C., Canuti, P., and Sassa, K., Landslide Science and Practice, Landslide Inventory and Susceptibility and Hazard Zoning, 1, Springer, Heidelberg, Berlin, New York, 95–101, https://doi.org/10.1007/978-3-642-31325-7_12, 2013. 
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Short summary
This paper describes the criteria for the optimal selection of remote sensing images to map event landslides, discussing the ability of monoscopic and stereoscopic VHR satellite images and ultra-high-resolution UAV images to resolve the landslide photographical and morphological signatures. The findings can be useful to decide on the optimal imagery and technique to be used when planning the production of a landslide inventory map.
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