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Multitemporal Landslide Inventory and Activity Analysis by Means of Aerial Photogrammetry and LiDAR Techniques in an Area of Southern Spain.

Authors :
Fernández, Tomás
Pérez-García, José L.
Gómez-López, José M.
Cardenal, Javier
Moya, Francisco
Delgado, Jorge
Source :
Remote Sensing. Jun2021, Vol. 13 Issue 11, p2110. 1p.
Publication Year :
2021

Abstract

This paper deals with the use of aerial photogrammetry and LiDAR techniques to analyze landslide activity over a long time span—just over 32 years. The data correspond to several aerial surveys (1984, 1996, 2001, 2005, 2009, 2010, 2011, 2013 and 2016) covering an area of about 50 km2 along highway A-44, near Jaén (Southern Spain). An ad hoc combined photogrammetric and LiDAR aerial survey of 2010 was established as the reference flight. This flight was processed by means of direct orientation methods and iterative adjustments between both data sets. Meanwhile, historical flights available in public geographical data servers were oriented by transferring ground control points from the reference flight. Then, digital surface models (DSMs) and orthophotographs were generated, as well as the corresponding differential models (DoDs), which, after the application of filters and taking into account the estimated uncertainty of ± 1 m, allowed us to identify true changes on the ground surface. This analysis, complemented by photointerpretation, led us to obtain a landslide multitemporal inventory in the study area that was analyzed in order to characterize the landslide type, morphology and activity. Three basic typologies were identified: rock falls–collapses, slides and flows. These types present different morphometric properties (area, perimeter and height interval) and are associated with different conditions (height, slope, orientation and lithology). Moreover, a set of monitoring areas, common for the different flights, was also used to analyze the activity throughout the study period. Thus, some more active periods were identified (2009–2010, 2010–2011, 2011–2013 and 1996–2001) among other less active ones (1984–1996, 2001–2005, 2005–2009 and 2013–2016), which are related to rainy events and dry years, respectively. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
13
Issue :
11
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
150828780
Full Text :
https://doi.org/10.3390/rs13112110