Abstract
Spatial information acquisition and analysis tools play a fundamental role to supplying the information necessary to produce landslide inventories, which represent the foundations for quantifying landslide hazard and vulnerability. In this frame, fundamental data are Digital Surface Models (DSMs) and Digital Elevation Models (DEMs).
The goal of this paper is just methodological, focused to illustrate the actual potentialities of DSMs generation from high resolution satellite Synthetic Aperture Radar (SAR) imagery with a radargrammetric stereo-mapping approach. The fundamental advantage of this approach is that it can work with just a couple of images (no matter for their coherence), which can be collected in a short time (half day to quite few days) thanks to the independence of satellite radar acquisition from weather (clouds), daylight and logistic constraints (as for airborne data collection).
The suite for the DSMs generation through the radargrammetric approach has been implemented in SISAR (Software per Immagini Satellitari ad Alta Risoluzione), a scientific software developed at the Geodesy and Geomatic Institute of the University of Rome “La Sapienza”. In order to demonstrate the radargrammetric mapping potentialities of high resolution SAR data, a test site was established in the area of Merano (Northern Italy), characterized by mixed morphology and land cover. The data available for the experiment were a COSMO-SkyMed SpotLight stereo pair and a LiDAR DEM, used as ground truth. An accuracy better than 3 m has been achieved in open areas and the implemented algorithm appears able to generate DSMs both over open and forested areas, where the accuracy is around 4 m.
Therefore, radargrammetric generation of DSMs from high resolution satellite SAR imagery appears a valuable tool to supply topographic information for landslide inventories at different scales.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Borga M, Dalla Fontana G, Da Ros D, Marchi L (1998) Shallow landslide hazard assessment using a physically based model and digital elevation data. Environ Geol 35(2–3):81–88
Brovelli M, Crespi M, Fratarcangeli F, Giannone F, Realini E (2008) Accuracy assessment of high resolution satellite imagery orientation by leave-one-out method. ISPRS J Photogramm Remote Sens 63(4):427–440
Capaldo P, Crespi M, Fratarcangeli F, Nascetti A, Pieralice F (2010) Definition of a radargrammetric model and application with COSMO-SkyMed imagery. In: Proceedings of the 2nd EARSeL Joint SIG Workshop, Ghent (Belgium), 22–24 Sept 2010 (in press)
Capaldo P, Crespi M, Fratarcangeli F, Nascetti A, Pieralice F (2011) High resolution SAR Radargrammetry. A first application with COSMO-SkyMed SpotLight Imagery, IEEE GRSL (in press)
Carrara A, Carratelli EP, Merenda L (1977) Computer-based data bank and statistical analysis of slope instability phenomena. Zeitschrift für Geomorphologie 21:187–222
Carrara A (1983) Multivariate models for landslide hazard evaluation. Math Geol 15(3):403–426
Carrara A, Cardinali M, Guzzetti F, Reichenbach P (1995) GIS-based techniques for mapping landslide hazard. In: Carrara A, Guzzetti F (eds) Geographical information systems in assessing natural hazards. Kluwer, Dordrecht, pp 135–176
Crosetto M, Aragues FP (1999) Radargrammetry and SAR interferometry for DEM generation: validation and data fusion. In: Proceedings of the CEOS SAR workshop, ESA-CNES, Toulouse, 26–29 Oct 1999, 6 pages
Guimarães RF, Montgomery DR, Greenberg HM, Fernandes NF, Trancoso Gomes RA, de Carvalho A, Júnior O (2003) Parameterization of soil properties for a model of topographic controls on shallow landsliding: application to Rio de Janeiro. Eng Geol 69:99–108
Guzzetti F, Carrara A, Cardinali M, Reichenbach P (1999) Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy. Geomorphology 31:181–216
Gritzner ML, Marcus WA, Aspinall R, Custer SG (2001) Assessing landslide potential using GIS, soil wetness modeling and topographic attributes, Payette River, Idaho. Geomorphology 37:149–165
Jacobsen K (2006) Digital surface models of city areas by very high-resolution space imagery. In: Proceedings of the 1st workshop of the EARSeL-SIG Urban Remote Sensing, 02–03 March, Berlin, unpaginated CD-ROM
JTC-1 Joint Technical Committee on Landslides and Engineered Slopes (2008) Guidelines for landslide susceptibility, hazard and risk zoning, for land use planning. Eng Geol 103:85–98
Leberl FW (1990) Radargrammetric image processing. Artech House, Norwood, p 595
Lee S, Chwae U, Min K (2002) Landslide susceptibility mapping by correlation between topography and geological structure: the Janghung area, Korea. Geomorphology 46:149–162
Lee S (2007) Application and verification of fuzzy algebraic operators to landslide susceptibility mapping. Environ Geol 52(4):615–623
Lee S, Pradhan B (2007) Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models. Landslides 4:33–41
Liu E, Liu H, Zhang Y, Guo Z (2009) An improved method of image denoising base on stationary wavelet. In: Proceedings of the IEEE global congress on intelligent systems. Xiamen, China, pp 379–383
Meric S, Fayard F, Pottier E (2009) Radargrammetric SAR image processing. In: Pei-Gee Peter H (ed) Geoscience and remote sensing. Intech, Vienna, pp 421–454
Nascetti A (2009) A stereo image matching strategy based on corner detection and least squares refinement: algorithm implementation in IDL development environment and testing over high resolution satellite imagery. Degree Thesis (unpublished)
Nichol JE, Shaker A, Wong M-S (2006) Application of high-resolution stereo satellite images to detailed landslide hazard assessment. Geomorphology 76:68–75
Park NW, Chi KH (2008) Quantitative assessment of landslide susceptibility using high‐resolution remote sensing data and a generalized additive model. Int J Remote Sens 29(1):247–264
Perko R, Raggam H, Deutscher J, Gutjahr K, Schardt M (2011) Forest assessment using high resolution SAR data in X-Band. Remote Sens 3:792–815
Raggam H, Gutjahr K, Perko R, Schardt M (2010) Assessment of the stereo-radargrammetric mapping potential of terraSAR-X multibeam spotlight data. IEEE Trans Geosci Remote Sens 48(2):971–977
Toutin T, Chenier R (2009) 3D radargrammetric modeling of RADARSAT-2 Ultrafine Mode: preliminary results of the geometric calibration. IEEE Geosci Remote Sens Lett 6(2):282–286
Van Westen CJ, Castellanos E, Kuriakose SL (2008) Spatial data for landslide susceptibility, hazard, and vulnerability assessment. An overview. Eng Geol 102(3–4):112–131
Zhang L, Gruen A (2006) Multi-image matching for DSM generation from IKONOS imagery. ISPRS J Photogramm Remote Sens 60(3):195–211
Acknowledgements
The COSMO-SkyMed stereo pairs were made available by e-Geos S.p.A., Rome (Italy), in the frame of a collaboration agreement; the authors are indebted to e-Geos S.p.A. for this. Moreover the authors thank very much Prof. K. Jacobsen for making available the DEMANAL software.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Capaldo, P., Crespi, M., Fratarcangeli, F., Nascetti, A., Pieralice, F. (2013). Radargrammetric Generation of DEMs from High Resolution Satellite SAR Imagery: A New tool for Landslide Hazard and Vulnerability Assessment. In: Margottini, C., Canuti, P., Sassa, K. (eds) Landslide Science and Practice. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31325-7_55
Download citation
DOI: https://doi.org/10.1007/978-3-642-31325-7_55
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31324-0
Online ISBN: 978-3-642-31325-7
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)