{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:13:19Z","timestamp":1760148799040,"version":"build-2065373602"},"reference-count":37,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2023,6,7]],"date-time":"2023-06-07T00:00:00Z","timestamp":1686096000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"SoLoMon project \u201cMonitoraggio a Lungo Termine di Grandi Frane basato su Sistemi Integrati di Sensori e Reti\u201d (Long-term monitoring of large-scale landslides based on integrated systems of sensors and networks)","award":["FESR 2014\u20132020","FESR4008"],"award-info":[{"award-number":["FESR 2014\u20132020","FESR4008"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Large-scale slow-moving deep-seated landslides are complex and potentially highly damaging phenomena. The detection of their dynamics in terms of displacement rate distribution is therefore a key point to achieve a better understanding of their behavior and support risk management. Due to their large dimensions, ranging from 1.5 to almost 4 km2, in situ monitoring is generally integrated using satellite and airborne remote sensing techniques. In the framework of the EFRE-FESR SoLoMon project, three test-sites located in the Autonomous Province of Bolzano (Italy) were selected for testing the possibility of retrieving significant slope displacement data from the analysis of multi-temporal airborne optic and light detection and ranging (LiDAR) surveys with digital image correlation (DIC) algorithms such as normalized cross-correlation (NCC) and phase correlation (PC). The test-sites were selected for a number of reasons: they are relevant in terms of hazard and risk; they are representative of different type of slope movements (earth-slides, deep seated gravitational slope Deformation and rockslides), and different rates of displacement (from few cm\/years to some m\/years); and they have been mapped and monitored with ground-based systems for many years (DIC results can be validated both qualitatively and quantitatively). Specifically, NCC and PC algorithms were applied to high-resolution (5 to 25 cm\/px) airborne optic and LiDAR-derived datasets (such as hillshade and slope maps computed from digital terrain models) acquired during the 2019\u20132021 period. Qualitative and quantitative validation was performed based on periodic GNSS surveys as well as on manual homologous point tracking. The displacement maps highlight that both DIC algorithms succeed in identifying and quantifying slope movements of multi-pixel magnitude in non-densely vegetated areas, while they struggle to quantify displacement patterns in areas characterized by movements of sub-pixel magnitude, especially if densely vegetated. Nonetheless, in all three landslides, they proved to be able to differentiate stable and active parts at the slope scale, thus representing a useful integration of punctual ground-based monitoring systems.<\/jats:p>","DOI":"10.3390\/rs15122971","type":"journal-article","created":{"date-parts":[[2023,6,8]],"date-time":"2023-06-08T02:02:28Z","timestamp":1686189748000},"page":"2971","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Detecting Recent Dynamics in Large-Scale Landslides via the Digital Image Correlation of Airborne Optic and LiDAR Datasets: Test Sites in South Tyrol (Italy)"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-4511-1448","authenticated-orcid":false,"given":"Melissa","family":"Tondo","sequence":"first","affiliation":[{"name":"Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via Giuseppe Campi, 103, 41125 Modena, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4682-9047","authenticated-orcid":false,"given":"Marco","family":"Mulas","sequence":"additional","affiliation":[{"name":"Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via Giuseppe Campi, 103, 41125 Modena, Italy"}]},{"given":"Giuseppe","family":"Ciccarese","sequence":"additional","affiliation":[{"name":"Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via Giuseppe Campi, 103, 41125 Modena, Italy"}]},{"given":"Gianluca","family":"Marcato","sequence":"additional","affiliation":[{"name":"Research Institute for Geo-Hydrological Protection (IRPI), National Research Council (CNR), Corso Stati Uniti, 4, 35127 Padova, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1486-403X","authenticated-orcid":false,"given":"Giulia","family":"Bossi","sequence":"additional","affiliation":[{"name":"Research Institute for Geo-Hydrological Protection (IRPI), National Research Council (CNR), Corso Stati Uniti, 4, 35127 Padova, Italy"}]},{"given":"David","family":"Tonidandel","sequence":"additional","affiliation":[{"name":"Office for Geology and Building Materials Testing, Autonomous Province of Bolzano, Via Val d\u2019Ega, 48, 39053 Cardano, Italy"}]},{"given":"Volkmar","family":"Mair","sequence":"additional","affiliation":[{"name":"Office for Geology and Building Materials Testing, Autonomous Province of Bolzano, Via Val d\u2019Ega, 48, 39053 Cardano, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3718-7748","authenticated-orcid":false,"given":"Alessandro","family":"Corsini","sequence":"additional","affiliation":[{"name":"Department of Chemical and Geological Sciences, University of Modena and Reggio Emilia, Via Giuseppe Campi, 103, 41125 Modena, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Highland, L.M., and Bobrowsky, P. (2008). The Landslide Handbook\u2014A Guide to Understanding Landslides.","DOI":"10.3133\/cir1325"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.rse.2016.11.007","article-title":"Correlation of Satellite Image Time\u2014Series for the Detection and Monitoring of Slow-Moving Landslides","volume":"189","author":"Stumpf","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.earscirev.2016.08.011","article-title":"Landslides in a Changing Climate","volume":"162","author":"Gariano","year":"2016","journal-title":"Earth Sci. Rev."},{"key":"ref_4","first-page":"103089","article-title":"Cloud-Based Interactive Susceptibility Modeling of Gully Erosion in Google Earth Engine","volume":"115","author":"Titti","year":"2022","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/B978-0-12-374739-6.00367-5","article-title":"Landslide Hazards and Climate Change in High Mountains","volume":"13","author":"Huggel","year":"2013","journal-title":"Treatise Geomorphol."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Mulas, M., Ciccarese, G., Truffelli, G., and Corsini, A. (2020). Displacements of an Active Moderately Rapid Landslide\u2014A Dataset Retrieved by Continuous GNSS Arrays. Data, 5.","DOI":"10.3390\/data5030071"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1016\/j.cageo.2013.10.015","article-title":"A Web-Based Platform for Automatic and Continuous Landslide Monitoring: The Rotolon (Eastern Italian Alps) Case Study","volume":"63","author":"Frigerio","year":"2014","journal-title":"Comput. Geosci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1016\/j.rse.2010.08.012","article-title":"Sub-Pixel Precision Image Matching for Measuring Surface Displacements on Mass Movements Using Normalized Cross-Correlation","volume":"115","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Mulas, M., Ciccarese, G., Truffelli, G., and Corsini, A. (2020). Integration of Digital Image Correlation of Sentinel-2 Data and Continuous GNSS for Long-Term Slope Movements Monitoring in Moderately Rapid Landslides. Remote Sens., 12.","DOI":"10.3390\/rs12162605"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"12265","DOI":"10.3390\/rs70912265","article-title":"Characteristics of Surface Deformation Detected by X-Band SAR Interferometry over Sichuan-Tibet Grid Connection Project Area, China","volume":"7","author":"Meng","year":"2015","journal-title":"Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.optlaseng.2014.04.002","article-title":"Digital Image Correlation in Experimental Mechanics and Image Registration in Computer Vision: Similarities, Differences and Complements","volume":"65","author":"Wang","year":"2015","journal-title":"Opt. Lasers Eng."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"841","DOI":"10.1016\/j.optlaseng.2011.02.023","article-title":"A Fast Digital Image Correlation Method for Deformation Measurement","volume":"49","author":"Pan","year":"2011","journal-title":"Opt. Lasers Eng."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"400","DOI":"10.3788\/AOS20092902.0400","article-title":"Large-Deformation Measurement Based on Reliable Initial Guess in Digital Image Correlation Method","volume":"29","author":"Pan","year":"2009","journal-title":"Acta Optica Sinica"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"640","DOI":"10.1002\/esp.3351","article-title":"Kinematics of Active Earthflows Revealed by Digital Image Correlation and DEM Subtraction Techniques Applied to Multi-Temporal LiDAR Data","volume":"38","author":"Daehne","year":"2013","journal-title":"Earth Surf. Process. Landf."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"102929","DOI":"10.1016\/j.earscirev.2019.102929","article-title":"Airborne Lidar Change Detection: An Overview of Earth Sciences Applications","volume":"198","author":"Okyay","year":"2019","journal-title":"Earth Sci. Rev."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Bickel, V.T., Manconi, A., and Amann, F. (2018). Quantitative Assessment of Digital Image Correlation Methods to Detect and Monitor Surface Displacements of Large Slope Instabilities. Remote Sens., 10.","DOI":"10.3390\/rs10060865"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Caporossi, P., Mazzanti, P., and Bozzano, F. (2018). Digital Image Correlation (DIC) Analysis of the 3 December 2013 Montescaglioso Landslide (Basilicata, Southern Italy): Results from a Multi-Dataset Investigation. Can. Hist. Rev., 7.","DOI":"10.3390\/ijgi7090372"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.geomorph.2004.09.012","article-title":"Field Monitoring of the Corvara Landslide (Dolomites, Italy) and Its Relevance for Hazard Assessment","volume":"66","author":"Corsini","year":"2005","journal-title":"Geomorphology"},{"key":"ref_19","unstructured":"Thiebes, B., Tomellari, E., Mejia-Aguilar, M., Rabanser, M., Schl\u00f6gel, R., Mulas, M., and Corsini, A. (2018). Landslides and Engineered Slopes. Experience, Theory and Practice, CRC Press."},{"key":"ref_20","first-page":"127","article-title":"Holocene Slope Dynamics in the Area of Corvara in Badia (Dolomites, Italy): Chronology and Paleoclimatic Significance of Some Landslides","volume":"24","author":"Corsini","year":"2001","journal-title":"Geogr. Fis. Dinam. Quat."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Schl\u00f6gel, R., Thiebes, B., Mulas, M., Cuozzo, G., Notarnicola, C., Schneiderbauer, S., Crespi, M., Mazzoni, A., Mair, V., and Corsini, A. (2017). Multi-Temporal x-Band Radar Interferometry Using Corner Reflectors: Application and Validation at the Corvara Landslide (Dolomites, Italy). Remote Sens., 9.","DOI":"10.3390\/rs9070739"},{"key":"ref_22","first-page":"1353","article-title":"Overview of 2001\u201308 GPS Monitoring at the Corvara Landslide and Perspectives from 2010\u201311 Use of HR X-Band SAR (Dolomites, Italy)","volume":"Volume 2","author":"Eberhardt","year":"2012","journal-title":"Landslides and Engineered Slopes: Protecting Society through Improved Understanding"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1007\/s10346-014-0498-5","article-title":"Geomechanical Assessment of the Corvara Earthflow through Numerical Modelling and Inverse Analysis","volume":"12","author":"Borgatti","year":"2015","journal-title":"Landslides"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"827","DOI":"10.5194\/isprsarchives-XL-7-W3-827-2015","article-title":"Long-Term Monitoring of a Deep-Seated, Slow-Moving Landslide by Mean of C-Band and X-Band Advanced Interferometric Products: The Corvara in Badia Case Study (Dolomites, Italy)","volume":"40","author":"Mulas","year":"2015","journal-title":"Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Iasio, C., Novali, F., Corsini, A., Mulas, M., Branzanti, M., Benedetti, E., Giannico, C., Tamburini, A., and Mair, V. (2012, January 22\u201327). COSMO SkyMed High Frequency\u2014High Resolution Monitoring of an Alpine Slow Landslide, Corvara in Badia, Northern Italy. Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany.","DOI":"10.1109\/IGARSS.2012.6351908"},{"key":"ref_26","unstructured":"Mulas, M., Corsini, A., Cuozzo, G., Callegari, M., Thiebes, B., and Mair, V. (2016). Landslides and Engineered Slopes. Experience, Theory and Practice, CRC Press."},{"key":"ref_27","unstructured":"Bossi, G., Mair, V., Mantovani, M., Marcato, G., N\u00f6ssing, L., Pasuto, A., and Stefani, M. (2012, January 3\u20138). The Ganderberg Landslide (South Tyrol, Italy): Residual Hazard Assessment and Risk Scenarios. Proceedings of the 11th International and 2nd North American Symposium on Landslide and Engineered Slopes, Banff, Canada."},{"key":"ref_28","first-page":"221","article-title":"Hazard Assessment of a Potential Rock Avalanche in South Tyrol, Italy: 3D Modeling and Risk Scenarios","volume":"2013","author":"Bossi","year":"2013","journal-title":"Ital. J. Eng. Geol. Environ."},{"key":"ref_29","first-page":"240","article-title":"Forward Simulation and Sensitivity Analysis of Run-out Scenarios Using MassMov2D at the Trafoi Rockslide (South Tyrol, Italy)","volume":"7","author":"Iannacone","year":"2013","journal-title":"Georisk"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"739","DOI":"10.1007\/978-3-642-31319-6_94","article-title":"Hot Spots for Simplified Risk Scenarios of the Trafoi Rockslide (South Tyrol)","volume":"Volume 6","author":"Corsini","year":"2013","journal-title":"Proceedings of the Landslide Science and Practice: Risk Assessment, Management and Mitigation\u20142nd World Landslide Forum, WLF 2011"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/j.rse.2011.11.024","article-title":"Evaluation of Existing Image Matching Methods for Deriving Glacier Surface Displacements Globally from Optical Satellite Imagery","volume":"118","author":"Heid","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"4062","DOI":"10.1109\/JSTARS.2019.2937690","article-title":"Image Registration with Fourier-Based Image Correlation: A Comprehensive Review of Developments and Applications","volume":"12","author":"Tong","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Brunetti, A., Gaeta, M., and Mazzanti, P. (2022, January 17\u201322). Multi-Frequency and Multi-Resolution EO Images for Smart Asset Management. Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS), Kuala Lumpur, Malaysia.","DOI":"10.1109\/IGARSS46834.2022.9883325"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Hermle, D., Gaeta, M., Keuschnig, M., Mazzanti, P., and Krautblatter, M. (2021, January 19\u201330). Multi-Temporal Analysis of Optical Remote Sensing for Time-Series Displacement of Gravitational Mass Movements, Sattelkar, Obersulzbach Valley, Austria. Proceedings of the 23rd EGU General Assembly, online.","DOI":"10.5194\/egusphere-egu21-8011"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Mazza, D., Cosentino, A., Romeo, S., Mazzanti, P., Guadagno, F.M., and Revellino, P. (2023). Remote Sensing Monitoring of the Pietrafitta Earth Flows in Southern Italy: An Integrated Approach Based on Multi-Sensor Data. Remote Sens., 15.","DOI":"10.3390\/rs15041138"},{"key":"ref_36","unstructured":"R Core Team (2022). R: A Language and Environment for Statistical Computing 2022, R Foundation for Statistical Computing."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Mazzanti, P., Caporossi, P., and Muzi, R. (2020). Sliding Time Master Digital Image Correlation Analyses of Cubesat Images for Landslide Monitoring: The Rattlesnake Hills Landslide (USA). Remote Sens., 12.","DOI":"10.3390\/rs12040592"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/12\/2971\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:50:07Z","timestamp":1760125807000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/12\/2971"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,7]]},"references-count":37,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2023,6]]}},"alternative-id":["rs15122971"],"URL":"https:\/\/doi.org\/10.3390\/rs15122971","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2023,6,7]]}}}