{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T06:20:10Z","timestamp":1762410010002,"version":"build-2065373602"},"reference-count":52,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,4,13]],"date-time":"2022-04-13T00:00:00Z","timestamp":1649808000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The need for widespread structural safety checks represents a stimulus for the research of advanced techniques for structural monitoring at the scale of single constructions or wide areas. In this work, a strategy to preliminarily identify and rank possible critical constructions in a built environment is presented, based on the joint exploitation of satellite radar remote sensing measurements and artificial intelligence (AI) techniques. The satellite measurements are represented by the displacement time series obtained through the Differential Synthetic Aperture Radar Interferometry (DInSAR) technique known as full resolution Small BAseline Subset (SBAS) approach, while the exploited AI technique is represented by the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) methodology. The DBSCAN technique is applied to the SBAS-DInSAR products relevant to the achieved Persistent Scatterers (PSs), to identify clusters of pixels corresponding to buildings within the investigated area. The analysis of the deformation evolution of each building cluster is performed in terms of velocity rates and statistics on the DInSAR measurements. Synthetic deformation maps of the areas are then retrieved to identify critical buildings. The proposed methodology is applied to three areas within the city of Rome (Italy), imaged by the COSMO-SkyMed SAR satellite constellation from ascending and descending orbits (in the time interval 2011\u20132019). Starting from the DInSAR measurements, the DBSCAN algorithm provides the automatic clustering of buildings within the three selected areas. Exploiting the derived deformation maps of each study area, a preliminary identification and ranking of critical buildings is achieved, thus confirming the validity of the proposed approach.<\/jats:p>","DOI":"10.3390\/rs14081872","type":"journal-article","created":{"date-parts":[[2022,4,13]],"date-time":"2022-04-13T23:07:16Z","timestamp":1649891236000},"page":"1872","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["On the Joint Exploitation of Satellite DInSAR Measurements and DBSCAN-Based Techniques for Preliminary Identification and Ranking of Critical Constructions in a Built Environment"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7304-0391","authenticated-orcid":false,"given":"Annalisa","family":"Mele","sequence":"first","affiliation":[{"name":"Department of Structures for Engineering and Architecture, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Autilia","family":"Vitiello","sequence":"additional","affiliation":[{"name":"Department of Physics \u201cEttore Pancini\u201d, University of Naples Federico II, Via Cinthia 21, 80126 Naples, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8240-7629","authenticated-orcid":false,"given":"Manuela","family":"Bonano","sequence":"additional","affiliation":[{"name":"Italian National Research Council, Institute for Electromagnetic Sensing of the Environment (CNR IREA), Via Diocleziano 328, 80124 Naples, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6638-1983","authenticated-orcid":false,"given":"Andrea","family":"Miano","sequence":"additional","affiliation":[{"name":"Department of Structures for Engineering and Architecture, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7296-2749","authenticated-orcid":false,"given":"Riccardo","family":"Lanari","sequence":"additional","affiliation":[{"name":"Italian National Research Council, Institute for Electromagnetic Sensing of the Environment (CNR IREA), Via Diocleziano 328, 80124 Naples, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4082-5616","authenticated-orcid":false,"given":"Giovanni","family":"Acampora","sequence":"additional","affiliation":[{"name":"Department of Physics \u201cEttore Pancini\u201d, University of Naples Federico II, Via Cinthia 21, 80126 Naples, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrea","family":"Prota","sequence":"additional","affiliation":[{"name":"Department of Structures for Engineering and Architecture, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1469","DOI":"10.1080\/15732479.2013.833949","article-title":"An application of the SBAS-DInSAR technique for the assessment of structural damage in the city of Rome","volume":"10","author":"Arangio","year":"2014","journal-title":"Struct. Infrastruct. Eng."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1429","DOI":"10.1007\/s13349-021-00518-4","article-title":"On the integration of multi-temporal synthetic aperture radar interferometry products and historical surveys data for buildings structural monitoring","volume":"11","author":"Miano","year":"2021","journal-title":"J. Civ. Struct. Health Monit."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"470","DOI":"10.1016\/j.proeng.2016.08.474","article-title":"Use of DInSAR data for multi-level vulnerability assessment of urban settings affected by slow-moving and intermittent landslides","volume":"158","author":"Infante","year":"2016","journal-title":"Procedia Eng."},{"key":"ref_4","unstructured":"Peduto, D., Pisciotta, G., Nicodemo, G., Arena, L., Ferlisi, S., Gull\u00e0, G., Borrelli, L., Fornaro, G., and Reale, D. (2016, January 17\u201318). A procedure for the analysis of building vulnerability to slow-moving landslides. Proceedings of the 1st IMEKO International Workshop on Metrology for Geotechnics, Benevento, Italy."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Del Soldato, M., Solari, L., Poggi, F., Raspini, F., Tom\u00e1s, R., Fanti, R., and Casagli, N. (2019). Landslide-Induced Damage Probability Estimation Coupling InSAR and Field Survey Data by Fragility Curves. Remote Sens., 11.","DOI":"10.3390\/rs11121486"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"109638","DOI":"10.1016\/j.engstruct.2019.109638","article-title":"Assessment of building behavior in slow-moving landslide-affected areas through DInSAR data and structural analysis","volume":"199","author":"Infante","year":"2019","journal-title":"Eng. Struct."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"3265","DOI":"10.1177\/1475921720983232","article-title":"The use of satellite data to support the structural health monitoring in areas affected by slow-moving landslides: A potential application to reinforced concrete buildings","volume":"20","author":"Miano","year":"2021","journal-title":"Struct. Health Monit."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1007\/s43452-022-00407-7","article-title":"Potential of remote sensing data to support the seismic safety assessment of reinforced concrete buildings affected by slow-moving landslides","volume":"22","author":"Mele","year":"2022","journal-title":"Arch. Civ. Eng."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Drougkas, A., Verstrynge, E., Van Balen, K., Shimoni, M., Croonenborghs, T., Hayen, R., and Declercq, P.Y. (2020). Country-scale InSAR monitoring for settlement and uplift damage calculation in architectural heritage structures. Struct. Health Monit., 1475921720942120.","DOI":"10.1177\/1475921720942120"},{"key":"ref_10","unstructured":"Giannico, C., Ferretti, A., Alberti, S., Jurina, L., Ricci, M., and Sciotti, A. (2012, January 3\u20136). Application of satellite radar interferometry for structural damage assessment and monitoring LifeCycle and Sustainability of Civil Infrastructure Systems. Proceedings of the 3rd International Symphosium on Life-Cycle Civil Engineering (IALCCE \u201912), Vienna, Austria."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1114","DOI":"10.1016\/j.ijrmms.2010.07.006","article-title":"Mapping ground movements in open pit mining areas using differential SAR interferometry","volume":"47","author":"Herrera","year":"2010","journal-title":"Int. J. Rock Mech. Min."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"114077","DOI":"10.1016\/j.engstruct.2022.114077","article-title":"Fragility curves for different classes of existing RC buildings under ground differential settlements","volume":"257","author":"Miano","year":"2022","journal-title":"Eng. Struct."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"102115","DOI":"10.1016\/j.ijdrr.2021.102115","article-title":"Subsidence in Como historic centre (northern Italy): Assessment of building vulnerability combining hydrogeological and stratigraphic features, Cosmo-SkyMed InSAR and damage data","volume":"56","author":"Nappo","year":"2021","journal-title":"Int. J. Disaster Risk Reduct."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"9183","DOI":"10.1029\/JB094iB07p09183","article-title":"Mapping small elevation changes over large areas: Differential radar interferometry","volume":"94","author":"Gabriel","year":"1989","journal-title":"J. Geophys. Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1029\/97RG03139","article-title":"Radar interferometry and its application to changes in the earth\u2019s surface","volume":"36","author":"Massonnet","year":"1998","journal-title":"Rev. Geophys."},{"key":"ref_16","first-page":"333","article-title":"Synthetic aperture radar interferometry","volume":"88","author":"Rosen","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"6-1","DOI":"10.1029\/2001GL014571","article-title":"Evidence for a peculiar style of ground deformation inferred at Vesuvius volcano","volume":"29","author":"Lanari","year":"2002","journal-title":"Geophys. Res. Lett."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2113","DOI":"10.1007\/s10346-018-1015-z","article-title":"Multisource data integration to investigate one century of evolution for the Agnone landslide (Molise, southern Italy)","volume":"15","author":"Riquelme","year":"2018","journal-title":"Landslides"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"4678","DOI":"10.3390\/rs70404678","article-title":"Building deformation assessment by means of persistent scatterer interferometry analysis on a landslide-affected area: The Volterra (Italy) case study","volume":"7","author":"Bianchini","year":"2015","journal-title":"Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Ponzo, F.C., Iacovino, C., Ditommaso, R., Bonano, M., Lanari, R., Soldovieri, F., Cuomo, V., Bozzano, F., Ciampi, P., and Rompato, M. (2021). Transport Infrastructure SHM Using Integrated SAR Data and On-Site Vibrational Acquisitions: \u201cPonte Della Musica\u2013Armando Trovajoli\u201d Case Study. Appl. Sci., 11.","DOI":"10.3390\/app11146504"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2523","DOI":"10.1109\/TGRS.2006.874137","article-title":"Automatic construction of building footprints from airborne LIDAR data","volume":"44","author":"Zhang","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"04017021","DOI":"10.1061\/(ASCE)CP.1943-5487.0000674","article-title":"Urban point cloud mining based on density clustering and MapReduce","volume":"31","author":"Aljumaily","year":"2017","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1887","DOI":"10.1109\/TGRS.2017.2769120","article-title":"Deep learning-based classification and reconstruction of residential scenes from large-scale point clouds","volume":"56","author":"Zhang","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2327","DOI":"10.1080\/01431161.2020.1851062","article-title":"DBSCAN-based point cloud extraction for Tomographic synthetic aperture radar (TomoSAR) three-dimensional (3D) building reconstruction","volume":"42","author":"Guo","year":"2021","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Rahimzad, M., Homayouni, S., Alizadeh Naeini, A., and Nadi, S. (2021). An Efficient Multi-Sensor Remote Sensing Image Clustering in Urban Areas via Boosted Convolutional Autoencoder (BCAE). Remote Sens., 13.","DOI":"10.3390\/rs13132501"},{"key":"ref_26","unstructured":"Franceschetti, G., and Lanari, R. (1999). Synthetic Aperture Radar Processing, CRC Press LLC. [1st ed.]."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2375","DOI":"10.1109\/TGRS.2002.803792","article-title":"A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms","volume":"40","author":"Berardino","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1377","DOI":"10.1109\/TGRS.2004.828196","article-title":"A small baseline approach for investigating deformations on full resolution differential SAR interferograms","volume":"42","author":"Lanari","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1665","DOI":"10.1080\/01431160701395278","article-title":"Two-scale surface deformation analysis using the SBAS-DInSAR technique: A case study of the city of Rome, Italy","volume":"29","author":"Manunta","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"4756","DOI":"10.1080\/01431161.2011.638340","article-title":"Long-term ERS\/ENVISAT deformation time-series generation at full spatial resolution via the extended SBAS technique","volume":"33","author":"Bonano","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.rse.2006.01.023","article-title":"A quantitative assessment of the SBAS algorithm performance for surface deformation retrieval from DInSAR data","volume":"102","author":"Casu","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"6259","DOI":"10.1109\/TGRS.2019.2904912","article-title":"The parallel SBAS approach for Sentinel-1 interferometric wide swath deformation time-series generation: Algorithm description and products quality assessment","volume":"57","author":"Manunta","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1463","DOI":"10.1007\/s00024-011-0403-2","article-title":"A Quantitative Assessment of DInSAR Measurements of Interseismic Deformation: The Southern San Andreas Fault Case Study","volume":"169","author":"Manzo","year":"2012","journal-title":"Pure Appl. Geophys."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1973","DOI":"10.1109\/TGRS.2012.2232933","article-title":"From previous C-band to new X-band SAR systems: Assessment of the DInSAR mapping improvement for deformation time-series retrieval in urban areas","volume":"51","author":"Bonano","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.tecto.2011.10.013","article-title":"Recent advances in SAR interferometry time series analysis for measuring crustal deformation","volume":"514","author":"Hooper","year":"2012","journal-title":"Tectonophysics"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"103756","DOI":"10.1016\/j.jobe.2021.103756","article-title":"Satellite radar interferometry: Potential and limitations for structural assessment and monitoring","volume":"46","author":"Talledo","year":"2022","journal-title":"J. Build. Eng."},{"key":"ref_37","first-page":"226","article-title":"A density-based algorithm for discovering clusters in large spatial databases with noise","volume":"96","author":"Ester","year":"1996","journal-title":"Kdd"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3068335","article-title":"DBSCAN revisited, revisited: Why and how you should (still) use DBSCAN","volume":"42","author":"Schubert","year":"2017","journal-title":"ACM Trans. Database Syst."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Huang, F., Zhu, Q., Zhou, J., Tao, J., Zhou, X., Jin, D., Tan, X., and Wang, L. (2017). Research on the Parallelization of the DBSCAN Clustering Algorithm for Spatial Data Mining Based on the Spark Platform. Remote Sens., 9.","DOI":"10.3390\/rs9121301"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Xie, C., Chen, P., Pan, D., Zhong, C., and Zhang, Z. (2021). Improved Filtering of ICESat-2 Lidar Data for Nearshore Bathymetry Estimation Using Sentinel-2 Imagery. Remote Sens., 13.","DOI":"10.3390\/rs13214303"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Roshandel, S., Liu, W., Wang, C., and Li, J. (2021). 3D Ocean Water Wave Surface Analysis on Airborne LiDAR Bathymetric Point Clouds. Remote Sens., 13.","DOI":"10.3390\/rs13193918"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Xu, Q., Cao, L., Xue, L., Chen, B., An, F., and Yun, T. (2019). Extraction of Leaf Biophysical Attributes Based on a Computer Graphic-based Algorithm Using Terrestrial Laser Scanning Data. Remote Sens., 11.","DOI":"10.3390\/rs11010015"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Starczewski, A., and Cader, A. (2019, January 16\u201320). Determining the EPS parameter of the DBSCAN algorithm. Proceedings of the International Conference on Artificial Intelligence and Soft Computing (ICAISC), Zakopane, Poland.","DOI":"10.1007\/978-3-030-20915-5_38"},{"key":"ref_44","first-page":"012012","article-title":"Determination of optimal epsilon (eps) value on dbscan algorithm to clustering data on peatland hotspots in sumatra","volume":"Volume 31","author":"Rahmah","year":"2016","journal-title":"IOP Conference Series: Earth and Environmental Science"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1023\/A:1009745219419","article-title":"Density-based clustering in spatial databases: The algorithm gdbscan and its applications","volume":"2","author":"Sander","year":"1998","journal-title":"Data Min. Knowl. Discov."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Berto, L., Doria, A., Saetta, A., Stella, A., and Talledo, D. (2021). Assessment of the Applicability of DInSAR Techniques for Structural Monitoring of Cultural Heritage and Archaeological Sites. International Workshop on Civil Structural Health Monitoring, Springer.","DOI":"10.1007\/978-3-030-74258-4_44"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"3160","DOI":"10.1016\/j.rse.2008.03.008","article-title":"Subsidence induced by urbanisation in the city of Rome detected by advanced InSAR technique and geotechnical investigations","volume":"112","author":"Stramondo","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.rse.2016.04.017","article-title":"On the joint exploitation of long-term DInSAR time series and geological information for the investigation of ground settlements in the town of Roma (Italy)","volume":"182","author":"Scifoni","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_49","first-page":"5","article-title":"Satellite A-DInSAR monitoring of the Vittoriano monument (Rome, Italy): Implications for heritage reserva tion","volume":"2","author":"Bozzano","year":"2020","journal-title":"Ital. J. Eng. Geol. Environ."},{"key":"ref_50","unstructured":"(2019). Decreto Ministeriale Sanit\u00e0 5 Luglio 1975\u2014Modificazioni Alle Istruzioni Ministeriali 20 Giugno 1896, Relativamente All\u2019altezza Minima ed ai Requisiti Igienico-Sanitari Principali dei Locali di Abitazione, Gazzetta Ufficiale n.190 del 18\/07\/1975, Ministry of Health of Italy. (In Italian)."},{"key":"ref_51","unstructured":"CTR (2021, November 08). Carta Tecnica Regionale Numerica Scala 1:500 Privincia di Roma. Available online: https:\/\/dati.lazio.it\/catalog\/it\/dataset\/carta-tecnica-regionale-2002-2003-5k-roma.it."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1007\/s40745-015-0040-1","article-title":"A comprehensive survey of clustering algorithms","volume":"2","author":"Xu","year":"2015","journal-title":"Ann. Data Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/8\/1872\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:53:27Z","timestamp":1760136807000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/8\/1872"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,13]]},"references-count":52,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["rs14081872"],"URL":"https:\/\/doi.org\/10.3390\/rs14081872","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2022,4,13]]}}}