{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T07:03:39Z","timestamp":1760598219679,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,2,9]],"date-time":"2023-02-09T00:00:00Z","timestamp":1675900800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003447","name":"State Scholarships Foundation (\u0399\u039a\u03a5)","doi-asserted-by":"publisher","award":["MIS-5000432"],"award-info":[{"award-number":["MIS-5000432"]}],"id":[{"id":"10.13039\/501100003447","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In many countries globally, information for new buildings is either scarce or incomplete. In an effort to bridge this information gap an approach based on public domain synthetic aperture radar (SAR) satellite data is introduced. The method is based on the persistent scatterer interferometry (PSI) technique in order to detect newly constructed buildings and estimate their heights in a selected case study area in Athens, Greece. The overall objective is to derive timely spatial information for building activity. A key concept of the approach is the residual height, i.e., the difference in height of each point compared to a reference point that is suitably selected. The data used are acquired by the Sentinel-1 satellite. Both ascending and descending orbits and dual polarizations (VV\/VH) are used. The results show that as much as 70% of new buildings can be detected at a vertical accuracy approximately of 2.5 m, which is sufficient to determine the number of stories per building. Overall, the proposed method can provide an efficient insight regarding building activity and provide a significant information layer for urban studies in a rapidly changing world.<\/jats:p>","DOI":"10.3390\/rs15040950","type":"journal-article","created":{"date-parts":[[2023,2,10]],"date-time":"2023-02-10T05:51:06Z","timestamp":1676008266000},"page":"950","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Monitoring Building Activity by Persistent Scatterer Interferometry"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3730-7279","authenticated-orcid":false,"given":"Vasilis","family":"Letsios","sequence":"first","affiliation":[{"name":"Spatial Analysis, GIS and Thematic Mapping Laboratory, Department of Planning and Regional Development, University of Thessaly, 38334 Volos, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5260-8232","authenticated-orcid":false,"given":"Ioannis","family":"Faraslis","sequence":"additional","affiliation":[{"name":"Department of Environmental Sciences, University of Thessaly, 41222 Larisa, Greece"}]},{"given":"Demetris","family":"Stathakis","sequence":"additional","affiliation":[{"name":"Spatial Analysis, GIS and Thematic Mapping Laboratory, Department of Planning and Regional Development, University of Thessaly, 38334 Volos, Greece"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Alaloul, W.S., Musarat, M.A., Rabbani, M.B.A., Iqbal, Q., Maqsoom, A., and Farooq, W. (2021). Construction Sector Contribution to Economic Stability: Malaysian Gdp Distribution. Sustainability, 13.","DOI":"10.3390\/su13095012"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1080\/19479832.2014.941018","article-title":"Measuring the Compactness of European Medium-Sized Cities by Spatial Metrics Based on Fused Data Sets","volume":"6","author":"Stathakis","year":"2015","journal-title":"Int. J. Image Data Fusion"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1092","DOI":"10.1080\/10106049.2015.1027289","article-title":"Examining Urban Sprawl in Europe Using Spatial Metrics","volume":"30","author":"Triantakonstantis","year":"2015","journal-title":"Geocarto Int."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"756","DOI":"10.1177\/0265813515595406","article-title":"Forecasting Urban Sprawl in Dhaka City of Bangladesh","volume":"43","author":"Pramanik","year":"2016","journal-title":"Environ. Plan. B Plan. Des."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2305","DOI":"10.1109\/TGRS.2006.872903","article-title":"Comparison of Computational Intelligence Based Classification Techniques for Remotely Sensed Optical Image Classification","volume":"44","author":"Stathakis","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"6361","DOI":"10.1080\/01431161.2012.687842","article-title":"Efficient Segmentation of Urban Areas by the VIBI","volume":"33","author":"Stathakis","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1109\/LGRS.2007.895285","article-title":"Feature Evolution for Classification of Remotely Sensed Data","volume":"4","author":"Stathakis","year":"2007","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"55","DOI":"10.14358\/PERS.74.1.55","article-title":"Global Elevation Ancillary Data for Land-Use Classification Using Granular Neural Networks","volume":"74","author":"Stathakis","year":"2008","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/36.898661","article-title":"Permanent Scatterers in SAR Interferometry","volume":"39","author":"Ferretti","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Chini, M., Pelich, R., Hostache, R., Matgen, P., and Lopez-Martinez, C. (2018). Towards a 20 m Global Building Map from Sentinel-1 SAR Data. Remote Sens., 10.","DOI":"10.3390\/rs10111833"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Balz, T., Washaya, P., and Jendryke, M. (2018, January 22\u201323). Urban Change Monitoring Using Globally Available Sentinel-1 Imagery. Proceedings of the 2018 International Workshop on Big Geospatial Data and Data Science (BGDDS), Wuhan, China.","DOI":"10.1109\/BGDDS.2018.8626814"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Cao, H., Zhang, H., Wang, C., and Zhang, B. (2018). Operational Built-up Areas Extraction for Cities in China Using Sentinel-1 SAR Data. Remote Sens., 10.","DOI":"10.3390\/rs10060874"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"35","DOI":"10.5194\/isprs-annals-IV-1-W1-35-2017","article-title":"Monitoring of Building Construction by 4D Change Detection Using Multi-Temporal SAR Images","volume":"4","author":"Yang","year":"2017","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Li, L., Wang, C., Zhang, H., and Zhang, B. (August, January 28). Residual Unet for Urban Building Change Detection with Sentinel-1 SAR Data. Proceedings of the IGARSS 2019\u20142019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan.","DOI":"10.1109\/IGARSS.2019.8898146"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Zhang, J., Cui, M., Wang, B., Chen, C., Zhou, Y., and Li, J. (2021, January 13\u201315). A Novel SAR Images Change Detection Method Based on Dynamic TUNET-CRF Model. Proceedings of the 2021 IEEE International Conference on Smart Internet of Things (SmartIoT), Jeju Island, Korea.","DOI":"10.1109\/SmartIoT52359.2021.00026"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"9856","DOI":"10.1109\/LGRS.2021.3119856","article-title":"Sentinel-1 and Sentinel-2 Data Fusion for Urban Change Detection Using a Dual Stream U-Net","volume":"19","author":"Hafner","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Jaturapitpornchai, R., Matsuoka, M., Kanemoto, N., Kuzuoka, S., Ito, R., and Nakamura, R. (2019). Newly Built Construction Detection in SAR Images Using Deep Learning. Remote Sens., 11.","DOI":"10.3390\/rs11121444"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1914","DOI":"10.1109\/LGRS.2019.2958262","article-title":"An Unsupervised Approach to Change Detection in Built-Up Areas by Multitemporal PolSAR Images","volume":"17","author":"Pirrone","year":"2020","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"6608","DOI":"10.1109\/JSTARS.2021.3076085","article-title":"Fine Building Segmentation in High-Resolution SAR Images Via Selective Pyramid Dilated Network","volume":"14","author":"Jing","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2877","DOI":"10.1109\/JSTARS.2022.3162670","article-title":"Test Statistics for Reflection Symmetry: Applications to Quad-Polarimetric SAR Data for Detection of Man-Made Structures","volume":"15","author":"Connetable","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_21","unstructured":"Zhu, F., Zhang, Y., and Li, D. (2016, January 3). A Novel Polarimetric Interferometric SAR Coherence Parameter and Its Application in Buildings Detection. Proceedings of the 2016 Progress in Electromagnetics Research Symposium, PIERS 2016 Proceedings, Shanghai, China."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2664","DOI":"10.1109\/TGRS.2014.2363548","article-title":"Building Change Detection in Multitemporal Very High Resolution SAR Images","volume":"53","author":"Marin","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Liu, L., Zhang, F., Wu, Q., and Wang, G. (2011, January 24\u201329). Building Footprint Extraction by Fusing Dual-Aspect SAR Images. Proceedings of the 2011 IEEE International Geoscience and Remote Sensing Symposium, Vancouver, BC, Canada.","DOI":"10.1109\/IGARSS.2011.6049487"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1109\/TGRS.2012.2205156","article-title":"Automatic Detection and Reconstruction of Building Radar Footprints From Single VHR SAR Images","volume":"51","author":"Ferro","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Rapuzzi, A., Nattero, C., Pelich, R., Chini, M., and Campanella, P. (2020, January 26). CNN-Based Building Footprint Detection from Sentinel-1 SAR Imagery. Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS), Waikoloa, HI, USA.","DOI":"10.1109\/IGARSS39084.2020.9323609"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"513","DOI":"10.5721\/EuJRS20144729","article-title":"Detecting the Number of Buildings in a Single High-Resolution SAR Image","volume":"47","author":"Cao","year":"2014","journal-title":"Eur. J. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Koppel, K., Zalite, K., Sisas, A., Voormansik, K., Praks, J., and Noorma, M. (2015, January 10). Sentinel-1 for Urban Area Monitoring-Analysing Local-Area Statistics and Interferometric Coherence Methods for Buildings\u2019 Detection. Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy.","DOI":"10.1109\/IGARSS.2015.7325981"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"4043","DOI":"10.1109\/TGRS.2007.906092","article-title":"Urban-Target Recognition by Means of Repeated Spaceborne SAR Images","volume":"45","author":"Perissin","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.isprsjprs.2015.10.011","article-title":"Persistent Scatterer Interferometry: A Review","volume":"115","author":"Crosetto","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Panagiotakis, E., Chrysoulakis, N., Charalampopoulou, V., and Poursanidis, D. (2018). Validation of Pleiades Tri-Stereo DSM in Urban Areas. ISPRS Int. J. Geoinf., 7.","DOI":"10.20944\/preprints201801.0030.v1"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3338","DOI":"10.1109\/TGRS.2006.877754","article-title":"High-Accuracy Urban DEM Using Permanent Scatterers","volume":"44","author":"Perissin","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_32","unstructured":"Colesanti, C., Ferretti, A., Perissin, D., Prati, C., and Rocca, F. (2003, January 1\u20135). Evaluating the Effect of the Observation Time on the Distribution of SAR Permanent Scatterers. Proceedings of the FRINGE 2003, Frascati, Italy."},{"key":"ref_33","unstructured":"Ferretti, A., Perissin, D., and Prati, C. (December, January 28). Spaceborne SAR Anatomy of a City. Proceedings of the FRINGE 2005, Frascati, Italy."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2343","DOI":"10.1109\/TGRS.2006.875455","article-title":"Validating the SAR Wavenumber Shift Principle With the ERS\u2013Envisat PS Coherent Combination","volume":"44","author":"Perissin","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1109\/TGRS.2011.2160644","article-title":"Repeat-Pass SAR Interferometry with Partially Coherent Targets","volume":"50","author":"Perissin","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_36","unstructured":"Liang, S. (2018). Comprehensive Remote Sensing, Elsevier."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/4\/950\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:28:24Z","timestamp":1760120904000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/4\/950"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,9]]},"references-count":36,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["rs15040950"],"URL":"https:\/\/doi.org\/10.3390\/rs15040950","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2023,2,9]]}}}