{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T15:35:45Z","timestamp":1769268945929,"version":"3.49.0"},"reference-count":35,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2022,6,24]],"date-time":"2022-06-24T00:00:00Z","timestamp":1656028800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"IDS Georadar"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Many Ground-Based Synthetic Aperture Radar (GBSAR) applications demand preliminary analysis to select areas with high-quality signal. That is, areas in which the phase can be processed to extract the desired information. The interferometric coherence and the amplitude dispersion index are important tools widely used in the literature to assess the quality of GBSAR images. So far, no direct relation has been found between the two. Indeed, they are parameters of different natures: amplitude dispersion index is calculated with only amplitude values, while coherence provides information also on the signal phase. The purpose of this article is to find a relation between the two parameters. Indeed, the amplitude dispersion index provides some practical advantages if compared to coherence estimators, especially to perform fast preliminary analysis. In this article, a theoretical relation between amplitude dispersion index and coherence is retrieved. GBSAR measurements acquired in different scenarios, at different working frequencies are presented and used to validate such a relation.<\/jats:p>","DOI":"10.3390\/rs14133039","type":"journal-article","created":{"date-parts":[[2022,6,26]],"date-time":"2022-06-26T22:50:23Z","timestamp":1656283823000},"page":"3039","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Temporal Coherence Estimators for GBSAR"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0822-8689","authenticated-orcid":false,"given":"Alessandra","family":"Beni","sequence":"first","affiliation":[{"name":"Department of Information Engineering, University of Florence, 50139 Florence, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7285-4588","authenticated-orcid":false,"given":"Lapo","family":"Miccinesi","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, University of Florence, 50139 Florence, Italy"}]},{"given":"Alberto","family":"Michelini","sequence":"additional","affiliation":[{"name":"IDS GeoRadar s.r.l., 56121 Pisa, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3661-726X","authenticated-orcid":false,"given":"Massimiliano","family":"Pieraccini","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, University of Florence, 50139 Florence, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/MGRS.2019.2963169","article-title":"Ground-Based Differential Interferometry SAR: A Review","volume":"8","author":"Wang","year":"2020","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"950","DOI":"10.1109\/36.175330","article-title":"Decorrelation in interferometric radar echoes","volume":"30","author":"Zebker","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3757","DOI":"10.1109\/JSTARS.2018.2863369","article-title":"Impact of Wind-Induced Scatterers Motion on GB-SAR Imaging","volume":"11","author":"Lort","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Monti-Guarnieri, A., Manzoni, M., Giudici, D., Recchia, A., and Tebaldini, S. (2020). Vegetated Target Decorrelation in SAR and Interferometry: Models, Simulation, and Performance Evaluation. Remote Sens., 12.","DOI":"10.3390\/rs12162545"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1109\/36.739146","article-title":"Coherence estimation for SAR imagery","volume":"37","author":"Touzi","year":"1999","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","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_7","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_8","doi-asserted-by":"crossref","unstructured":"Dainty, J.C. (1975). Statistical Properties of Laser Speckle Patterns. Laser Speckle and Related Phenomena, Springer.","DOI":"10.1007\/978-3-662-43205-1"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/S0165-1684(01)00158-X","article-title":"Statistical characterisation and modelling of SAR images","volume":"82","author":"Chitroub","year":"2002","journal-title":"Signal Process."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"775","DOI":"10.3390\/s100100775","article-title":"Statistical Modeling of SAR Images: A Survey","volume":"10","author":"Gao","year":"2010","journal-title":"Sensors"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2454","DOI":"10.1109\/TGRS.2004.836792","article-title":"Ground-based radar interferometry for landslides monitoring: Atmospheric and instrumental decorrelation sources on experimental data","volume":"42","author":"Luzi","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2942","DOI":"10.1109\/TGRS.2010.2043442","article-title":"Decorrelation of L-Band and C-Band Interferometry Over Vegetated Areas in California","volume":"48","author":"Wei","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2436","DOI":"10.1109\/TGRS.2013.2261077","article-title":"Atmospheric Phase Screen Compensation in Ground-Based SAR with a Multiple-Regression Model Over Mountainous Regions","volume":"52","author":"Iglesias","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1109\/LGRS.2010.2090647","article-title":"Atmospheric Phase Screen in Ground-Based Radar: Statistics and Compensation","volume":"8","author":"Iannini","year":"2010","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_15","first-page":"1","article-title":"Time-Series Clustering Methodology for Estimating Atmospheric Phase Screen in Ground-Based InSAR Data","volume":"60","author":"Izumi","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Hu, C., Deng, Y., Tian, W., and Zhao, Z. (2019). A Compensation Method for a Time\u2013Space Variant Atmospheric Phase Applied to Time-Series GB-SAR Images. Remote Sens., 11.","DOI":"10.3390\/rs11202350"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2022.3229302","article-title":"A Grid Partition Method for Atmospheric Phase Compensation in GB-SAR","volume":"60","author":"Deng","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_18","first-page":"1","article-title":"Atmospheric Phase Screen Compensation on Wrapped Ground-Based SAR Interferograms","volume":"60","author":"Falabella","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3289","DOI":"10.1109\/TGRS.2007.902286","article-title":"Modeling Interferogram Stacks","volume":"45","author":"Rocca","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2285","DOI":"10.1109\/LGRS.2017.2761900","article-title":"Quantification of Temporal Decorrelation in X-, C-, and L-Band Interferometry for the Permafrost Region of the Qinghai\u2013Tibet Plateau","volume":"14","author":"Tang","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1096","DOI":"10.1109\/TGRS.2014.2333814","article-title":"Temporal Decorrelation in L-, C-, and X-band Satellite Radar Interferometry for Pasture on Drained Peat Soils","volume":"53","author":"Morishita","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1109\/36.581984","article-title":"SAR interferometry: A \u201cQuick and dirty\u201d coherence estimator for data browsing","volume":"35","author":"Guarnieri","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2254","DOI":"10.1109\/TGRS.2003.817196","article-title":"Speckle filtering and coherence estimation of polarimetric sar interferometry data for forest applications","volume":"41","author":"Lee","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1109\/TAU.1973.1162496","article-title":"Estimation of the magnitude-squared coherence function via overlapped fast Fourier transform processing","volume":"21","author":"Carter","year":"1973","journal-title":"IEEE Trans. Audio Electroacoust."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1029\/RG006i003p00347","article-title":"The application of the discrete Fourier transform in the estimation of power spectra, coherence, and bispectra of geophysical data","volume":"6","author":"Hinich","year":"1968","journal-title":"Rev. Geophys."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Blasch, E., and Yang, C. (2012, January 2\u20135). FFT-based auto-correlation estimation (FACE) for extended radar pulse integration subject to large doppler change. Proceedings of the 2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA), Montreal, QC, Canada.","DOI":"10.1109\/ISSPA.2012.6310465"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1116","DOI":"10.1109\/TGRS.2004.826554","article-title":"Analysis and statistical characterization of interferometric SAR signals based on the power spectral density function","volume":"42","author":"Holzner","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1594","DOI":"10.1186\/s40064-016-3262-6","article-title":"Atmospheric phase screen correction in ground-based SAR with PS technique","volume":"5","author":"Qiu","year":"2016","journal-title":"SpringerPlus"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1459","DOI":"10.1109\/TGRS.2005.848707","article-title":"Permanent scatterers analysis for atmospheric correction in ground-based SAR interferometry","volume":"43","author":"Noferini","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_30","first-page":"567","article-title":"A statistical description of polarimetric and interferometric synthetic aperture radar data","volume":"449","author":"Tough","year":"1995","journal-title":"Proc. R. Soc. Lond. Ser. A Math. Phys. Sci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1690","DOI":"10.1364\/JOSA.69.001690","article-title":"Speckle-pattern intensity and phase: Second-order conditional statistics","volume":"69","author":"Donati","year":"1979","journal-title":"J. Opt. Soc. Am."},{"key":"ref_32","unstructured":"Bamler, R., and Just, D. (2002, January 18\u201321). Phase statistics and decorrelation in SAR interferograms. Proceedings of the IGARSS\u201993\u2014IEEE International Geoscience and Remote Sensing Symposium, Tokyo, Japan."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"R1","DOI":"10.1088\/0266-5611\/14\/4\/001","article-title":"Synthetic aperture radar interferometry","volume":"14","author":"Bamler","year":"1998","journal-title":"Inverse Probl."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1109\/TMTT.2016.2613926","article-title":"ArcSAR: Theory, Simulations, and Experimental Verification","volume":"65","author":"Pieraccini","year":"2016","journal-title":"IEEE Trans. Microw. Theory Tech."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Di Pasquale, A., Nico, G., Pitullo, A., and Prezioso, G. (2018). Monitoring Strategies of Earth Dams by Ground-Based Radar Interferometry: How to Extract Useful Information for Seismic Risk Assessment. Sensors, 18.","DOI":"10.3390\/s18010244"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/13\/3039\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:39:33Z","timestamp":1760139573000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/13\/3039"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,24]]},"references-count":35,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2022,7]]}},"alternative-id":["rs14133039"],"URL":"https:\/\/doi.org\/10.3390\/rs14133039","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,24]]}}}