{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:01:32Z","timestamp":1760241692486,"version":"build-2065373602"},"reference-count":25,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2018,7,25]],"date-time":"2018-07-25T00:00:00Z","timestamp":1532476800000},"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>This paper proposes a new method for forest height estimation using single-baseline single frequency polarimetric synthetic aperture radar interferometry (PolInSAR) data. The new algorithm estimates the forest height based on the random volume over the ground with a volume temporal decorrelation (RVoG+VTD) model. We approach the problem using a four-stage geometrical method without the need for any prior information. In order to decrease the number of unknown parameters in the RVoG+VTD model, the mean extinction coefficient is estimated in an independent procedure. In this respect, the suggested algorithm estimates the mean extinction coefficient as a function of a geometrical index based on the signal penetration in the volume layer. As a result, the proposed four-stage algorithm can be used for forest height estimation using the repeat pass PolInSAR data, affected by temporal decorrelation, without the need for any auxiliary data. The suggested algorithm was applied to the PolInSAR data of the European Space Agency (ESA), BioSAR 2007 campaign. For the performance analysis of the proposed approach, repeat pass experimental SAR (ESAR) L-band data, acquired over the Remningstorp test site in Southern Sweden, is employed. The experimental result shows that the four-stage method estimates the volume height with an average root mean square error (RMSE) of 2.47 m against LiDAR heights. It presents a significant improvement of forest height accuracy, i.e., 5.42 m, compared to the three-stage method result, which ignores the temporal decorrelation effect.<\/jats:p>","DOI":"10.3390\/rs10081174","type":"journal-article","created":{"date-parts":[[2018,7,25]],"date-time":"2018-07-25T08:28:47Z","timestamp":1532507327000},"page":"1174","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Four-Stage Inversion Algorithm for Forest Height Estimation Using Repeat Pass Polarimetric SAR Interferometry Data"],"prefix":"10.3390","volume":"10","author":[{"given":"Tayebe","family":"Managhebi","sequence":"first","affiliation":[{"name":"Faculty of Geodesy and Geomatics, K. N. Toosi University of Technology, Tehran 19667-15433, Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2731-9057","authenticated-orcid":false,"given":"Yasser","family":"Maghsoudi","sequence":"additional","affiliation":[{"name":"Faculty of Geodesy and Geomatics, K. N. Toosi University of Technology, Tehran 19667-15433, Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4325-8741","authenticated-orcid":false,"given":"Mohammad Javad","family":"Valadan Zoej","sequence":"additional","affiliation":[{"name":"Faculty of Geodesy and Geomatics, K. N. Toosi University of Technology, Tehran 19667-15433, Iran"}]}],"member":"1968","published-online":{"date-parts":[[2018,7,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1449","DOI":"10.1029\/96RS01763","article-title":"Vegetation characteristics and underlying topography from interferometric radar","volume":"31","author":"Treuhaft","year":"1996","journal-title":"Radio Sci."},{"key":"ref_2","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_3","doi-asserted-by":"crossref","first-page":"1551","DOI":"10.1109\/36.718859","article-title":"Polarimetric SAR interferometry","volume":"36","author":"Cloude","year":"1998","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1049\/ip-rsn:20030449","article-title":"Three-stage inversion process for polarimetric SAR interferometry","volume":"150","author":"Cloude","year":"2003","journal-title":"IEE Proc. Radar Sonar Navig."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2352","DOI":"10.1109\/36.964971","article-title":"Single-baseline polarimetric SAR interferometry","volume":"39","author":"Papathanassiou","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2792","DOI":"10.1109\/TGRS.2015.2505707","article-title":"Extended three-stage polarimetric SAR interferometry algorithm by dual-polarization data","volume":"54","author":"Wenxue","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1109\/LGRS.2018.2808945","article-title":"An improved three-stage inversion algorithm in forest height estimation using single-baseline polarimetric SAR interferometry data","volume":"15","author":"Managhebi","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Managhebi, T., Maghsoudi, Y., and Valadanzoej, M.J. (2018). A volume optimization method to improve the three-stage inversion algorithm for forest height estimation using PolInSAR data. IEEE Geosci. Remote Sens. Lett., accepted.","DOI":"10.1109\/LGRS.2018.2830744"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Xie, Q., Zhu, J., Wang, C., and Fu, H. (2014, January 11\u201314). Boreal forest height inversion using E-SAR PolInSAR data based coherence optimization methods and three-stage algorithm. Proceedings of the Earth Observation and Remote Sensing Applications (EORSA), Changsha, China.","DOI":"10.1109\/EORSA.2014.6927867"},{"key":"ref_10","unstructured":"Papathanassiou, K., and Cloude, S.R. (2003, January 21\u201325). The effect of temporal decorrelation on the inversion of forest parameters from PoI-InSAR data. Proceedings of the International Geoscience and Remote Sensing Symposium, Toulouse, France."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"4752","DOI":"10.1109\/TGRS.2015.2409066","article-title":"Extraction of structural and dynamic properties of forests from polarimetric-interferometric SAR data affected by temporal decorrelation","volume":"53","author":"Lavalle","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Zhou, Y.S., Hong, W., Cao, F., Wang, Y.P., and Wu, Y.R. (2008, January 7\u201311). Analysis of temporal decorrelation in dual-baseline PolInSAR vegetation parameter estimation. Proceedings of the Geoscience and Remote Sensing Symposium, Boston, MA, USA.","DOI":"10.1109\/IGARSS.2008.4779031"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1086","DOI":"10.1109\/TGRS.2009.2031101","article-title":"Estimation of forest structure, ground, and canopy layer characteristics from multibaseline polarimetric interferometric SAR data","volume":"48","author":"Neumann","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2880","DOI":"10.1109\/TGRS.2011.2174367","article-title":"A temporal decorrelation model for polarimetric radar interferometers","volume":"50","author":"Lavalle","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1314","DOI":"10.1007\/s11430-013-4669-3","article-title":"Forest-height inversion using repeat-pass spaceborne polInSAR data","volume":"57","author":"Li","year":"2014","journal-title":"Sci. China Earth Sci."},{"key":"ref_16","unstructured":"Hajnsek, I., Scheiber, R., Lee, S., Ulander, L., Gustavsson, A., Tebaldini, S., and Monti-Guarnieri, A. (2008). BIOSAR 2007: Technical Assistance for the Development of Airborne SAR and Geophysical Measurements during the BioSAR 2007 Experiment, ESA-ESTEC."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Richards, J.A. (2009). Remote Sensing with Imaging Radar, Springer.","DOI":"10.1007\/978-3-642-02020-9"},{"key":"ref_18","unstructured":"Lee, S.-K. (2012). Forest Parameter Estimation Using Polarimetric SAR Interferometry Techniques at Low Frequencies. [Ph.D. Thesis, ETH Zurich]."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1018","DOI":"10.1007\/s11430-015-5070-1","article-title":"Inversion of vegetation height from PolInSAR using complex least squares adjustment method","volume":"58","author":"Fu","year":"2015","journal-title":"Sci. China Earth Sci."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Xie, Q., Zhu, J., Wang, C., Fu, H., Lopez-Sanchez, J.M., and Ballester-Berman, J.D. (2017). A Modified Dual-Baseline PolInSAR Method for Forest Height Estimation. Remote Sens., 9.","DOI":"10.3390\/rs9080819"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1048","DOI":"10.1109\/TGRS.2014.2332553","article-title":"PolInSAR coherence region modeling and inversion: The best normal matrix approximation solution","volume":"53","author":"Cui","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"963","DOI":"10.1109\/36.673687","article-title":"A three-component scattering model for polarimetric SAR data","volume":"36","author":"Freeman","year":"1998","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","unstructured":"Lee, S.-k., Kugler, F., Hajnsek, I., and Papathanassiou, K. (2009, January 26\u201330). The impact of temporal decorrelation over forest terrain in polarimetric SAR interferometry. Proceedings of the International Workshop on Applications of Polarimetry and Polarimetric Interferometry (Pol-InSAR), Frascati, Italy."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Cloude, S. (2010). Polarisation: Applications in Remote Sensing, Oxford University Press. [1st ed.].","DOI":"10.1093\/acprof:oso\/9780199569731.001.0001"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1528","DOI":"10.1109\/TGRS.2009.2032538","article-title":"Forest modeling for height inversion using single-baseline InSAR\/Pol-InSAR data","volume":"48","author":"Garestier","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/8\/1174\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:14:15Z","timestamp":1760195655000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/8\/1174"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,25]]},"references-count":25,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2018,8]]}},"alternative-id":["rs10081174"],"URL":"https:\/\/doi.org\/10.3390\/rs10081174","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2018,7,25]]}}}