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In this article, a forest height estimation approach combining P-band and X-band interferometric synthetic aperture radar (InSAR) was introduced. The forest height was estimated using the difference in the penetration of long- and short-wavelength radars to the forest. That is, the P-band and X-band InSAR data were used to extract the digital terrain model (DTM) and digital surface model (DSM), respectively. For the DTM, an improved time-frequency (TF) analysis method was used to reduce the effect of forest scatterers on the extraction of a pure understory terrain phase based on P-band InSAR. For the DSM, a novel compensation algorithm based on a multi-layer model (MLM) was proposed to remove the penetration bias of the X-band. Compared to the existing method based on the infinitely deep uniform volumes (IDUV) model, the MLM-based method is more in line with the characteristics of forest structure and the scattering mechanism for X-band InSAR. The airborne P-band repeat-pass InSAR and spaceborne X-band (TanDEM-X) single-pass InSAR data were used to verify the proposed method over the study area in the Saihanba Forest Farm in Hebei, China. The results demonstrated that the improved TF method can achieve high-precision DTM extraction based on P-band InSAR data, and the root mean square error (RMSE) was 0.94 m. The proposed MLM-based compensation method of the DSM achieved a smaller error (RMSE: 1.67 m) compared to the IDUV-based method (RMSE: 3.01 m). Under the same DTM extracted by P-band InSAR, the estimation accuracy of forest height based on the MLM method was 86.58% (RMSE: 1.81 m), which was 8.49% higher than that of the IDUV-based method (RMSE: 2.98 m).<\/jats:p>","DOI":"10.3390\/rs14133070","type":"journal-article","created":{"date-parts":[[2022,6,26]],"date-time":"2022-06-26T22:50:23Z","timestamp":1656283823000},"page":"3070","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Forest Height Estimation Approach Combining P-Band and X-Band Interferometric SAR Data"],"prefix":"10.3390","volume":"14","author":[{"given":"Kunpeng","family":"Xu","sequence":"first","affiliation":[{"name":"Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China"},{"name":"Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Chinese Academy of Forestry, Beijing 100091, China"}]},{"given":"Lei","family":"Zhao","sequence":"additional","affiliation":[{"name":"Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China"},{"name":"Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Chinese Academy of Forestry, Beijing 100091, China"}]},{"given":"Erxue","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China"},{"name":"Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Chinese Academy of Forestry, Beijing 100091, China"}]},{"given":"Kun","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Remote Sensing Satellite, China Academy of Space Technology, Beijing 100094, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3665-1978","authenticated-orcid":false,"given":"Dacheng","family":"Liu","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100090, China"}]},{"given":"Tao","family":"Li","sequence":"additional","affiliation":[{"name":"Land Satellite Remote Sensing Application Center, Ministry of Natural Resources, Beijing 100048, China"}]},{"given":"Zengyuan","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China"},{"name":"Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Chinese Academy of Forestry, Beijing 100091, China"}]},{"given":"Yaxiong","family":"Fan","sequence":"additional","affiliation":[{"name":"Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China"},{"name":"Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Chinese Academy of Forestry, Beijing 100091, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,26]]},"reference":[{"key":"ref_1","unstructured":"GCOS (2016). The Global Observing System for Climate: Implementation Needs, Global Climate Observing System."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1136","DOI":"10.1016\/j.foreco.2008.11.022","article-title":"A comparison of lidar, radar, and field measurements of canopy height in pine and hardwood forests of southeastern North America","volume":"257","author":"Sexton","year":"2009","journal-title":"For. Ecol. Manag."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"111283","DOI":"10.1016\/j.rse.2019.111283","article-title":"Forest biomass estimation over three distinct forest types using TanDEM-X InSAR data and simulated GEDI lidar data","volume":"232","author":"Qi","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1109\/TGRS.2011.2159614","article-title":"Multibaseline polarimetric SAR tomography of a boreal forest at P-and L-bands","volume":"50","author":"Tebaldini","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Cloude, S. (2009). Polarisation: Applications in Remote Sensing, OUP Oxford.","DOI":"10.1093\/acprof:oso\/9780199569731.001.0001"},{"key":"ref_6","unstructured":"Aulinger, T., Mette, T., Papathanassion, K., Hajnsek, I., Heurich, M., and Krzystek, P. (2005, January 17\u201321). Validation of heights from interferometric SAR and LIDAR over the temperate forest site \u201cNationalpark Bayerischer Wald\u201d. Proceedings of the POLinSAR 2005 Workshop, Frascati, Italy."},{"key":"ref_7","first-page":"74","article-title":"Estimating canopy fuel parameters in a Pacific Northwest conifer forest using multifrequency polarimetric IFSAR","volume":"900","author":"Andersen","year":"2004","journal-title":"Image"},{"key":"ref_8","first-page":"1682","article-title":"Tropical forest biomass mapping from dual frequency SAR interferometry (X and P-Bands)","volume":"35","author":"Santos","year":"2004","journal-title":"ISPRS Int. Soc. Photogramm. Remote Sens. Tech. Comm. VII"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3189","DOI":"10.1109\/JSTARS.2016.2520900","article-title":"The dual-band PolInSAR method for forest parametrization","volume":"9","author":"Shiroma","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1016\/j.rse.2006.11.014","article-title":"Forest canopy height and carbon estimation at Monks Wood National Nature Reserve, UK, using dual-wavelength SAR interferometry","volume":"108","author":"Balzter","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Karamvasis, K., and Karathanassi, V. (2015, January 16\u201319). Forest canopy height estimation using double-frequency repeat pass interferometry. Proceedings of the Third International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2015), Paphos, Cyprus.","DOI":"10.1117\/12.2192581"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"6404","DOI":"10.1109\/TGRS.2013.2296533","article-title":"TanDEM-X Pol-InSAR performance for forest height estimation","volume":"52","author":"Kugler","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"997","DOI":"10.1007\/s11771-020-4348-4","article-title":"A review of underlying topography estimation over forest areas by InSAR: Theory, advances, challenges and perspectives","volume":"27","author":"Xie","year":"2020","journal-title":"J. Cent. South Univ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"993","DOI":"10.1029\/96GL00456","article-title":"Dual-frequency interferometric SAR observations of a tropical rain-forest","volume":"23","author":"Rignot","year":"1996","journal-title":"Geophys. Res. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Mercer, B., Zhang, Q., Schwaebisch, M., Denbina, M., and Cloude, S. (2009, January 26\u201331). Forest height and ground topography at L-band from an experimental single-pass airborne Pol-InSAR system. Proceedings of the POLinSAR 2009, Frascati, Italy.","DOI":"10.1109\/IGARSS.2009.5418224"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1016\/j.rse.2018.03.033","article-title":"The impacts of spatial baseline on forest canopy height model and digital terrain model retrieval using P-band PolInSAR data","volume":"210","author":"Liao","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3544","DOI":"10.1109\/TGRS.2008.922032","article-title":"Forest height inversion using high-resolution P-band Pol-InSAR data","volume":"46","author":"Garestier","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Fu, H., Zhu, J., Wang, C., Wang, H., and Zhao, R. (2017). Underlying topography estimation over forest areas using high-resolution P-band single-baseline PolInSAR data. Remote Sens., 9.","DOI":"10.3390\/rs9040363"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1029\/1999RS900108","article-title":"Vertical structure of vegetated land surfaces from interferometric and polarimetric radar","volume":"35","author":"Treuhaft","year":"2000","journal-title":"Radio Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.isprsjprs.2013.11.009","article-title":"A practical method for SRTM DEM correction over vegetated mountain areas","volume":"87","author":"Su","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1016\/j.isprsjprs.2018.11.021","article-title":"Canopy penetration depth estimation with TanDEM-X and its compensation in temperate forests","volume":"147","author":"Schlund","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Ni, W., Guo, Z., Sun, G., and Chi, H. (2010, January 25\u201330). Investigation of forest height retrieval using SRTM-DEM and ASTER-GDEM. Proceedings of the 2010 IEEE International Geoscience and Remote Sensing Symposium, Honolulu, HI, USA.","DOI":"10.1109\/IGARSS.2010.5651443"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"7303","DOI":"10.3390\/rs6087303","article-title":"The penetration depth derived from the synthesis of ALOS\/PALSAR InSAR data and ASTER GDEM for the mapping of forest biomass","volume":"6","author":"Ni","year":"2014","journal-title":"Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Solberg, S., May, J., Bogren, W., Breidenbach, J., Torp, T., and Gizachew, B. (2018). Interferometric SAR DEMs for forest change in Uganda 2000\u20132012. Remote Sens., 10.","DOI":"10.3390\/rs10020228"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2319","DOI":"10.1109\/TGRS.2007.896613","article-title":"InSAR elevation bias caused by penetration into uniform volumes","volume":"45","author":"Dall","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","first-page":"71","article-title":"On some spectral properties of TanDEM-X interferograms over forested areas","volume":"10","author":"Krieger","year":"2012","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_27","unstructured":"Soja, M.J., and Ulander, L.M. (2014, January 3\u20135). Two-level forest model inversion of interferometric TanDEM-X data. Proceedings of the EUSAR 2014, 10th European Conference on Synthetic Aperture Radar, Berlin, Germany."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2020.3042202","article-title":"A New Approach for Forest Height Inversion Using X-Band Single-Pass InSAR Coherence Data","volume":"60","author":"Zhao","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1109\/LGRS.2014.2354551","article-title":"Estimation of forest height and canopy density from a single InSAR correlation coefficient","volume":"12","author":"Soja","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Soja, M.J., Persson, H.J., and Ulander, L.M. (2015, January 26\u201331). Detection of forest change and robust estimation of forest height from two-level model inversion of multi-temporal, single-pass InSAR data. Proceedings of the 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy.","DOI":"10.1109\/IGARSS.2015.7326673"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"112132","DOI":"10.1016\/j.rse.2020.112132","article-title":"Automated estimation of forest height and underlying topography over a Brazilian tropical forest with single-baseline single-polarization TanDEM-X SAR interferometry","volume":"252","author":"Lei","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1109\/TGRS.2007.907602","article-title":"Pine forest height inversion using single-pass X-band PolInSAR data","volume":"46","author":"Garestier","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_33","unstructured":"Ferro-Famil, L., Reigber, A., and Pottier, E. (2003, January 21\u201325). Scene characterization using sub-aperture polarimetric interferometric SAR data. Proceedings of the IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium, Toulouse, France."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1109\/LGRS.2011.2164051","article-title":"SAR target analysis based on multiple-sublook decomposition: A visual exploration approach","volume":"9","author":"Singh","year":"2011","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"714","DOI":"10.1109\/36.158865","article-title":"Real-time synthetic aperture radar(SAR) processing with a new subaperture approach","volume":"30","author":"Moreira","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_36","unstructured":"Small, D. (1998). Generation of Digital Elevation Models through Spaceborne SAR Interferometry, University of Zurich."},{"key":"ref_37","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_38","doi-asserted-by":"crossref","unstructured":"Pang, Y., Li, Z., Ju, H., Lu, H., Jia, W., Si, L., Guo, Y., Liu, Q., Li, S., and Liu, L. (2016). LiCHy: The CAF\u2019s LiDAR, CCD and hyperspectral integrated airborne observation system. Remote Sens., 8.","DOI":"10.3390\/rs8050398"},{"key":"ref_39","first-page":"14","article-title":"The comprehensive airborne remote sensing experiment in Saihanba forest farm","volume":"25","author":"Pang","year":"2021","journal-title":"J. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1016\/j.isprsjprs.2008.03.001","article-title":"Improved filtering parameter determination for the Goldstein radar interferogram filter","volume":"63","author":"Li","year":"2008","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1364\/JOSAA.18.000338","article-title":"Two-dimensional phase unwrapping with use of statistical models for cost functions in nonlinear optimization","volume":"18","author":"Chen","year":"2001","journal-title":"JOSA A"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"3317","DOI":"10.1109\/TGRS.2007.900693","article-title":"TanDEM-X: A satellite formation for high-resolution SAR interferometry","volume":"45","author":"Krieger","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1016\/j.rse.2015.12.037","article-title":"SAR tomography for the retrieval of forest biomass and height: Cross-validation at two tropical forest sites in French Guiana","volume":"175","author":"Minh","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Li, W., Tong, Q., Xu, L., Ji, P., Dong, F., Yu, Y., Chen, J., Zhao, L., Zhang, L., and Xie, C. (2019, January 26\u201329). The P-band SAR Satellite: Opportunities and Challenges. Proceedings of the 2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR), Xiamen, China.","DOI":"10.1109\/APSAR46974.2019.9048581"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/13\/3070\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:38:42Z","timestamp":1760139522000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/13\/3070"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,26]]},"references-count":44,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2022,7]]}},"alternative-id":["rs14133070"],"URL":"https:\/\/doi.org\/10.3390\/rs14133070","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,26]]}}}