{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T07:03:55Z","timestamp":1773817435571,"version":"3.50.1"},"reference-count":71,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2020,3,19]],"date-time":"2020-03-19T00:00:00Z","timestamp":1584576000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000844","name":"European Space Agency","doi-asserted-by":"publisher","award":["4000119231"],"award-info":[{"award-number":["4000119231"]}],"id":[{"id":"10.13039\/501100000844","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>BIOMASS is ESA\u2019s seventh Earth Explorer mission, scheduled for launch in 2022. The satellite will be the first P-band SAR sensor in space and will be operated in fully polarimetric interferometric and tomographic modes. The mission aim is to map forest above-ground biomass (AGB), forest height (FH) and severe forest disturbance (FD) globally with a particular focus on tropical forests. This paper presents the algorithms developed to estimate these biophysical parameters from the BIOMASS level 1 SAR measurements and their implementation in the BIOMASS level 2 prototype processor with a focus on the AGB product. The AGB product retrieval uses a physically-based inversion model, using ground-canceled level 1 data as input. The FH product retrieval applies a classical PolInSAR inversion, based on the Random Volume over Ground Model (RVOG). The FD product will provide an indication of where significant changes occurred within the forest, based on the statistical properties of SAR data. We test the AGB retrieval using modified airborne P-Band data from the AfriSAR and TropiSAR campaigns together with reference data from LiDAR-based AGB maps and plot-based ground measurements. For AGB estimation based on data from a single heading, comparison with reference data yields relative Root Mean Square Difference (RMSD) values mostly between 20% and 30%. Combining different headings in the estimation process significantly improves the AGB retrieval to slightly less than 20%. The experimental results indicate that the implemented retrieval scheme provides robust results that are within mission requirements.<\/jats:p>","DOI":"10.3390\/rs12060985","type":"journal-article","created":{"date-parts":[[2020,3,19]],"date-time":"2020-03-19T10:01:35Z","timestamp":1584612095000},"page":"985","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["The BIOMASS Level 2 Prototype Processor: Design and Experimental Results of Above-Ground Biomass Estimation"],"prefix":"10.3390","volume":"12","author":[{"given":"Francesco","family":"Banda","sequence":"first","affiliation":[{"name":"Aresys, 20132 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4227-1565","authenticated-orcid":false,"given":"Davide","family":"Giudici","sequence":"additional","affiliation":[{"name":"Aresys, 20132 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thuy Le","family":"Le Toan","sequence":"additional","affiliation":[{"name":"Centre d\u2019Etudes Spatiales de la Biosph\u00e8re, 31400 Toulouse, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1228-9839","authenticated-orcid":false,"given":"Mauro Mariotti","family":"Mariotti d\u2019Alessandro","sequence":"additional","affiliation":[{"name":"Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5736-0379","authenticated-orcid":false,"given":"Kostas","family":"Papathanassiou","sequence":"additional","affiliation":[{"name":"German Aerospace Center (DLR), 82234 Wessling, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4452-4829","authenticated-orcid":false,"given":"Shaun","family":"Quegan","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, University of Sheffield, Sheffield S10 2TG, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guido","family":"Riembauer","sequence":"additional","affiliation":[{"name":"European Space Agency, 2201 AZ Noordwijk, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Klaus","family":"Scipal","sequence":"additional","affiliation":[{"name":"European Space Agency, 2201 AZ Noordwijk, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4683-3142","authenticated-orcid":false,"given":"Maciej","family":"Soja","sequence":"additional","affiliation":[{"name":"MJ Soja Consulting, Hobart, 7000 Tasmania, Australia"},{"name":"School of Technology, University of Tasmania, Environments and Design, Hobart, 7000 Tasmania, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefano","family":"Tebaldini","sequence":"additional","affiliation":[{"name":"Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5757-9517","authenticated-orcid":false,"given":"Lars","family":"Ulander","sequence":"additional","affiliation":[{"name":"Department of Space, Earth and Environment, Chalmers University of Technology, S-412 96 Gothenburg, Sweden"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ludovic","family":"Villard","sequence":"additional","affiliation":[{"name":"Centre d\u2019Etudes Spatiales de la Biosph\u00e8re, 31400 Toulouse, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1007\/s10712-019-09551-x","article-title":"Aspects of Forest Biomass in the Earth System: Its Role and Major Unknowns","volume":"40","author":"Reichstein","year":"2019","journal-title":"Surv. Geophys."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1783","DOI":"10.5194\/essd-11-1783-2019","article-title":"Global Carbon Budget 2019","volume":"11","author":"Friedlingstein","year":"2019","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_3","unstructured":"ESA (2012). BIOMASS\u2014Report for Mission Selection\u2014An Earth Explorer to Observe Forest Biomass, European Space Agency. SP-1324\/1."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.rse.2019.03.032","article-title":"The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space","volume":"227","author":"Quegan","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"231","DOI":"10.4155\/cmt.11.18","article-title":"Advances in remote sensing technology and implications for measuring and monitoring forest carbon stocks and change","volume":"2","author":"Goetz","year":"2011","journal-title":"Carbon Manag."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"735","DOI":"10.1007\/s10712-019-09506-2","article-title":"Understanding the Land Carbon Cycle with Space Data: Current Status and Prospects","volume":"40","author":"Exbrayat","year":"2019","journal-title":"Surv. Geophys."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"9899","DOI":"10.1073\/pnas.1019576108","article-title":"Benchmark map of forest carbon stocks in tropical regions across three continents","volume":"108","author":"Saatchi","year":"2011","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1016\/j.rse.2010.09.018","article-title":"Retrieval of growing stock volume in boreal forest using hyper-temporal series of Envisat ASAR ScanSAR backscatter measurements","volume":"115","author":"Santoro","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"757","DOI":"10.1007\/s10712-019-09510-6","article-title":"The Role and Need for Space-Based Forest Biomass-Related Measurements in Environmental Management and Policy","volume":"40","author":"Herold","year":"2019","journal-title":"Surv. Geophys."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2832","DOI":"10.1109\/TGRS.2015.2506399","article-title":"Single and Multipolarimetric P-Band SAR Tomography of Subsurface Ice Structure","volume":"54","author":"Banda","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Banda, F., Giudici, D., Quegan, S., and Scipal, K. (2018, January 22\u201327). The Retrieval Concept of the Biomass Forest Biomass Prototype Processor. Proceedings of the IGARSS 2018\u20142018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8518434"},{"key":"ref_12","unstructured":"ESA (2015). Biomass Mission Requirements Document, European Space Agency. EOP-SM\/1645."},{"key":"ref_13","unstructured":"FAO (2009). Assessment of the Status of the Development of the Standards for the Terrestrial Essential Climate Variables, GTOS Secretariat, UN Food and Agriculture Organisation."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Philip, M. (1994). Measuring Trees and Forests, CAB International. [2nd ed.].","DOI":"10.1079\/9780851988832.0000"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.rse.2017.05.003","article-title":"Coverage of high biomass forests by the ESA BIOMASS mission under defense restrictions","volume":"196","author":"Carreiras","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1856","DOI":"10.1109\/TGRS.2013.2255880","article-title":"Impacts of Ionospheric Scintillation on the BIOMASS P-Band Satellite SAR","volume":"52","author":"Rogers","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Quegan, S., Lomas, M., Papathanassiou, K.P., Kim, J., Tebaldini, S., Giudici, D., Scagliola, M., Guccione, P., Dall, J., and Dubois-Fenandez, P. (2018, January 22\u201327). Calibration Challenges for the Biomass P-Band SAR Instrument. Proceedings of the IGARSS 2018\u20142018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8518646"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2142","DOI":"10.1109\/36.868873","article-title":"First demonstration of airborne SAR tomography using multibaseline L-band data","volume":"38","author":"Reigber","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1297","DOI":"10.1109\/LGRS.2015.2394235","article-title":"The Impact of Temporal Decorrelation on BIOMASS Tomography of Tropical Forests","volume":"12","author":"Tebaldini","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"967","DOI":"10.1109\/TGRS.2013.2246170","article-title":"Relating P-Band Synthetic Aperture Radar Tomography to Tropical Forest Biomass","volume":"52","author":"Rocca","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1109\/JSTARS.2014.2359231","article-title":"Relating P-Band SAR Intensity to Biomass for Tropical Dense Forests in Hilly Terrain: \u03b30 or t0?","volume":"8","author":"Villard","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2646","DOI":"10.1109\/TGRS.2012.2219538","article-title":"Regression-Based Retrieval of Boreal Forest Biomass in Sloping Terrain Using P-Band SAR Backscatter Intensity Data","volume":"51","author":"Soja","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1718","DOI":"10.1109\/TGRS.2014.2346656","article-title":"Soil Moisture Estimation Under Tropical Forests Using UHF Radar Polarimetry","volume":"53","author":"Saatchi","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3177","DOI":"10.1111\/gcb.12629","article-title":"Improved allometric models to estimate the aboveground biomass of tropical trees","volume":"20","author":"Chave","year":"2014","journal-title":"Glob. Chang. Biol."},{"key":"ref_25","unstructured":"Lee, J.S. (2009). and Pottier, E.. Polarimetric Radar Imaging: From Basics to Applications, CRC Press. [1st ed.]."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Brandl, S., Mette, T., Falk, W., Vallet, P., R\u00f6tzer, T., and Pretzsch, H. (2018). Static site indices from different national forest inventories: harmonization and prediction from site conditions. Ann. For. Sci., 75.","DOI":"10.1007\/s13595-018-0737-3"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3462","DOI":"10.1109\/TGRS.2018.2885057","article-title":"Multispectral Airborne LiDAR Data in the Prediction of Boreal Tree Species Composition","volume":"57","author":"Kukkonen","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1721","DOI":"10.3390\/f6051721","article-title":"A Benchmark of Lidar-Based Single Tree Detection Methods Using Heterogeneous Forest Data from the Alpine Space","volume":"6","author":"Eysn","year":"2015","journal-title":"Forests"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3377","DOI":"10.5194\/bg-15-3377-2018","article-title":"Canopy area of large trees explains aboveground biomass variations across neotropical forest landscapes","volume":"15","author":"Meyer","year":"2018","journal-title":"Biogeosciences"},{"key":"ref_30","unstructured":"Tang, S. (2017). Quantifying Differences in Forest Structures with Quantitative Structure Models from TLS Data. [Master\u2019s Thesis, UCL]."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Saatchi, S., Ramachandran, N., Tebaldini, S., Quegan, S., Le Toan, T., Papathanassiou, K., Chave, J., Shugart, H., Jeffery, K., and White, L. (August, January 28). Estimation of Tropical Forest Structure and Biomass from Airborne P-band Backscatter and TomoSAR Measurements. Proceedings of the IGARSS 2019\u20142019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan.","DOI":"10.1109\/IGARSS.2019.8898797"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"4430","DOI":"10.1109\/TGRS.2013.2246573","article-title":"Phenomenology of Ground Scattering in a Tropical Forest Through Polarimetric Synthetic Aperture Radar Tomography","volume":"51","author":"Tebaldini","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_33","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_34","doi-asserted-by":"crossref","first-page":"4132","DOI":"10.1109\/TGRS.2009.2023785","article-title":"Algebraic Synthesis of Forest Scenarios From Multibaseline PolInSAR Data","volume":"47","author":"Tebaldini","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_35","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":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Banda, F., Mariotti d\u2019Alessandro, M., and Tebaldini, S. (2020). Ground and Volume Decomposition as a Proxy for AGB from P-Band SAR Data. Remote Sens., 12.","DOI":"10.3390\/rs12020240"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Mariotti d\u2019Alessandro, M., Tebaldini, S., Quegan, S., Soja, M., and Ulander, L.M.H. (2018, January 22\u201327). Interferometric Ground Notching of SAR Images for Estimating Forest Above Ground Biomass. Proceedings of the IGARSS 2018\u20142018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8517706"},{"key":"ref_38","unstructured":"Mancon, S., Giudici, D., and Tebaldini, S. (2018, January 4\u20137). The ionospheric effects mitigation in the BIOMASS mission exploiting multi-squint coherence supported by Faraday rotation. Proceedings of the EUSAR 2018, 12th European Conference on Synthetic Aperture Radar, Aachen, Germany."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1775","DOI":"10.1109\/TGRS.2015.2488358","article-title":"Phase Calibration of Airborne Tomographic SAR Data via Phase Center Double Localization","volume":"54","author":"Tebaldini","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1109\/5.838084","article-title":"Synthetic aperture radar interferometry","volume":"88","author":"Rosen","year":"2000","journal-title":"Proc. IEEE"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"3081","DOI":"10.1109\/TGRS.2011.2120616","article-title":"Flattening Gamma: Radiometric Terrain Correction for SAR Imagery","volume":"49","author":"Small","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"3347","DOI":"10.1109\/JSTARS.2015.2431433","article-title":"Framework for Fusion of Ascending and Descending Pass TanDEM-X Raw DEMs","volume":"8","author":"Deo","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Mariotti d\u2019Alessandro, M., and Tebaldini, S. (2019). Digital Terrain Model Retrieval in Tropical Forests Through P-Band SAR Tomography. IEEE Trans. Geosci. Remote Sens.","DOI":"10.1109\/TGRS.2019.2908517"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Soja, M.J., Mariotti d\u2019Alessandro, M., Quegan, S., Tebaldini, S., and Ulander, L.M.H. (2018, January 22\u201327). Model-Based Estimation of Tropical Forest Biomass from Notch-Filtered P-Band Sar Backscatter. Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8517614"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"863","DOI":"10.1007\/s10712-019-09528-w","article-title":"Ground Data are Essential for Biomass Remote Sensing Missions","volume":"40","author":"Chave","year":"2019","journal-title":"Surv. Geophys."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"3512","DOI":"10.1109\/JSTARS.2018.2816962","article-title":"Comparison of Small- and Large-Footprint Lidar Characterization of Tropical Forest Aboveground Structure and Biomass: A Case Study From Central Gabon","volume":"11","author":"Silva","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Rosen, P., Hensley, S., Shaffer, S., Edelstein, W., Kim, Y., Kumar, R., Misra, T., Bhan, R., and Sagi, R. (2017, January 23\u201328). The NASA-ISRO SAR (NISAR) mission dual-band radar instrument preliminary design. Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, USA.","DOI":"10.1109\/IGARSS.2017.8127836"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1126\/science.1244693","article-title":"High-Resolution Global Maps of 21st-Century Forest Cover Change","volume":"342","author":"Hansen","year":"2013","journal-title":"Science"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"3007","DOI":"10.1109\/TGRS.2015.2510160","article-title":"Determining the Points of Change in Time Series of Polarimetric SAR Data","volume":"54","author":"Conradsen","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1017","DOI":"10.1007\/s10712-019-09541-z","article-title":"A Joint ESA-NASA Multi-mission Algorithm and Analysis Platform (MAAP) for Biomass, NISAR, and GEDI","volume":"40","author":"Albinet","year":"2019","journal-title":"Surv. Geophys."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1115","DOI":"10.1109\/36.536527","article-title":"Radiometric Slope Correction of Synthetic-Aperture Radar Images","volume":"34","author":"Ulander","year":"1996","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.cageo.2014.07.005","article-title":"Optimisation of global grids for high-resolution remote sensing data","volume":"72","author":"Sabel","year":"2014","journal-title":"Comput. Geosci."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1791","DOI":"10.1109\/TGRS.2012.2205264","article-title":"Incidence Angle Normalization of Radar Backscatter Data","volume":"51","author":"Mladenova","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_54","unstructured":"Soja, M.J., Banda, F., Ulander, L.M.H., Mariotti d\u2019Alessandro, M., Tebaldini, S., Quegan, S., and Scipal, K. Above-Ground Biomass Estimation with ESA\u2019s 7th Earth Explorer Mission BIOMASS: Algorithm Basics and Performance over Tropical Forests, Remote Sens. Environ., in review."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"5294","DOI":"10.1109\/TGRS.2015.2420996","article-title":"Forest Height Estimation by Means of Pol-InSAR Data Inversion: The Role of the Vertical Wavenumber","volume":"53","author":"Kugler","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"855","DOI":"10.1109\/36.298013","article-title":"The wavenumber shift in SAR interferometry","volume":"32","author":"Gatelli","year":"1994","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"965","DOI":"10.1109\/TGRS.2014.2331142","article-title":"Capabilities of BIOMASS Tomography for Investigating Tropical Forests","volume":"53","author":"Tebaldini","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_58","unstructured":"DLR, Aresys, and Politecnico di Milano (2019). BIOMASS DEM Product Prototype Processor Critical Review of CoSCS and DEM Algorithms, ESA, ESTEC."},{"key":"ref_59","unstructured":"Dixon, P.M. (2006). Bootstrap Resampling. Encyclopedia of Environmetrics, American Cancer Society."},{"key":"ref_60","unstructured":"Flores, A., Herndon, K., Thapa, R., and Cherrington, E. (2019). The SAR Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation, NASA Marshall Space Flight Center."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Mariotti d\u2019Alessandro, M., Tebaldini, S., Soja, M.J., Ulander, L.M.H., Quegan, S., and Scipal, K. (2020). Interferometric Ground Cancellation for Above Ground Biomass Estimation. IEEE Trans. Geosci. Remote Sens.","DOI":"10.1109\/TGRS.2020.2976854"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"3617","DOI":"10.1109\/JSTARS.2018.2851606","article-title":"In Situ Reference Datasets From the TropiSAR and AfriSAR Campaigns in Support of Upcoming Spaceborne Biomass Missions","volume":"11","author":"Tao","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Verdin, K.L., Godt, J.W., Funk, C., Pedreros, D., Worstell, B., and Verdin, J. (2007). Development of a Global Slope Dataset for Estimation of Landslide Occurence Resulting from Earthquakes, U.S. Geological Survey. U.S. Geological Survey, Open-File Report 2007-1188.","DOI":"10.3133\/ofr20071188"},{"key":"ref_64","unstructured":"Latham, J., Cumani, R., Rosati, I., and Bloise, M. (2014). FAO Global Land Cover (GLC-SHARE) Beta-Release 1.0 Database, Land and Water Division."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Simard, M., Naiara, P., Fisher, J., and Baccini, A. (2011). Mapping forest canopy height globally with spaceborne lidar. J. Geophys. Res., 116.","DOI":"10.1029\/2011JG001708"},{"key":"ref_66","unstructured":"FAO (2018). The Forest Resources Assessment Programme (FRA) 2020\u2014Terms and Definitions, FAO. FRA Working Paper 188."},{"key":"ref_67","first-page":"53","article-title":"Forest biomass retrieval approaches from earth observation in different biomes","volume":"77","author":"Quegan","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Santoro, M., and Cartus, O. (2018). Research Pathways of Forest Above-Ground Biomass Estimation Based on SAR Backscatter and Interferometric SAR Observations. Remote Sens., 10.","DOI":"10.3390\/rs10040608"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"3402","DOI":"10.1109\/JSTARS.2018.2859050","article-title":"Forest Structure Characterization From SAR Tomography at L-Band","volume":"11","author":"Tello","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"3505","DOI":"10.1109\/JSTARS.2018.2818796","article-title":"An Empirical Study on the Impact of Changing Weather Conditions on Repeat-Pass SAR Tomography","volume":"11","author":"Bai","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"3564","DOI":"10.1109\/JSTARS.2018.2814825","article-title":"Temporal Survey of P- and L-Band Polarimetric Backscatter in Boreal Forests","volume":"11","author":"Monteith","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/6\/985\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:09:39Z","timestamp":1760173779000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/6\/985"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,19]]},"references-count":71,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2020,3]]}},"alternative-id":["rs12060985"],"URL":"https:\/\/doi.org\/10.3390\/rs12060985","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3,19]]}}}