{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T05:13:04Z","timestamp":1780636384059,"version":"3.54.1"},"reference-count":76,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2020,4,26]],"date-time":"2020-04-26T00:00:00Z","timestamp":1587859200000},"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>An assessment of the National Aeronautics and Space Administration NASA\u2019s Cyclone Global Navigation Satellite System (CyGNSS) mission for biomass studies is presented in this work on rain, coniferous, dry, and moist tropical forests. The main objective is to investigate the capability of Global Navigation Satellite Systems Reflectometry (GNSS-R) for biomass retrieval over dense forest canopies from a space-borne platform. The potential advantage of CyGNSS, as compared to monostatic Synthetic Aperture Radar (SAR) missions, relies on the increasing signal attenuation by the vegetation cover, which gradually reduces the coherent scattering component \u03c3 coh , 0 . This term can only be collected in a bistatic radar geometry. This point motivates the study of the relationship between several observables derived from Delay Doppler Maps (DDMs) with Above-Ground Biomass (AGB). This assessment is performed at different elevation angles \u03b8 e as a function of Canopy Height (CH). The selected biomass products are obtained from data collected by the Geoscience Laser Altimeter System (GLAS) instrument on-board the Ice, Cloud, and land Elevation Satellite (ICESat-1). An analysis based on the first derivative of the experimentally derived polynomial fitting functions shows that the sensitivity requirements of the Trailing Edge TE and the reflectivity \u0393 reduce with increasing biomass up to ~ 350 and ~ 250 ton\/ha over the Congo and Amazon rainforests, respectively. The empirical relationship between TE and \u0393 with AGB is further evaluated at optimum angular ranges using Soil Moisture Active Passive (SMAP)-derived Vegetation Optical Depth ( VOD ), and the Polarization Index ( PI ). Additionally, the potential influence of Soil Moisture Content (SMC) is investigated over forests with low AGB.<\/jats:p>","DOI":"10.3390\/rs12091368","type":"journal-article","created":{"date-parts":[[2020,4,28]],"date-time":"2020-04-28T10:30:58Z","timestamp":1588069858000},"page":"1368","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":106,"title":["Above-Ground Biomass Retrieval over Tropical Forests: A Novel GNSS-R Approach with CyGNSS"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7775-7314","authenticated-orcid":false,"given":"Hugo","family":"Carreno-Luengo","sequence":"first","affiliation":[{"name":"Centre Tecn\u00f2logic de Telecomunicacions de Catalunya (CTTC\/CERCA), 08860 Barcelona, Spain"},{"name":"Climate and Space Sciences and Engineering Department, University of Michigan, 500 S. State Street, Ann Arbor, MI 48109, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8924-9029","authenticated-orcid":false,"given":"Guido","family":"Luzi","sequence":"additional","affiliation":[{"name":"Centre Tecn\u00f2logic de Telecomunicacions de Catalunya (CTTC\/CERCA), 08860 Barcelona, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michele","family":"Crosetto","sequence":"additional","affiliation":[{"name":"Centre Tecn\u00f2logic de Telecomunicacions de Catalunya (CTTC\/CERCA), 08860 Barcelona, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,4,26]]},"reference":[{"key":"ref_1","unstructured":"Barker, C., Barry, R., Brady, M., Brown, J., Christiansen, H., Cihlar, J., Clow, G., Csiszar, I., Dolman, H., and Famiglietti, J. (2008). Terrestrial Essential Climate Variables for Climate Assessment Mitigation and Adaptation, Food and Agriculture Organization (FAO) of the United Nations."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2009JG000935","article-title":"Importance of biomass in the global carbon cycle","volume":"114","author":"Houghton","year":"2009","journal-title":"J. Geophys. Res."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"013537","DOI":"10.1117\/1.2795724","article-title":"Revised method for forest canopy height estimation from geoscience laser altimeter system waveforms","volume":"1","author":"Lefsky","year":"2007","journal-title":"J. Appl. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3802","DOI":"10.1109\/JSTARS.2014.2353661","article-title":"Evaluation of ALOS\/PALSAR L-band data for the estimation of eucalyptus plantations aboveground biomass in Brazil","volume":"8","author":"Baghdadi","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2850","DOI":"10.1016\/j.rse.2011.03.020","article-title":"The BIOMASS mission: Mapping global forest biomass to better understand the terrestrial carbon cycle","volume":"115","author":"Quegan","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_6","unstructured":"Healey, S.P., Hernandez, M.W., Edwards, D.P., Lefsky, M.A., Freeman, E., Patterson, P.L., Lindquist, E.J., and Lister, A.J. (2015). CMS: GLAS LiDAR-derived Global Estimates of Forest Canopy Height, 2004\u20132008, ORNL DAAC."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Goncalves, F., Treuhaft, R., Law, B., Almeida, A., Walker, W., Baccini, A., dos Santos, J.R., and Graca, P. (2017). Estimating aboveground biomass in tropical forests: Field methods and error analysis for the calibration of remote sensing observations. Remote Sens., 9.","DOI":"10.3390\/rs9010047"},{"key":"ref_8","first-page":"331","article-title":"A passive reflectometry and interferometry system (PARIS): Application to ocean altimetry","volume":"17","year":"1993","journal-title":"ESA J."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1229","DOI":"10.1109\/TGRS.2017.2785343","article-title":"Revisiting the GNSS-R waveform statistics and its impact on altimetric retrievals","volume":"56","author":"Li","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"7-1","DOI":"10.1029\/2000RS002539","article-title":"First spaceborne observation of an earth-reflected GPS signal","volume":"37","author":"Lowe","year":"2002","journal-title":"Radio Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1229","DOI":"10.1109\/TGRS.2005.845643","article-title":"Detection and processing of bistatically reflected GPS signals from a low Earth orbit for the purpose of ocean remote sensing","volume":"43","author":"Gleason","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Unwin, M., Jales, P., Blunt, P., and Duncan, S. (2012, January 5\u20137). Preparation for the first flight of SSTL\u2019s next generation space GNSS receivers. Proceedings of the 6th ESA\/European Workshop Satellite NAVITEC GNSS Signals Signal Processor, Noordwijk, The Netherlands.","DOI":"10.1109\/NAVITEC.2012.6423101"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Carreno-Luengo, H., Lowe, S.T., Zuffada, C., Esterhuizen, S., and Oveisgharan, S. (2017). Spaceborne GNSS-R from the SMAP mission: First assessment of polarimetric scatterometry over land and cryosphere. Remote Sens., 9.","DOI":"10.3390\/rs9040362"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1175\/BAMS-D-14-00218.1","article-title":"New ocean winds satellite mission to probe hurricanes and tropical convection","volume":"97","author":"Ruf","year":"2015","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1109\/LGRS.2016.2636664","article-title":"Remote sensing of snow water equivalent using P-band coherent reflection","volume":"14","author":"Shah","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"8272","DOI":"10.1029\/2018GL078923","article-title":"Use of Cyclone Global Navigation Satellite System (CYGNSS) observations for estimation of soil moisture","volume":"45","author":"Kim","year":"2018","journal-title":"Geophys. Res. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1109\/JSTARS.2018.2856588","article-title":"Sensitivity of CyGNSS bistatic reflectivity and SMAP microwave radiometry brightness temperature to geophysical parameters over land surfaces","volume":"12","author":"Luzi","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Chew, C., Small, E., and Podest, E. (2018, January 22\u201327). Monitoring land surface hydrology using CyGNSS. Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8517971"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-018-27673-x","article-title":"CYGNSS data map flood inundation during the 2017 Atlantic hurricane season","volume":"8","author":"Chew","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Jensen, K., McDonald, K., Podest, E., Rodriguez-Alvarez, N., Horna, V., and Steiner, N. (2018). Assessing L-Band GNSS-Reflectometry and imaging radar for detecting sub-canopy inundation dynamics in a tropical wetlands complex. Remote Sens., 10.","DOI":"10.3390\/rs10091431"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"12065","DOI":"10.1029\/2019GL085134","article-title":"A CYGNSS-based algorithm for the detection of inland waterbodies","volume":"46","author":"Ruf","year":"2019","journal-title":"Geophys. Res. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Crespo, J.A., Posselt, D.J., and Asharaf, S. (2019). CYGNSS Surface Heat Flux Product Development. Remote Sens., 11.","DOI":"10.20944\/preprints201908.0250.v1"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2470","DOI":"10.1109\/TGRS.2005.853926","article-title":"Radiative transfer model for microwave bistatic scattering from forests canopies","volume":"43","author":"Liang","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1823","DOI":"10.1016\/j.asr.2010.04.025","article-title":"Forest biomass monitoring with GNSS-R: Theoretical simulations","volume":"47","author":"Ferrazzoli","year":"2011","journal-title":"Adv. Space Res."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"863","DOI":"10.1016\/j.asr.2014.02.007","article-title":"GPS-Reflectometry: Forest canopies polarization scattering properties and modelling","volume":"54","author":"Wu","year":"2014","journal-title":"Adv. Space Res."},{"key":"ref_26","first-page":"6542","article-title":"SAVERS: A simulator of GNSS reflections from bare soil and vegetated soils","volume":"52","author":"Pierdicca","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_27","unstructured":"Egido, A. (2013). GNSS Refectometry for Land Remote Sensing Applications. [Ph.D. Thesis, Universitat Politecnica de Catalunya (UPC)]."},{"key":"ref_28","first-page":"2652","article-title":"First results of a GNSS-R experiment from a stratospheric balloon over boreal forests","volume":"54","author":"Camps","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"13120","DOI":"10.3390\/rs71013120","article-title":"First polarimetric GNSS-R measurements from a stratospheric flight over boreal forests","volume":"7","author":"Vidal","year":"2015","journal-title":"Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1049","DOI":"10.1109\/TGRS.2018.2864631","article-title":"ScCoBi-Veg: A generalized bistatic scattering model of reflectometry from vegetation for signals of opportunity applications","volume":"57","author":"Kurum","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/S0022-5193(75)80051-8","article-title":"Developmental algorithms for multicellular organisms: A survey of L-systems","volume":"54","author":"Lindermayer","year":"1975","journal-title":"J. Theor. Bio."},{"key":"ref_32","unstructured":"Tsang, L., Kong, J.A., and Shin, R.T. (1985). Theory of Microwave Remote Sensing, Wiley Interscience."},{"key":"ref_33","first-page":"150","article-title":"Performance of GNSS-R GLORI data for biomass estimation over the Landes forests","volume":"74","author":"Zribi","year":"2019","journal-title":"Elsevier Int. J. Earth Obs. Geoinf."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Motte, E., Zribi, M., Fanise, P., Egido, A., Darrozes, J., Al-Yaari, A., Baghdadi, N., Baup, F., Dayau, S., and Fieuzal, R. (2016). GLORI: A GNSS-R dual polarization airborne instrument for land surface monitoring. Sensors, 16.","DOI":"10.3390\/s16050732"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Pierdicca, N., Mollfulleda, A., Constantini, F., Guerriero, L., Dente, L., Paloscia, S., Santi, E., and Zribi, M. (2018, January 22\u201327). Spaceborne GNSS Reflectometry data for land applications: An analysis of Techdemosat data. Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8517987"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Santi, E., Paloscia, S., Pettinato, S., Fontanelli, G., Clarizia, M.-P., Guerriero, L., and Pierdicca, N. (August, January 28). Forest biomass estimate on local and global scales through GNSS reflectometry techniques. Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan.","DOI":"10.1109\/IGARSS.2019.8899140"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1109\/JSTARS.2018.2885391","article-title":"Foreword to the special issue on Cyclone Global Navigation Satellite System (CYGNSS) early on orbit performance","volume":"12","author":"Ruf","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_38","unstructured":"CYGNSS (2019, May 11). CYGNSS Level 1 Science Data Record. Ver. 2.1. Available online: http:\/\/dx.doi.org\/10.5067\/CYGNS-L1X20."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1406","DOI":"10.1111\/gcb.13139","article-title":"An integrated pan-tropical biomass map using multiple reference datasets","volume":"2","author":"Avitabile","year":"2016","journal-title":"Glob. Chang. Biol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"951","DOI":"10.1109\/36.841977","article-title":"Scattering of GPS signals from the ocean with wind remote sensing applications","volume":"38","author":"Zavorotny","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Ulaby, F.T., and Long, D.G. (2014). Microwave Radar and Radiometric Remote Sensing, Univ, Michigan Press.","DOI":"10.3998\/0472119356"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Pierdicca, N., Guerriero, L., Brogioni, M., and Egido, A. (2012, January 22\u201327). On the coherent and non-coherent components of bare soil and vegetated terrain bistatic scattering: Modelling the GNSS-R signal over land. Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany.","DOI":"10.1109\/IGARSS.2012.6350689"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1959","DOI":"10.1109\/TGRS.2017.2771253","article-title":"Bistatic radar equation for signals of opportunity revisited","volume":"56","author":"Voronovich","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"954","DOI":"10.1002\/2013GL058725","article-title":"Sea surface topography retrieved from GNSS reflectometry phase data of the GEOHALO flight mission","volume":"41","author":"Semmling","year":"2014","journal-title":"Geophys. Res. Lett."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1560","DOI":"10.1109\/JSTARS.2014.2300232","article-title":"Cross-correlation waveform analysis for conventional and interferometric GNSS-R approaches","volume":"7","author":"Camps","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Carreno-Luengo, H., Luzi, G., and Crosetto, M. (2018). Impact of the elevation angle on CyGNSS GNSS-R bistatic reflectivity as a function of effective surface roughness over land surfaces. Remote Sens., 10.","DOI":"10.3390\/rs10111749"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Camps, A., Vall-llosera, M., Park, H., Portal, G., and Rossato, L. (2018). Sensitivity of TDS-1 reflectivity to soil moisture: Global and regional differences and impact of different spatial scales. Remote Sens., 10.","DOI":"10.3390\/rs10111856"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1109\/LGRS.2018.2878359","article-title":"Analysis of vegetation optical depth and soil moisture retrieval by SMOS over tropical forests","volume":"16","author":"Vittucci","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1016\/j.rse.2017.06.037","article-title":"L-band vegetation optical depth and effective scattering albedo estimation from SMAP","volume":"198","author":"Konings","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"767","DOI":"10.1002\/2015GL066624","article-title":"First spaceborne observation of sea surface heightusing GPS-Reflectometry","volume":"43","author":"Clarizia","year":"2016","journal-title":"AGU Geophys. Res. Lett."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"2227","DOI":"10.1109\/JSTARS.2019.2895510","article-title":"Analysis of CyGNSS data for soil moisture retrieval","volume":"12","author":"Clarizia","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1109\/JSTARS.2018.2867773","article-title":"Design and performance of a GPS constellation power monitor system for improved CYGNSS L1B calibration","volume":"12","author":"Wang","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1109\/JSTARS.2018.2849323","article-title":"An assessment of CYGNSS normalized bistatic radar cross section calibration","volume":"12","author":"Said","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"4322","DOI":"10.1109\/TGRS.2018.2890646","article-title":"Time-series retrieval of soil moisture using CYGNSS","volume":"57","author":"Johnson","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_55","unstructured":"Entekhabi, D., Yueh, S., O\u2019Neill, P.E., Kellogg, K.H., Allen, A., Bindlish, R., Brown, M., Chan, S., Colliander, A., and Crow, W.T. (2019, April 04). SMAP Handbook. Soil Moisture Active Passive. Available online: https:\/\/nsidc.org\/data\/SPL3SMP_E\/versions\/1."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"931","DOI":"10.1016\/j.rse.2017.08.025","article-title":"Development and assessment of the SMAP enhanced passive soil moisture product","volume":"204","author":"Chan","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_57","unstructured":"O\u2019Neill, P., Chan, S., Njoku, E., Jackson, T., and Bindlish, R. (2019, April 16). Soil Moisture Active Passive (SMAP) Algorithm Theoretical Basis Document Level 2 & 3 Soil Moisture (Passive) Data Products. Revision C. Available online: https:\/\/nsidc.org\/data\/SPL3SMP_E\/versions\/1."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"4627","DOI":"10.5194\/bg-15-4627-2018","article-title":"An evaluation of SMOS L-band vegetation optical depth (L-VOD) data sets: High sensitivity of L-VOD to aboveground biomass in Africa","volume":"15","author":"Mialon","year":"2018","journal-title":"Biogeosciences"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"S275","DOI":"10.1088\/0959-7174\/14\/2\/009","article-title":"Microwave radiometry of forests","volume":"14","author":"Pampaloni","year":"2004","journal-title":"Waves Random Media"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1109\/36.7687","article-title":"Microwave polarization index for monitoring vegetation growth","volume":"26","author":"Paloscia","year":"1988","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"3861","DOI":"10.1109\/JSTARS.2017.2703629","article-title":"Vegetation water content retrieval by means of multifrequency microwave acquisitions from AMSR2","volume":"10","author":"Santi","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Paloscia, S., Pampaloni, P., and Santi, E. (2018). Radiometric microwave indices for remote sensing of land surfaces. Remote Sens., 10.","DOI":"10.3390\/rs10121859"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Carreno-Luengo, H., Luzi, G., and Crosetto, M. (2019). First evaluation of topography on GNSS-R: An empirical study based on a digital elevation model. Remote Sens., 11.","DOI":"10.3390\/rs11212556"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"180040","DOI":"10.1038\/sdata.2018.40","article-title":"A suite of global cross-scale topographic variables for environmental and biodiversity modelling","volume":"5","author":"Amatulli","year":"2018","journal-title":"Nat. Sci. Data"},{"key":"ref_65","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?","volume":"8","author":"Villard","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_66","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":"Natl. Acad. Sci. USA"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1038\/nclimate1354","article-title":"Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps","volume":"2","author":"Baccini","year":"2012","journal-title":"Nat. Clim. Chang."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Yu, Y., and Saatchi, S. (2016). Sensitivity of L-band SAR backscatter to aboveground biomass of global forests. Remote Sens., 8.","DOI":"10.3390\/rs8060522"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"D\u2019Addio, S., Buck, C., and Martin-Neira, M. (2008, January 7\u201311). PARIS altimetry precision prediction with Galileo signals-in-space. Proceedings of the2008 IEEE International Geoscience and Remote Sensing Symposium, Boston, MA, USA.","DOI":"10.1109\/IGARSS.2008.4779283"},{"key":"ref_70","first-page":"151","article-title":"Vegetation optical depth at L-band and above ground biomass in the tropical range: Evaluating their relationships at continental and regional scales","volume":"19","author":"Vittucci","year":"2019","journal-title":"Elsevier Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_71","unstructured":"Newman, A. (2000). Tropical Rainforest: Our Most Valuable and Endangered Habitat with a Blueprint for Its Survival into the Third Millennium, Checkmark Books. [2nd ed.]."},{"key":"ref_72","unstructured":"(2019, January 02). Dryland and Dryland with Forests, Available online: https:\/\/earthobservatory.nasa.gov\/IOTD\/view.php?id=90635."},{"key":"ref_73","unstructured":"(2020, January 01). Tropical and Subtropical Coniferous Forests. Available online: https:\/\/www.worldwildlife.org\/biomes\/tropical-and-subtropical-coniferous-forests."},{"key":"ref_74","unstructured":"(2020, January 20). Tropical and Subtropical Dry Broadleaf Forest Ecoregions. Available online: https:\/\/web.archive.org\/web\/20120425205410\/http:\/\/wwf.panda.org\/about_our_earth\/ecoregions\/about\/habitat_types\/selecting_terrestrial_ecoregions\/habitat02.cfm."},{"key":"ref_75","unstructured":"(2020, January 20). The Congo Basin Forest. Available online: https:\/\/globalforestatlas.yale.edu\/region\/congo."},{"key":"ref_76","unstructured":"(2020, January 20). The Amazon Basin Forest. Available online: https:\/\/globalforestatlas.yale.edu\/region\/amazon."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/9\/1368\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:32:03Z","timestamp":1760362323000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/9\/1368"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,26]]},"references-count":76,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2020,5]]}},"alternative-id":["rs12091368"],"URL":"https:\/\/doi.org\/10.3390\/rs12091368","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4,26]]}}}