{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T13:54:55Z","timestamp":1783691695235,"version":"3.55.0"},"reference-count":67,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2019,4,10]],"date-time":"2019-04-10T00:00:00Z","timestamp":1554854400000},"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>Knowledge of the aboveground biomass (AGB) of large pasture fields is invaluable as it assists graziers to set stocking rate. In this preliminary evaluation, we investigated the response of Sentinel-1 (S1) Synthetic Aperture Radar (SAR) data to biophysical variables (leaf area index, height and AGB) for native pasture grasses on a hilly, pastoral farm. The S1 polarimetric parameters such as backscattering coefficients, scattering entropy, scattering anisotropy, and mean scattering angle were regressed against the widely used morphological parameters of leaf area index (LAI) and height, as well as AGB of pasture grasses. We found S1 data to be more responsive to the pasture parameters when using a 1 m digital elevation model (DEM) to orthorectify the SAR image than when we employed the often-used Shuttle Radar Topography 30 m and 90 m Missions. With the 1m DEM analysis, a significant quadratic relationship was observed between AGB and VH cross-polarisation (R2 = 0.71), and significant exponential relationships between polarimetric entropy and LAI and AGB (R2 = 0.53 and 0.45, respectively). Similarly, the mean scattering angle showed a significant exponential relationship with LAI and AGB (R2 = 0.58 and R2 = 0.83, respectively). The study also found a significant quadratic relationship between the mean scattering angle and pasture height (R2 = 0.72). Despite a relatively small dataset and single season, the mean scattering angle in conjunction with a generalised additive model (GAM) explained 73% of variance in the AGB estimates. The GAM model estimated AGB with a root mean square error of 392 kg\/ha over a range in pasture AGB of 443 kg\/ha to 2642 kg\/ha with pasture LAI ranging from 0.27 to 1.87 and height 3.25 cm to 13.75 cm. These performance metrics, while indicative at best owing to the limited datasets used, are nonetheless encouraging in terms of the application of S1 data to evaluating pasture parameters under conditions which may preclude use of traditional optical remote sensing systems.<\/jats:p>","DOI":"10.3390\/rs11070872","type":"journal-article","created":{"date-parts":[[2019,4,10]],"date-time":"2019-04-10T11:25:08Z","timestamp":1554895508000},"page":"872","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["A Preliminary Investigation of the Potential of Sentinel-1 Radar to Estimate Pasture Biomass in a Grazed Pasture Landscape"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3301-7063","authenticated-orcid":false,"given":"Richard Azu","family":"Crabbe","sequence":"first","affiliation":[{"name":"Precision Agriculture Research Group; University of New England, Armidale, NSW 2351, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David William","family":"Lamb","sequence":"additional","affiliation":[{"name":"Precision Agriculture Research Group; University of New England, Armidale, NSW 2351, Australia"},{"name":"Food Agility Cooperative Research Centre, University of New England, Armidale, NSW 2351, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Clare","family":"Edwards","sequence":"additional","affiliation":[{"name":"Precision Agriculture Research Group; University of New England, Armidale, NSW 2351, Australia"},{"name":"Central Tablelands Local Land Services, Mudgee, NSW 2850, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3101-5462","authenticated-orcid":false,"given":"Karl","family":"Andersson","sequence":"additional","affiliation":[{"name":"Precision Agriculture Research Group; University of New England, Armidale, NSW 2351, Australia"},{"name":"Food Agility Cooperative Research Centre, University of New England, Armidale, NSW 2351, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1897-4175","authenticated-orcid":false,"given":"Derek","family":"Schneider","sequence":"additional","affiliation":[{"name":"Precision Agriculture Research Group; University of New England, Armidale, NSW 2351, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,4,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"796","DOI":"10.1071\/AN11174","article-title":"Optimising pasture and grazing management decisions on the Cicerone Project farmlets over variable time horizons","volume":"53","author":"Behrendt","year":"2013","journal-title":"Anim. Prod. Sci."},{"key":"ref_2","unstructured":"Gherardi, S., Anderton, L., Sneddon, J., Oldham, C., and Mata, G. (2004, January 18\u201322). Pastures from space\u2013the value to Australian sheep producers of satellite-based pasture information. Proceedings of the 12th Australasian Remote Sensing and Photogrammetry Conference, Freemantle, WA, Australia."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/j.compag.2017.01.029","article-title":"PastureBase Ireland: A grassland decision support system and national database","volume":"136","author":"Hanrahan","year":"2017","journal-title":"Comput. Electron. Agric."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"754","DOI":"10.1017\/S2040470017000838","article-title":"Estimating pasture biomass with active optical sensors","volume":"8","author":"Andersson","year":"2017","journal-title":"Adv. Anim. Biosci."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Schaefer, M.T., and Lamb, D.W. (2016). A combination of plant NDVI and LiDAR measurements improve the estimation of pasture biomass in tall fescue (Festuca arundinacea var. Fletcher). Remote Sens., 8.","DOI":"10.3390\/rs8020109"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1071\/CP10019","article-title":"Evaluating an active optical sensor for quantifying and mapping green herbage mass and growth in a perennial grass pasture","volume":"61","author":"Trotter","year":"2010","journal-title":"Crop Pasture Sci."},{"key":"ref_7","unstructured":"Clarke, D., Litherland, A., Mata, G., and Burling-Claridge, R. (2006, January 26\u201328). Pasture Monitoring from Space. Proceedings of the South Island Dairy Event Conference, Invercargill, New Zealand."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2699","DOI":"10.1080\/01431161003743181","article-title":"Quantitative mapping of pasture biomass using satellite imagery","volume":"32","author":"Edirisinghe","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_9","first-page":"184","article-title":"Estimating above-ground biomass on mountain meadows and pastures through remote sensing","volume":"38","author":"Barrachina","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Sibanda, M., Mutanga, O., Rouget, M., and Kumar, L. (2017). Estimating biomass of native grass grown under complex management treatments using WorldView-3 spectral derivatives. Remote Sens., 9.","DOI":"10.3390\/rs9010055"},{"key":"ref_11","first-page":"43","article-title":"Monitoring grass nutrients and biomass as indicators of rangeland quality and quantity using random forest modelling and WorldView-2 data","volume":"43","author":"Ramoelo","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3619","DOI":"10.1080\/01431160110114529","article-title":"Estimating leaf nitrogen concentration in ryegrass (Lolium spp.) pasture using the chlorophyll red-edge: theoretical modelling and experimental observations","volume":"23","author":"Lamb","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_13","first-page":"88","article-title":"Evaluating the relationship between biomass, percent groundcover and remote sensing indices across six winter cover crop fields in Maryland, United States","volume":"39","author":"Prabhakara","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"300","DOI":"10.2134\/agronj1984.00021962007600020029x","article-title":"Estimating Absorbed Photosynthetic Radiation and Leaf Area Index from Spectral Reflectance in Wheat 1","volume":"76","author":"Asrar","year":"1984","journal-title":"Agron. J."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"752","DOI":"10.2134\/agronj1986.00021962007800040039x","article-title":"Techniques for Measuring Intercepted and Absorbed Photosynthetically Active Radiation in Corn Canopies 1","volume":"78","author":"Gallo","year":"1986","journal-title":"Agron. J."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"970","DOI":"10.1109\/PROC.1985.13230","article-title":"Microwave remote sensing from space","volume":"73","author":"Carver","year":"1985","journal-title":"Proc. IEEE"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1109\/MGRS.2013.2248301","article-title":"A tutorial on synthetic aperture radar","volume":"1","author":"Moreira","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_18","first-page":"13","article-title":"A review on biomass estimation methods using synthetic aperture radar data","volume":"1","author":"Ghasemi","year":"2011","journal-title":"Int. J. Geomat. Geosci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3611","DOI":"10.3390\/rs5073611","article-title":"Pasture Monitoring Using SAR with COSMO-SkyMed, ENVISAT ASAR, and ALOS PALSAR in Otway, Australia","volume":"5","author":"Wang","year":"2013","journal-title":"Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"25481","DOI":"10.1029\/95JD00852","article-title":"Estimation of canopy water content in Konza Prairie grasslands using synthetic aperture radar measurements during FIFE","volume":"100","author":"Saatchi","year":"1995","journal-title":"J. Geophys. Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/0034-4257(90)90102-R","article-title":"Ground-based X-band (3-cm wave) radar backscattering of agricultural crops. II. Wheat, barley, and oats; the impact of canopy structure","volume":"34","author":"Bouman","year":"1990","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"737","DOI":"10.5194\/isprsarchives-XL-8-737-2014","article-title":"Role of Polarimetric SAR data for discrimination\/biophysical parameters of crops based on canopy architecture","volume":"XL\u20138","author":"Haldar","year":"2014","journal-title":"ISPRS-Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1016\/0098-3004(94)00095-C","article-title":"Topographic dependence of synthetic aperture radar imagery","volume":"21","author":"Franklin","year":"1995","journal-title":"Comput. Geosci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3075","DOI":"10.1080\/014311698214190","article-title":"Effect of digital elevation model on topographic correction of airborne SAR","volume":"19","author":"Goyal","year":"1998","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1109\/36.3012","article-title":"Radiometric correction of C-band imagery for topographic effects in regions of moderate relief","volume":"26","author":"Hinse","year":"1988","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3553","DOI":"10.1080\/01431160010007060","article-title":"A simple method to account for topography in the radiometric correction of radar imagery","volume":"22","author":"Leclerc","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_27","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_28","doi-asserted-by":"crossref","first-page":"1036","DOI":"10.1109\/36.263774","article-title":"The effect of topography on SAR calibration","volume":"31","author":"Chapman","year":"1993","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"661","DOI":"10.3390\/rs4030661","article-title":"The influence of DEM quality on mapping accuracy of coniferous- and deciduous-dominated forest using TerraSAR-X images","volume":"4","author":"Ortiz","year":"2012","journal-title":"Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1109\/JSTARS.2010.2072984","article-title":"Orthorectification and slope correction of SAR data using DEM and its accuracy evaluation","volume":"3","author":"Shimada","year":"2010","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1893","DOI":"10.1080\/0143116031000101611","article-title":"Geometric processing of remote sensing images: models, algorithms and methods","volume":"25","author":"Toutin","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1109\/JSTARS.2010.2077619","article-title":"Generating large-scale high-quality SAR mosaic datasets: application to PALSAR Data for global monitoring","volume":"3","author":"Shimada","year":"2010","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"McNeill, S.J., Pairman, D., Belliss, S.E., Dalley, D., and Dynes, R. (2010). Robust Estimation of Pasture Biomass Using Dual-polarisation TerrASAR-X Imagery, IEEE.","DOI":"10.1109\/IGARSS.2010.5649266"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1080\/07038992.2017.1394181","article-title":"Can polarimetric RADARSAT-2 images provide a solution to quantify non-photosynthetic vegetation biomass in semi-arid mixed grassland?","volume":"43","author":"Li","year":"2017","journal-title":"Can. J. Remote Sens."},{"key":"ref_35","unstructured":"(2017, May 03). ESA, Sentinel-1 Team Sentinel-1 User Handbook 2013. Available online: https:\/\/sentinel.esa.int."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Isbell, R. (2016). The Australian Soil Classification, CSIRO Publishing.","DOI":"10.1071\/9781486304646"},{"key":"ref_37","unstructured":"(2018, October 21). BoM Climate statistics for Australian locations, Available online: http:\/\/www.bom.gov.au\/climate\/averages\/tables\/cw_056037_All.shtml."},{"key":"ref_38","unstructured":"Oliveira, D., Medeiros, S., Aroeira, L., Barioni, L., and Lana, D. (2001, January 11\u201321). Estimating herbage mass in stargrass (Cynodon nlenfuensis var nlenfuensis) using sward surface height and the rising plate meter. Proceedings of the XIX International Grassland Congress: Grassland Ecosystems: An outlook into the 21st century, Sao Pedro, Brazil."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"475","DOI":"10.2307\/3899458","article-title":"A rising plate meter for estimating production and utilization","volume":"39","author":"Scrivner","year":"1986","journal-title":"J. Range Manag."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1109\/36.134089","article-title":"Relating forest biomass to SAR data","volume":"30","author":"Beaudoin","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1109\/36.485127","article-title":"A review of target decomposition theorems in radar polarimetry","volume":"34","author":"Cloude","year":"1996","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1109\/36.551935","article-title":"An entropy based classification scheme for land applications of polarimetric SAR","volume":"35","author":"Cloude","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","unstructured":"Cloude, S. (2007, January January). The Dual Polarization Entropy\/Alpha Decomposition: A PALSAR Case Study. Proceedings of the 3rd International Workshop on Science and Applications of SAR Polarimetry and Polarimetric Interferometry Conference, Frascati, Italy."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2233","DOI":"10.1109\/JSTARS.2016.2570427","article-title":"A Modified H\u2212\u03b1 Classification Method for DCP Compact Polarimetric Mode by Reconstructing Quad H and \u03b1 Parameters From Dual Ones","volume":"9","author":"Ghods","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"7447","DOI":"10.3390\/rs70607447","article-title":"Scattering Mechanism Extraction by a Modified Cloude-Pottier Decomposition for Dual Polarization SAR","volume":"7","author":"Ji","year":"2015","journal-title":"Remote Sens."},{"key":"ref_46","unstructured":"Lee, J.-S., and Pottier, E. (2009). Polarimetric Radar Imaging: From Basics to Applications, CRC Press. Optical Science and Engineering."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"879","DOI":"10.1016\/j.asr.2017.05.034","article-title":"Sentinel-1A\u2013First precise orbit determination results","volume":"60","author":"Peter","year":"2017","journal-title":"Adv. Space Res."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"3875","DOI":"10.1080\/01431161003786016","article-title":"SRTM DEM and its application advances","volume":"32","author":"Yang","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Verma, N., Lamb, D., Reid, N., and Wilson, B. (2016). Comparison of Canopy Volume Measurements of Scattered Eucalypt Farm Trees Derived from High Spatial Resolution Imagery and LiDAR. Remote Sens., 8.","DOI":"10.3390\/rs8050388"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"380","DOI":"10.1016\/S0146-664X(81)80018-4","article-title":"Refined filtering of image noise using local statistics","volume":"15","author":"Lee","year":"1981","journal-title":"Comput. Graph. Image Process."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Yommy, A.S., Liu, R., and Wu, A.S. (2015, January 26\u201327). SAR Image Despeckling Using Refined Lee Filter. Proceedings of the 2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics, Hangzhou, China.","DOI":"10.1109\/IHMSC.2015.236"},{"key":"ref_52","unstructured":"Parisi, J.F., and Ustin, S.L. (1990, January 15\u201318). Quantitative estimation of standing biomass from L-band multipolarization data. Proceedings of the 10th Annual International Symposium on Geoscience and Remote Sensing, College Park, MD, USA."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/0034-4257(94)90142-2","article-title":"Radar remote sensing of forest and wetland ecosystems in the Central American tropics","volume":"48","author":"Pope","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1109\/36.134086","article-title":"An empirical model and an inversion technique for radar scattering from bare soil surfaces","volume":"30","author":"Oh","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1080\/10106040701538157","article-title":"Retrieval of surface roughness using multi-polarized Envisat-1 ASAR data","volume":"23","author":"Srivastava","year":"2008","journal-title":"Geocarto Int."},{"key":"ref_56","unstructured":"Veci, L., Prats-Iraola, P., Scheiber, R., Collard, F., Fomferra, N., and Engdahl, M. (2012, January 14\u201318). The Sentinel-1 Toolbox; 2014. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Quebec, QC, Canada."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"587","DOI":"10.2307\/3236170","article-title":"Generalized additive models in plant ecology","volume":"2","author":"Yee","year":"1991","journal-title":"J. Veg. Sci."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Breusch, T.S., and Pagan, A.R. (1979). A simple test for heteroscedasticity and random coefficient variation. Econom. J. Econom. Soc., 1287\u20131294.","DOI":"10.2307\/1911963"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"384","DOI":"10.1080\/22797254.2017.1336067","article-title":"de la Comparison of regression models to estimate biomass losses and CO2 emissions using low-density airborne laser scanning data in a burnt Aleppo pine forest","volume":"50","author":"Domingo","year":"2017","journal-title":"Eur. J. Remote Sens."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Meng, B., Ge, J., Liang, T., Yang, S., Gao, J., Feng, Q., Cui, X., Huang, X., and Xie, H. (2017). Evaluation of Remote Sensing Inversion Error for the Above-Ground Biomass of Alpine Meadow Grassland Based on Multi-Source Satellite Data. Remote Sens., 9.","DOI":"10.3390\/rs9040372"},{"key":"ref_61","unstructured":"(2018). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1548","DOI":"10.1080\/01621459.2016.1180986","article-title":"Smoothing Parameter and Model Selection for General Smooth Models","volume":"111","author":"Wood","year":"2016","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_63","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_64","unstructured":"Henderson, F.M., and Lewis, A.J. (1998). Principles and Applications of Imaging Radar. Manual of Remote Sensing, John Wiley & Sons. [3rd ed.]."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1080\/01431160500214050","article-title":"Comparative evaluation of the sensitivity of multi-polarized multi-frequency SAR backscatter to plant density","volume":"27","author":"Patel","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0034-4257(96)00121-6","article-title":"A study of the relationship between radar backscatter and regenerating tropical forest biomass for spaceborne SAR instruments","volume":"60","author":"Luckman","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Freeman, A., and Durden, S.L. (1993, January 12). Three-component scattering model to describe polarimetric SAR data. Proceedings of the Radar Polarimetry, San Diego, CA, USA.","DOI":"10.1117\/12.140618"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/7\/872\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:44:27Z","timestamp":1760186667000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/7\/872"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,10]]},"references-count":67,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2019,4]]}},"alternative-id":["rs11070872"],"URL":"https:\/\/doi.org\/10.3390\/rs11070872","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,10]]}}}