{"id":59,"date":"2022-06-11T10:01:57","date_gmt":"2022-06-11T09:01:57","guid":{"rendered":"https:\/\/rainfor.org\/?page_id=59"},"modified":"2026-03-03T16:51:00","modified_gmt":"2026-03-03T16:51:00","slug":"publications","status":"publish","type":"page","link":"https:\/\/rainfor.org\/en\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"\n

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Carreiras J M B; Higginbottom T; Godlee J L; Harrison S; Benitez L; Mograbi P J; Levesley A; Melga\u00e7o K; Milodowski D; Pickavance G; Wells G; Oliveira E A; Arroyo L; Bowers S; Brienen R J W; Cardoso D; Castro A A J F; Chavez E; Coutinho \u00cd A C; Domingues T F; Elias F; Santo M M E; Feldpausch T R; Galbraith D; Gloor E; Gon\u00e7alves F M P; Gotore T; Ishida F Y; Killeen T J; Malhi Y; Marimon B S; Marimon-J\u00fanior B H; Ramos D M; Reis S M A; McNicol I; Mitchard E T A; Moonlight P; Morandi P S; Morellato P; Muchawona A; Muledi J; Murakami A; Shutcha M N; Nieto-Quintano P; Parada-Gutierrez A; Prestes N C C S; Queiroz L P; Rodrigues P M S; Silva J O; Santos R M; S\u00e4rkinen T; Silva D F P F; Oliveira T C S; Steininger M; Tchamba J; Veenendaal E; Zuanny D; Baker T R; Dexter K G; Hegerl G; Pennington R T; Phillips O L; Sitch S; Williams M; Quegan S; Ryan C M<\/p>

Determinants of L-band backscatter in dry tropical ecosystems: Implications for biomass mapping<\/a> Journal Article<\/span> <\/p>

In: <\/span>Remote Sens. Environ., <\/span>vol. 334, <\/span>no. 115213, <\/span>pp. 115213, <\/span>2026<\/span>.<\/p>

Abstract<\/a><\/span> | Links<\/a><\/span> | BibTeX<\/a><\/span><\/p>

@article{Carreiras2026-nx,
\r\ntitle = {Determinants of L-band backscatter in dry tropical ecosystems:  Implications for biomass mapping},
\r\nauthor = {Jo\u00e3o M B Carreiras and Thomas Higginbottom and John L Godlee and Sam Harrison and Lorena Benitez and Penelope J Mograbi and Aurora Levesley and Karina Melga\u00e7o and David Milodowski and Georgia Pickavance and Geoff Wells and Edmar Almeida Oliveira and Luzmila Arroyo and Sam Bowers and Roel J W Brienen and Domingos Cardoso and Ant\u00f3nio Alberto Jorge Farias Castro and Ezequiel Chavez and \u00cdtalo A C Coutinho and Tom\u00e1s F Domingues and Fernando Elias and M\u00e1rio Marcos Esp\u00edrito Santo and Ted R Feldpausch and David Galbraith and Emanuel Gloor and Francisco M P Gon\u00e7alves and Tatenda Gotore and Francoise Yoko Ishida and Timothy J Killeen and Yadvinder Malhi and Beatriz S Marimon and Ben Hur Marimon-J\u00fanior and Desir\u00e9e Marques Ramos and Simone Matias Almeida Reis and Ian McNicol and Edward T A Mitchard and Peter Moonlight and Paulo S Morandi and Patricia Morellato and Anderson Muchawona and Jonathan Muledi and Alejandro Murakami and Mylor Ngoy Shutcha and Paula Nieto-Quintano and Alexander Parada-Gutierrez and Nayane Cristina Candida Santos Prestes and Luciano Paganucci Queiroz and Priscyla M S Rodrigues and Jhonathan Oliveira Silva and Rubens M Santos and Tiina S\u00e4rkinen and Domingos Fortunato P F Silva and Tony C Sousa Oliveira and Marc Steininger and Jos\u00e9 Tchamba and Elmar Veenendaal and D\u00e9bora Zuanny and Tim R Baker and Kyle G Dexter and Gabriele Hegerl and R Toby Pennington and Oliver L Phillips and Stephen Sitch and Mathew Williams and Shaun Quegan and Casey M Ryan},
\r\nurl = {https:\/\/rainfor.org\/wp-content\/uploads\/sites\/129\/2026\/03\/1-s2.0-S0034425725006170-main.pdf},
\r\ndoi = {10.1016\/j.rse.2025.115213},
\r\nyear  = {2026},
\r\ndate = {2026-03-01},
\r\nurldate = {2026-03-01},
\r\njournal = {Remote Sens. Environ.},
\r\nvolume = {334},
\r\nnumber = {115213},
\r\npages = {115213},
\r\npublisher = {Elsevier BV},
\r\nabstract = {Accurate characterization of the role of the dry tropics in the global carbon cycle requires precise estimation of woody biomass changes due to ecological and anthropogenic change, including deforestation, forest degradation, regrowth, mortality and enhanced tree growth due to climate change. L-band Synthetic Aperture Radar (SAR) backscatter observations offer a reliable option to consistently map these processes as they are (i) available globally since 2007 (JAXA ALOS-1, ALOS-2 and ALOS-4), and (ii) sensitive to woody structure, such as aboveground biomass density (
\r\n) up to \u223c100 t ha\u22121. However, we lack multi-site empirical understanding of the scattering processes that determine the relationship between L-band SAR and woody vegetation structure in the dry tropics, and how this is mediated by soil properties.
\r\nThis study used observations from ground plots in Africa (n = 171), Australia (n = 6), and South America (n = 44) to understand the impact of vegetation structure and soil properties on spatially and temporally coincident fully-polarimetric L-band SAR data. Fully-polarimetric L-band SAR single-look complex data were converted to scattering mechanisms\/parameters using van Zyl, Cloude-Pottier, and Freeman-Durden polarimetric decompositions to elucidate the physical mechanisms involved. Multivariate SAR-vegetation-soil relationships were analysed using a theory-informed structural equation modelling approach. The strongest positive effects on volume scattering come from stem density (stems ha\u22121) and mean stem biomass of trees, and soil water and sand content (standardized regression coefficients of 0.3, 0.1, 0.2 and 0.1, respectively). The only significant effect on surface scattering is from stem density (0.1). Significant effects on double bounce scattering are from stem density (0.3) and soil sand content (\u22120.2). Since 
\r\n is the product of stem density and mean stem biomass, this modelling framework points to a stronger effect from the number of trees rather than their size\/biomass. Therefore, 
\r\n maps relying solely on radar intensity may not reflect significant changes when 
\r\n is increasing due to the growth of existing stems. Additionally, such maps might overestimate changes in 
\r\n when driven by the recruitment of new stems or loss of existing stems. Full-polarimetric observations allow the decomposition of the radar signal into volume scattering, surface scattering, and double bounce, enabling the inversion of structural equation models to retrieve both stem density and mean stem biomass. This provides a more comprehensive description of forest structure compared to retrieving only 
\r\n. As this approach depends on full-polarimetric data, its effectiveness is closely tied to the availability of such observations. Our findings underscore the value of recent and upcoming missions such as ALOS-4 PALSAR-3, BIOMASS and ROSE-L, and highlight the need to prioritise the acquisition of quad-pol SAR data to support future large-scale retrieval of vegetation structure attributes.},
\r\nkeywords = {},
\r\npubstate = {published},
\r\ntppubtype = {article}
\r\n}
\r\n<\/pre><\/div>
Close<\/a><\/p><\/div>
Accurate characterization of the role of the dry tropics in the global carbon cycle requires precise estimation of woody biomass changes due to ecological and anthropogenic change, including deforestation, forest degradation, regrowth, mortality and enhanced tree growth due to climate change. L-band Synthetic Aperture Radar (SAR) backscatter observations offer a reliable option to consistently map these processes as they are (i) available globally since 2007 (JAXA ALOS-1, ALOS-2 and ALOS-4), and (ii) sensitive to woody structure, such as aboveground biomass density (
\r\n) up to \u223c100 t ha\u22121. However, we lack multi-site empirical understanding of the scattering processes that determine the relationship between L-band SAR and woody vegetation structure in the dry tropics, and how this is mediated by soil properties.
\r\nThis study used observations from ground plots in Africa (n = 171), Australia (n = 6), and South America (n = 44) to understand the impact of vegetation structure and soil properties on spatially and temporally coincident fully-polarimetric L-band SAR data. Fully-polarimetric L-band SAR single-look complex data were converted to scattering mechanisms\/parameters using van Zyl, Cloude-Pottier, and Freeman-Durden polarimetric decompositions to elucidate the physical mechanisms involved. Multivariate SAR-vegetation-soil relationships were analysed using a theory-informed structural equation modelling approach. The strongest positive effects on volume scattering come from stem density (stems ha\u22121) and mean stem biomass of trees, and soil water and sand content (standardized regression coefficients of 0.3, 0.1, 0.2 and 0.1, respectively). The only significant effect on surface scattering is from stem density (0.1). Significant effects on double bounce scattering are from stem density (0.3) and soil sand content (\u22120.2). Since 
\r\n is the product of stem density and mean stem biomass, this modelling framework points to a stronger effect from the number of trees rather than their size\/biomass. Therefore, 
\r\n maps relying solely on radar intensity may not reflect significant changes when 
\r\n is increasing due to the growth of existing stems. Additionally, such maps might overestimate changes in 
\r\n when driven by the recruitment of new stems or loss of existing stems. Full-polarimetric observations allow the decomposition of the radar signal into volume scattering, surface scattering, and double bounce, enabling the inversion of structural equation models to retrieve both stem density and mean stem biomass. This provides a more comprehensive description of forest structure compared to retrieving only 
\r\n. As this approach depends on full-polarimetric data, its effectiveness is closely tied to the availability of such observations. Our findings underscore the value of recent and upcoming missions such as ALOS-4 PALSAR-3, BIOMASS and ROSE-L, and highlight the need to prioritise the acquisition of quad-pol SAR data to support future large-scale retrieval of vegetation structure attributes.<\/div>
Close<\/a><\/p><\/div>