{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T04:03:10Z","timestamp":1767844990377,"version":"3.49.0"},"reference-count":86,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,3,23]],"date-time":"2022-03-23T00:00:00Z","timestamp":1647993600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001807","name":"S\u00e3o Paulo Research Foundation","doi-asserted-by":"publisher","award":["2016\/21043-8"],"award-info":[{"award-number":["2016\/21043-8"]}],"id":[{"id":"10.13039\/501100001807","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001807","name":"S\u00e3o Paulo Research Foundation","doi-asserted-by":"publisher","award":["2019\/21662-8"],"award-info":[{"award-number":["2019\/21662-8"]}],"id":[{"id":"10.13039\/501100001807","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003593","name":"National Council for Scientific and Technological Development","doi-asserted-by":"publisher","award":["458022\/2013-6"],"award-info":[{"award-number":["458022\/2013-6"]}],"id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002322","name":"Coordena\u00e7\u00e3o de Aperfeicoamento de Pessoal de N\u00edvel Superior","doi-asserted-by":"publisher","award":["Finance code 001"],"award-info":[{"award-number":["Finance code 001"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100020705","name":"Amazon Fund","doi-asserted-by":"publisher","award":["14209291"],"award-info":[{"award-number":["14209291"]}],"id":[{"id":"10.13039\/501100020705","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Climate and Land Use Alliance","award":["2010-57219"],"award-info":[{"award-number":["2010-57219"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Fire is a major forest degradation component in the Amazon forests. Therefore, it is important to improve our understanding of how the post-fire canopy structure changes cascade through the spectral signals registered by medium-resolution satellite sensors over time. We contrasted accumulated yearly temporal changes in forest aboveground biomass (AGB), measured in permanent plots, and in traditional spectral indices derived from Landsat-8 images. We tested if the spectral indices can improve Random Forest (RF) models of post-fire AGB losses based on pre-fire AGB, proxied by AGB data from immediately after a fire. The delta normalized burned ratio, non-photosynthetic vegetation, and green vegetation (\u0394NBR, \u0394NPV, and \u0394GV, respectively), relative to pre-fire data, were good proxies of canopy damage through tree mortality, even though small and medium trees were the most affected tree size. Among all tested predictors, pre-fire AGB had the highest RF model importance to predicting AGB within one year after fire. However, spectral indices significantly improved AGB loss estimates by 24% and model accuracy by 16% within two years after a fire, with \u0394GV as the most important predictor, followed by \u0394NBR and \u0394NPV. Up to two years after a fire, this study indicates the potential of structural and spectral-based spatial data for integrating complex post-fire ecological processes and improving carbon emission estimates by forest fires in the Amazon.<\/jats:p>","DOI":"10.3390\/rs14071545","type":"journal-article","created":{"date-parts":[[2022,3,23]],"date-time":"2022-03-23T22:08:06Z","timestamp":1648073286000},"page":"1545","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Quantifying Post-Fire Changes in the Aboveground Biomass of an Amazonian Forest Based on Field and Remote Sensing Data"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7668-1226","authenticated-orcid":false,"given":"Aline","family":"Pontes-Lopes","sequence":"first","affiliation":[{"name":"Earth Observation and Geoinformatics Division, National Institute for Space Research (INPE), S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7151-8697","authenticated-orcid":false,"given":"Ricardo","family":"Dalagnol","sequence":"additional","affiliation":[{"name":"Earth Observation and Geoinformatics Division, National Institute for Space Research (INPE), S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"},{"name":"NASA-Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA"},{"name":"Institute of the Environment and Sustainability, University of California, Los Angeles, CA 90095, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4454-7732","authenticated-orcid":false,"given":"Andeise Cerqueira","family":"Dutra","sequence":"additional","affiliation":[{"name":"Earth Observation and Geoinformatics Division, National Institute for Space Research (INPE), S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"}]},{"given":"Camila Val\u00e9ria","family":"de Jesus Silva","sequence":"additional","affiliation":[{"name":"Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK"},{"name":"Amazon Environmental Research Institute (IPAM), Bras\u00edlia 71503-505, Brazil"}]},{"given":"Paulo Maur\u00edcio Lima","family":"de Alencastro Gra\u00e7a","sequence":"additional","affiliation":[{"name":"Environmental Dynamics Coordination, National Institute for Research in Amazonia (INPA), Manaus 69067-375, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4134-6708","authenticated-orcid":false,"given":"Luiz Eduardo","family":"de Oliveira e Cruz de Arag\u00e3o","sequence":"additional","affiliation":[{"name":"Earth Observation and Geoinformatics Division, National Institute for Space Research (INPE), S\u00e3o Jos\u00e9 dos Campos 12227-010, Brazil"},{"name":"College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4RJ, UK"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2956","DOI":"10.1111\/gcb.15029","article-title":"Satellite-based estimates reveal widespread forest degradation in the Amazon","volume":"26","author":"Bullock","year":"2020","journal-title":"Glob. Chang. Biol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1378","DOI":"10.1126\/science.abb3021","article-title":"Long-term forest degradation surpasses deforestation in the Brazilian Amazon","volume":"369","author":"Matricardi","year":"2020","journal-title":"Science"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1038\/s41558-021-01026-5","article-title":"Carbon loss from forest degradation exceeds that from deforestation in the Brazilian Amazon","volume":"11","author":"Qin","year":"2021","journal-title":"Nat. Clim. Chang."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"18110","DOI":"10.1073\/pnas.1302584110","article-title":"Increased dry-season length over southern Amazonia in recent decades and its implication for future climate projection","volume":"110","author":"Fu","year":"2013","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1237","DOI":"10.5194\/esd-8-1237-2017","article-title":"Synergy between land use and climate change increases future fire risk in Amazon forests","volume":"8","author":"Morton","year":"2017","journal-title":"Earth Syst. Dyn."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1007\/s00267-014-0408-6","article-title":"Simulating Deforestation and Carbon Loss in Amazonia: Impacts in Brazil\u2019s Roraima State from Reconstructing Highway BR-319 (Manaus-Porto Velho)","volume":"55","author":"Barni","year":"2014","journal-title":"Environ. Manag."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"634","DOI":"10.1126\/science.abd6977","article-title":"The Amazon\u2019s road to deforestation","volume":"369","author":"Ferrante","year":"2020","journal-title":"Science"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1038\/s41467-017-02771-y","article-title":"21st Century drought-related fires counteract the decline of Amazon deforestation carbon emissions","volume":"9","author":"Anderson","year":"2018","journal-title":"Nat. Commun."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1038\/s41586-018-0300-2","article-title":"The tropical forest carbon cycle and climate change","volume":"559","author":"Mitchard","year":"2018","journal-title":"Nature"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"114023","DOI":"10.1088\/1748-9326\/abb62c","article-title":"Estimating the multi-decadal carbon deficit of burned Amazonian forests","volume":"15","author":"Silva","year":"2020","journal-title":"Environ. Res. Lett."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2516","DOI":"10.1111\/gcb.13172","article-title":"Effects of experimental fuel additions on fire intensity and severity: Unexpected carbon resilience of a neotropical forest","volume":"22","author":"Brando","year":"2016","journal-title":"Glob. Chang. Biol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1664","DOI":"10.1890\/05-0404","article-title":"Micrometeorological and Canopy Controls of Fire Susceptibility in a Forested Amazon Landscape","volume":"15","author":"Ray","year":"2005","journal-title":"Ecol. Appl."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1175\/EI150.1","article-title":"Forest understory fire in the Brazilian Amazon in ENSO and non-ENSO years: Area burned and committed carbon emissions","volume":"10","author":"Alencar","year":"2006","journal-title":"Earth Interact."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"20210094","DOI":"10.1098\/rspb.2021.0094","article-title":"Drought-driven wildfire impacts on structure and dynamics in a wet Central Amazonian forest","volume":"288","author":"Silva","year":"2021","journal-title":"Proc. R. Soc. B Biol. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1706","DOI":"10.1016\/j.rse.2011.03.002","article-title":"Mapping canopy damage from understory fires in Amazon forests using annual time series of Landsat and MODIS data","volume":"115","author":"Morton","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1098\/rstb.2003.1423","article-title":"Ecological responses to El Ni\u00f1o\u2013induced surface fires in central Brazilian Amazonia: Management implications for flammable tropical forests","volume":"359","author":"Barlow","year":"2004","journal-title":"Philos. Trans. R. Soc. London. Ser. B Biol. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"6347","DOI":"10.1073\/pnas.1305499111","article-title":"Abrupt increases in Amazonian tree mortality due to drought-fire interactions","volume":"111","author":"Brando","year":"2014","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"20180043","DOI":"10.1098\/rstb.2018.0043","article-title":"Drought-induced Amazonian wildfires instigate a decadal-scale disruption of forest carbon dynamics","volume":"373","author":"Silva","year":"2018","journal-title":"Philos. Trans. R. Soc. B Biol. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1016\/S0378-1127(02)00548-0","article-title":"Surface wildfires in central Amazonia: Short-term impact on forest structure and carbon loss","volume":"179","author":"Haugaasen","year":"2003","journal-title":"For. Ecol. Manag."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1046\/j.1461-0248.2003.00394.x","article-title":"Large tree mortality and the decline of forest biomass following Amazonian wildfires","volume":"6","author":"Barlow","year":"2003","journal-title":"Ecol. Lett."},{"key":"ref_21","first-page":"L07701","article-title":"Spatial patterns and fire response of recent Amazonian droughts","volume":"34","author":"Malhi","year":"2007","journal-title":"Geophys. Res. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1779","DOI":"10.1098\/rstb.2007.0026","article-title":"Interactions between rainfall, deforestation and fires during recent years in the Brazilian Amazonia","volume":"363","author":"Malhi","year":"2008","journal-title":"Philos. Trans. R. Soc."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"97","DOI":"10.3389\/feart.2019.00097","article-title":"Fire Responses to the 2010 and 2015\/2016 Amazonian Droughts","volume":"7","author":"Anderson","year":"2019","journal-title":"Front. Earth Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2755","DOI":"10.5194\/bg-14-2755-2017","article-title":"Changing patterns of fire occurrence in proximity to forest edges, roads and rivers between NW Amazonian countries","volume":"14","author":"Armenteras","year":"2017","journal-title":"Biogeosciences"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1739","DOI":"10.1002\/2014GB005008","article-title":"Disentangling the contribution of multiple land covers to fire-mediated carbon emissions in Amazonia during the 2010 drought","volume":"29","author":"Anderson","year":"2015","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1111\/btp.12153","article-title":"Fire damage in seasonally flooded and upland forests of the Central Amazon","volume":"46","author":"Nelson","year":"2014","journal-title":"Biotropica"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1624","DOI":"10.1007\/s10021-021-00607-x","article-title":"White-Sand Savannas Expand at the Core of the Amazon after Forest Wildfires","volume":"24","author":"Flores","year":"2021","journal-title":"Ecosystems"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1017\/S0266467403003328","article-title":"Morphological correlates of fire-induced tree mortality in a central Amazonian forest","volume":"19","author":"Barlow","year":"2003","journal-title":"J. Trop. Ecol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"630","DOI":"10.1111\/j.1365-2486.2011.02533.x","article-title":"Fire-induced tree mortality in a neotropical forest: The roles of bark traits, tree size, wood density and fire behavior","volume":"18","author":"Brando","year":"2012","journal-title":"Glob. Chang. Biol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1111\/ele.13409","article-title":"Thinner bark increases sensitivity of wetter Amazonian tropical forests to fire","volume":"23","author":"Staver","year":"2020","journal-title":"Ecol. Lett."},{"key":"ref_31","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_32","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_33","doi-asserted-by":"crossref","unstructured":"Campanharo, W.A., Lopes, A.P., Anderson, L.O., Silva, T.F.M.R., and Arag, L.E.O.C. (2019). Translating Fire Impacts in Southwestern Amazonia into Economic Costs. Remote Sens., 11.","DOI":"10.3390\/rs11070764"},{"key":"ref_34","unstructured":"Neuenschwander, L.F. (1999). Measuring and remote sensing of burn severity. Proceedings Joint Fire Science Conference and Workshop, University of Idaho and International Association of Wildland Fire."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1186\/s42408-018-0021-9","article-title":"Examining post-fire vegetation recovery with Landsat time series analysis in three western North American forest types","volume":"15","author":"Bright","year":"2019","journal-title":"Fire Ecol."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Lutes, D.C., Keane, R.E., Caratti, J.F., Key, C.H., Benson, N.C., Sutherland, S., and Gangi, L.J. (2006). Landscape Assessment (LA). MON: Fire Effects Monitoring and Inventory System, Department of Agriculture, Forest Service, Rocky Mountain Research Station.","DOI":"10.2737\/RMRS-GTR-164"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"853","DOI":"10.2307\/1941742","article-title":"Forest disturbance by large blowdowns in the Brazilian Amazon","volume":"75","author":"Nelson","year":"1994","journal-title":"Ecology"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"3322","DOI":"10.1016\/j.rse.2011.07.015","article-title":"Detection of subpixel treefall gaps with Landsat imagery in Central Amazon forests","volume":"115","author":"Chambers","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1175\/2010EI372.1","article-title":"Analyzing the impacts of frequency and severity of forest fire on the recovery of disturbed forest using landsat time series and EO-1 hyperion in the Southern Brazilian Amazon","volume":"15","author":"Numata","year":"2011","journal-title":"Earth Interact."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.rse.2016.06.017","article-title":"Contrasting fire damage and fire susceptibility between seasonally flooded forest and upland forest in the Central Amazon using portable profiling LiDAR","volume":"184","author":"Almeida","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1016\/j.rse.2003.12.015","article-title":"Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity","volume":"92","author":"Root","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1071\/WF07049","article-title":"Fire intensity, fire severity and burn severity: A brief review and suggested usage","volume":"18","author":"Keeley","year":"2009","journal-title":"Int. J. Wildland Fire"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2225","DOI":"10.1002\/eap.1368","article-title":"Landscape-scale consequences of differential tree mortality from catastrophic wind disturbance in the Amazon","volume":"26","author":"Rifai","year":"2016","journal-title":"Ecol. Appl."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"118960","DOI":"10.1016\/j.foreco.2021.118960","article-title":"Mapping the terrestrial ecoregions of the Purus-Madeira interfluve in the Amazon Forest using machine learning techniques","volume":"488","author":"Ximenes","year":"2021","journal-title":"For. Ecol. Manag."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Junk, W.J. (1997). The Large Central Amazonian River Floodplains Near Manaus: Geological, Climatological, Hydrological and Geomorphological Aspects. The Central Amazon Floodplain. Ecological Studies, Springer.","DOI":"10.1007\/978-3-662-03416-3"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"150066","DOI":"10.1038\/sdata.2015.66","article-title":"The climate hazards infrared precipitation with stations\u2014a new environmental record for monitoring extremes","volume":"2","author":"Funk","year":"2015","journal-title":"Sci. Data"},{"key":"ref_47","unstructured":"Giglio, L., Justice, C., Boschetti, L., and Roy, D. (2015). MCD64A1 MODIS\/Terra+Aqua Burned Area Monthly L3 Global 500 m SIN Grid V006 [Data Set], NASA EOSDIS Land Processes DAAC."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"20170308","DOI":"10.1098\/rstb.2017.0308","article-title":"Tree growth and stem carbon accumulation in human-modified Amazonian forests following drought and fire","volume":"373","author":"Berenguer","year":"2018","journal-title":"Philos. Trans. R. Soc. B Biol. Sci."},{"key":"ref_49","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_50","doi-asserted-by":"crossref","first-page":"994","DOI":"10.1016\/j.foreco.2013.09.045","article-title":"Amazon palm biomass and allometry","volume":"310","author":"Goodman","year":"2013","journal-title":"For. Ecol. Manag."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1017\/S0266467400001437","article-title":"Integrating liana abundance and forest stature into an estimate of total aboveground biomass for an eastern Amazonian forest","volume":"16","author":"Gerwing","year":"2000","journal-title":"J. Trop. Ecol."},{"key":"ref_52","unstructured":"R Core Team (2020). R: A language and Environment for Statistical Computing, R Core Team."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.rse.2016.04.008","article-title":"Preliminary analysis of the performance of the Landsat 8\/OLI land surface reflectance product","volume":"185","author":"Vermote","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_54","unstructured":"(2022, February 03). USGS Landsat 8 Surface Reflectance Tier 1 (LANDSAT\/LC08\/C01\/T1_SR). Available online: https:\/\/gee.stac.cloud\/BJmBzK1uPSS1qPWphBuPHgfbcqSkzxvCWZ94q."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Arai, E., Shimabukuro, Y.E., Dutra, A.C., and Duarte, V. (2019). Detection and Analysis of Forest Degradation by Fire Using Landsat\/Oli Images in Google Earth Engine. Int. Geosci. Remote Sens. Symp., 1649\u20131652.","DOI":"10.1109\/IGARSS.2019.8899250"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1109\/36.103288","article-title":"The least-squares mixing models to generate fraction images derived from remote sensing multispectral data","volume":"29","author":"Shimabukuro","year":"1991","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_58","unstructured":"(2021, March 10). Copernicus Sentinel Data 2021, Processed by ESA. Acessed on Google Earth Engine. Available online: https:\/\/developers.google.com\/earth-engine\/datasets\/catalog\/COPERNICUS_S2?hl=en#description."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"227","DOI":"10.2307\/2992183","article-title":"Adaptation: Statistics and a Null Model for Estimating Phylogenetic Effects","volume":"39","author":"Gittleman","year":"1990","journal-title":"Syst. Zool."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"526","DOI":"10.1093\/bioinformatics\/bty633","article-title":"ape 5.0: An environment for modern phylogenetics and evolutionary analyses in R","volume":"35","author":"Paradis","year":"2019","journal-title":"Bioinformatics"},{"key":"ref_61","unstructured":"Kassambara, A. (2020). Ggpubr: \u201cGgplot2\u201d Based Publication Ready Plots, R Package. Version 0.4.0."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_63","first-page":"18","article-title":"Classification and Regression by randomForest","volume":"2","author":"Liaw","year":"2002","journal-title":"R News"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1002\/bimj.200810425","article-title":"Simultaneous Inference in General Parametric Models","volume":"50","author":"Hothorn","year":"2008","journal-title":"Biom. J."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Kuhn, M. (2008). Building Predictive Models in R Using the caret Package. J. Stat. Softw., 28.","DOI":"10.18637\/jss.v028.i05"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"421","DOI":"10.32614\/RJ-2017-016","article-title":"pdp: An R Package for Constructing Partial Dependence Plots","volume":"9","author":"Greenwell","year":"2017","journal-title":"R J."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1016\/j.rse.2002.08.002","article-title":"Mapping forest degradation in the Eastern Amazon from SPOT 4 through spectral mixture models","volume":"87","author":"Souza","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1016\/j.tree.2007.05.001","article-title":"Regional ecosystem structure and function: Ecological insights from remote sensing of tropical forests","volume":"22","author":"Chambers","year":"2007","journal-title":"Trends Ecol. Evol."},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Viana-Soto, A., Aguado, I., Salas, J., and Garc\u00eda, M. (2020). Identifying Post-Fire Recovery Trajectories and Driving Factors Using Landsat Time Series in Fire-Prone Mediterranean Pine Forests. Remote Sens., 12.","DOI":"10.3390\/rs12091499"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1038\/nature18326","article-title":"Anthropogenic disturbance in tropical forests can double biodiversity loss from deforestation","volume":"535","author":"Barlow","year":"2016","journal-title":"Nature"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1890\/1051-0761(1997)007[0713:FIASLR]2.0.CO;2","article-title":"Fire in Amazonian selectively logged rain forest and the potential for fire reduction","volume":"7","author":"Holdsworth","year":"1997","journal-title":"Ecol. Appl."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.foreco.2012.11.044","article-title":"Forest fires in southwestern Brazilian Amazonia: Estimates of area and potential carbon emissions","volume":"291","author":"Fearnside","year":"2013","journal-title":"For. Ecol. Manag."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"e2019377118","DOI":"10.1073\/pnas.2019377118","article-title":"Tracking the impacts of El Ni\u00f1o drought and fire in human-modified Amazonian forests","volume":"118","author":"Berenguer","year":"2021","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1071\/WF18062","article-title":"Altered vegetation structure from mechanical thinning treatments changed wildfire behaviour in the wildland\u2013urban interface on the 2011 Wallow Fire, Arizona, USA","volume":"28","author":"Johnson","year":"2019","journal-title":"Int. J. Wildland Fire"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"664","DOI":"10.1111\/j.1744-7429.2010.00644.x","article-title":"Effects of Plot Size and Census Interval on Descriptors of Forest Structure and Dynamics","volume":"42","author":"Wagner","year":"2010","journal-title":"Biotropica"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1186\/s13021-015-0021-x","article-title":"Effects of field plot size on prediction accuracy of aboveground biomass in airborne laser scanning-assisted inventories in tropical rain forests of Tanzania","volume":"10","author":"Mauya","year":"2015","journal-title":"Carbon Balance Manag."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"111323","DOI":"10.1016\/j.rse.2019.111323","article-title":"Combining LiDAR and hyperspectral data for aboveground biomass modeling in the Brazilian Amazon using different regression algorithms","volume":"232","author":"Ometto","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1016\/S0378-1127(01)00509-6","article-title":"Biomass estimation in the Tapajos National Forest, Brazil","volume":"154","author":"Keller","year":"2001","journal-title":"For. Ecol. Manag."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/j.rse.2012.10.017","article-title":"A meta-analysis of terrestrial aboveground biomass estimation using lidar remote sensing","volume":"128","author":"Zolkos","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Mutanga, O., and Kumar, L. (2019). Google Earth Engine Applications. Remote Sens., 11.","DOI":"10.3390\/rs11050591"},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1016\/j.rse.2009.12.018","article-title":"Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches","volume":"114","author":"Powell","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_82","first-page":"15425","article-title":"Improving the spatial-temporal analysis of Amazonian fires","volume":"27","author":"Berenguer","year":"2020","journal-title":"Glob. Chang. Biol."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.rse.2014.07.028","article-title":"Importance of sample size, data type and prediction method for remote sensing-based estimations of aboveground forest biomass","volume":"154","author":"Fassnacht","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1080\/15481603.2014.972866","article-title":"Spectral\/textural attributes from ALI\/EO-1 for mapping primary and secondary tropical forests and studying the relationships with biophysical parameters","volume":"51","author":"Silva","year":"2014","journal-title":"GIScience Remote Sens."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1080\/17538947.2014.990526","article-title":"A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems","volume":"9","author":"Lu","year":"2016","journal-title":"Int. J. Digit. Earth"},{"key":"ref_86","first-page":"163","article-title":"Sensitivity of ALOS\/PALSAR imagery to forest degradation by fire in northern Amazon","volume":"49","author":"Martins","year":"2016","journal-title":"Int. J. Appl. Earth Obs. 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