{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T20:37:31Z","timestamp":1791923851710,"version":"4.3.4"},"reference-count":58,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,2,1]],"date-time":"2025-02-01T00:00:00Z","timestamp":1738368000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,1,25]],"date-time":"2025-01-25T00:00:00Z","timestamp":1737763200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","doi-asserted-by":"publisher","award":["UID\/00239"],"award-info":[{"award-number":["UID\/00239"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000104","name":"NASA","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000104","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100023561","name":"Government of Spain Ministry of Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100023561","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100008510","name":"University of Maryland","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100008510","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006136","name":"Fuel Cell Technologies Program","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006136","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Environmental Management"],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1016\/j.jenvman.2025.124313","type":"journal-article","created":{"date-parts":[[2025,1,31]],"date-time":"2025-01-31T10:42:53Z","timestamp":1738320173000},"page":"124313","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":26,"special_numbering":"C","title":["Calibration of GEDI footprint aboveground biomass models in Mediterranean forests with NFI plots: A comparison of approaches"],"prefix":"10.1016","volume":"375","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2957-7810","authenticated-orcid":false,"given":"Adri\u00e1n","family":"Pascual","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul B.","family":"May","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1649-7720","authenticated-orcid":false,"given":"Aar\u00f3n","family":"C\u00e1rdenas-Mart\u00ednez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan","family":"Guerra-Hern\u00e1ndez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-3963-0933","authenticated-orcid":false,"given":"Neha","family":"Hunka","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jamis M.","family":"Bruening","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sean P.","family":"Healey","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John D.","family":"Armston","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ralph O.","family":"Dubayah","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.jenvman.2025.124313_bib1","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.foreco.2013.09.007","article-title":"National Forest Inventory and forest observational studies in Spain: applications to forest modeling","volume":"316","author":"\u00c1lvarez-Gonz\u00e1lez","year":"2014","journal-title":"For. Ecol. Manag."},{"key":"10.1016\/j.jenvman.2025.124313_bib2","series-title":"Using High-Performance Global Navigation Satellite System Technology to Improve Forest Inventory and Analysis Plot Coordinates in the Pacific Region (PNW-GTR-1000; P. PNW-GTR-1000)","author":"Andersen","year":"2022"},{"key":"10.1016\/j.jenvman.2025.124313_bib4","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2022.112917","article-title":"A comprehensive framework for assessing the accuracy and uncertainty of global above-ground biomass maps","volume":"272","author":"Araza","year":"2022","journal-title":"Rem. Sens. Environ."},{"key":"10.1016\/j.jenvman.2025.124313_bib5","author":"Armston","year":"2023"},{"key":"10.1016\/j.jenvman.2025.124313_bib7","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1016\/j.rse.2018.04.044","article-title":"Geostatistical estimation of forest biomass in interior Alaska combining Landsat-derived tree cover, sampled airborne lidar and field observations","volume":"212","author":"Babcock","year":"2018","journal-title":"Rem. Sens. Environ."},{"issue":"1","key":"10.1016\/j.jenvman.2025.124313_bib67","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1186\/s13021-022-00214-w","article-title":"On the use of Earth Observation to support estimates of national greenhouse gas emissions and sinks for the Global stocktake process: lessons learned from ESA-CCI RECCAP2","volume":"17","author":"Bastos","year":"2022","journal-title":"Carbon Balance Manag."},{"key":"10.1016\/j.jenvman.2025.124313_bib9","doi-asserted-by":"crossref","DOI":"10.3389\/ffgc.2023.1149153","article-title":"Precise and unbiased biomass estimation from GEDI data and the US Forest Inventory","volume":"6","author":"Bruening","year":"2023","journal-title":"Frontiers in Forests and Global Change"},{"issue":"8","key":"10.1016\/j.jenvman.2025.124313_bib10","doi-asserted-by":"crossref","DOI":"10.1088\/1748-9326\/acdf03","article-title":"Estimating aboveground biomass density using hybrid statistical inference with GEDI lidar data and Paraguay's national forest inventory","volume":"18","author":"Bullock","year":"2023","journal-title":"Environ. Res. Lett."},{"key":"10.1016\/j.jenvman.2025.124313_bib12","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2024.176453","article-title":"Analysing long-term spatiotemporal land surface phenology patterns over the Iberian Peninsula using 250 m MODIS EVI2 data","volume":"954","author":"Caparros-Santiago","year":"2024","journal-title":"Sci. Total Environ."},{"key":"10.1016\/j.jenvman.2025.124313_bib13","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2023.113703","article-title":"Structural and species diversity explain aboveground carbon storage in forests across the United States: evidence from GEDI and forest inventory data","volume":"295","author":"Crockett","year":"2023","journal-title":"Rem. Sens. Environ."},{"key":"10.1016\/j.jenvman.2025.124313_bib14","doi-asserted-by":"crossref","DOI":"10.1016\/j.biocon.2020.108907","article-title":"ForestGEO: understanding forest diversity and dynamics through a global observatory network","volume":"253","author":"Davies","year":"2021","journal-title":"Biol. Conserv."},{"issue":"12","key":"10.1016\/j.jenvman.2025.124313_bib15","doi-asserted-by":"crossref","first-page":"2279","DOI":"10.3390\/rs13122279","article-title":"Assessing the accuracy of GEDI data for canopy height and aboveground biomass estimates in mediterranean forests","volume":"13","author":"Dorado-Roda","year":"2021","journal-title":"Rem. Sens."},{"key":"10.1016\/j.jenvman.2025.124313_bib17","doi-asserted-by":"crossref","DOI":"10.1016\/j.srs.2020.100002","article-title":"The global ecosystem dynamics investigation: high-resolution laser ranging of the earth's forests and topography","volume":"1","author":"Dubayah","year":"2020","journal-title":"Science of Remote Sensing"},{"issue":"9","key":"10.1016\/j.jenvman.2025.124313_bib16","doi-asserted-by":"crossref","DOI":"10.1088\/1748-9326\/ac8694","article-title":"GEDI launches a new era of biomass inference from space","volume":"17","author":"Dubayah","year":"2022","journal-title":"Environ. Res. Lett."},{"key":"10.1016\/j.jenvman.2025.124313_bib64","author":"Dubayah","year":"2022"},{"key":"10.1016\/j.jenvman.2025.124313_bib19","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2021.112845","article-title":"Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission","volume":"270","author":"Duncanson","year":"2022","journal-title":"Rem. Sens. Environ."},{"key":"10.1016\/j.jenvman.2025.124313_bib20","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":"Rem. Sens. Environ."},{"issue":"11","key":"10.1016\/j.jenvman.2025.124313_bib69","doi-asserted-by":"crossref","first-page":"4811","DOI":"10.5194\/essd-14-4811-2022","article-title":"Global carbon budget 2022","volume":"14","author":"Friedlingstein","year":"2022","journal-title":"Earth Syst. Sci. Data"},{"key":"10.1016\/j.jenvman.2025.124313_bib21","doi-asserted-by":"crossref","DOI":"10.1016\/j.gecco.2021.e01901","article-title":"Progress on incorporating biodiversity monitoring in REDD+ through national forest inventories","volume":"32","author":"Gillerot","year":"2021","journal-title":"Global Ecology and Conservation"},{"key":"10.1016\/j.jenvman.2025.124313_bib22","doi-asserted-by":"crossref","DOI":"10.1016\/j.foreco.2020.118690","article-title":"Developing a site index model for P. Pinaster stands in NW Spain by combining bi-temporal ALS data and environmental data","volume":"481","author":"Guerra-Hern\u00e1ndez","year":"2021","journal-title":"For. Ecol. Manag."},{"issue":"1","key":"10.1016\/j.jenvman.2025.124313_bib23","doi-asserted-by":"crossref","DOI":"10.1080\/22797254.2024.2315413","article-title":"Using bi-temporal ALS and NFI-based time-series data to account for large-scale aboveground carbon dynamics: the showcase of mediterranean forests","volume":"57","author":"Guerra-Hern\u00e1ndez","year":"2024","journal-title":"European Journal of Remote Sensing"},{"key":"10.1016\/j.jenvman.2025.124313_bib25","doi-asserted-by":"crossref","DOI":"10.1016\/j.srs.2023.100106","article-title":"Computational tools for assessing forest recovery with GEDI shots and forest change maps","volume":"8","author":"Holcomb","year":"2023","journal-title":"Science of Remote Sensing"},{"issue":"2","key":"10.1016\/j.jenvman.2025.124313_bib65","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1029\/2018EA000506","article-title":"The GEDI simulator: a large-footprint waveform lidar simulator for calibration and validation of spaceborne missions","volume":"6","author":"Hancock","year":"2019","journal-title":"Earth Space Sci."},{"key":"10.1016\/j.jenvman.2025.124313_bib26","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2024.114174","article-title":"Repeat GEDI footprints measure the effects of tropical forest disturbances","volume":"308","author":"Holcomb","year":"2024","journal-title":"Rem. Sens. Environ."},{"issue":"12","key":"10.1016\/j.jenvman.2025.124313_bib27","doi-asserted-by":"crossref","DOI":"10.1088\/1748-9326\/ad0b60","article-title":"On the NASA GEDI and ESA CCI biomass maps: aligning for uptake in the UNFCCC global stocktake","volume":"18","author":"Hunka","year":"2023","journal-title":"Environ. Res. Lett."},{"key":"10.1016\/j.jenvman.2025.124313_bib28","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2024.114557","article-title":"A geostatistical approach to enhancing national forest biomass assessments with Earth Observation to aid climate policy needs","volume":"318","author":"Hunka","year":"2025","journal-title":"Rem. Sens. Environ."},{"issue":"4","key":"10.1016\/j.jenvman.2025.124313_bib30","doi-asserted-by":"crossref","DOI":"10.1088\/1748-9326\/ad3661","article-title":"Vicarious calibration of GEDI biomass with Landsat age data for understanding secondary forest carbon dynamics","volume":"19","author":"Jha","year":"2024","journal-title":"Environ. Res. Lett."},{"issue":"9","key":"10.1016\/j.jenvman.2025.124313_bib68","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1890\/1540-9295(2004)002[0475:WITWAM]2.0.CO;2","article-title":"Where in the world are my field plots? Using GPS effectively in environmental field studies","volume":"2","author":"Johnson","year":"2004","journal-title":"Front. Ecol. Environ."},{"issue":"4","key":"10.1016\/j.jenvman.2025.124313_bib32","doi-asserted-by":"crossref","DOI":"10.1029\/2022EA002516","article-title":"Algorithm theoretical basis document for GEDI footprint aboveground biomass density","volume":"10","author":"Kellner","year":"2022","journal-title":"Earth Space Sci."},{"key":"10.1016\/j.jenvman.2025.124313_bib33","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2019.111597","article-title":"Structure metrics to generalize biomass estimation from lidar across forest types from different continents","volume":"237","author":"Knapp","year":"2020","journal-title":"Rem. Sens. Environ."},{"issue":"7","key":"10.1016\/j.jenvman.2025.124313_bib34","doi-asserted-by":"crossref","first-page":"1587","DOI":"10.1111\/2041-210X.14084","article-title":"Effects of outliers on remote sensing\u2010assisted forest biomass estimation: a case study from the United States national forest inventory","volume":"14","author":"Knott","year":"2023","journal-title":"Methods Ecol. Evol."},{"issue":"11","key":"10.1016\/j.jenvman.2025.124313_bib35","doi-asserted-by":"crossref","first-page":"3317","DOI":"10.1109\/TGRS.2007.900693","article-title":"TanDEM-X: a satellite formation for high-resolution SAR interferometry","volume":"45","author":"Krieger","year":"2007","journal-title":"IEEE Trans. Geosci. Rem. Sens."},{"issue":"3","key":"10.1016\/j.jenvman.2025.124313_bib36","doi-asserted-by":"crossref","first-page":"827","DOI":"10.1111\/gcb.16497","article-title":"Toward a forest biomass reference measurement system for remote sensing applications","volume":"29","author":"Labri\u00e8re","year":"2023","journal-title":"Global Change Biol."},{"key":"10.1016\/j.jenvman.2025.124313_bib37","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2022.113402","article-title":"First validation of GEDI canopy heights in African savannas","volume":"285","author":"Li","year":"2023","journal-title":"Rem. Sens. Environ."},{"key":"10.1016\/j.jenvman.2025.124313_bib39","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2021.112571","article-title":"Performance evaluation of GEDI and ICESat-2 laser altimeter data for terrain and canopy height retrievals","volume":"264","author":"Liu","year":"2021","journal-title":"Rem. Sens. Environ."},{"issue":"37","key":"10.1016\/j.jenvman.2025.124313_bib40","doi-asserted-by":"crossref","DOI":"10.1126\/sciadv.adh4097","article-title":"The overlooked contribution of trees outside forests to tree cover and woody biomass across Europe","volume":"9","author":"Liu","year":"2023","journal-title":"Sci. Adv."},{"issue":"1","key":"10.1016\/j.jenvman.2025.124313_bib41","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":"International Journal of Digital Earth"},{"issue":"1","key":"10.1016\/j.jenvman.2025.124313_bib66","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1139\/X10-164","article-title":"Influence of Global Navigation Satellite System errors in positioning inventory plots for tree-height distribution studiesThis article is one of a selection of papers from Extending Forest Inventory and Monitoring over Space and Time","volume":"41","author":"Mauro","year":"2011","journal-title":"Can. J. For. Res."},{"key":"10.1016\/j.jenvman.2025.124313_bib42","author":"May"},{"issue":"12","key":"10.1016\/j.jenvman.2025.124313_bib70","doi-asserted-by":"crossref","first-page":"3378","DOI":"10.1111\/gcb.16682","article-title":"Spatial heterogeneity of global forest aboveground carbon stocks and fluxes constrained by spaceborne lidar data and mechanistic modeling","volume":"29","author":"Ma","year":"2023","journal-title":"Glob. Change Biol."},{"key":"10.1016\/j.jenvman.2025.124313_bib43","doi-asserted-by":"crossref","DOI":"10.1016\/j.tfp.2021.100171","article-title":"Commercial forest carbon protocol over-credit bias delimited by zero-threshold carbon accounting","volume":"7","author":"Marino","year":"2022","journal-title":"Trees, Forests and People"},{"key":"10.1016\/j.jenvman.2025.124313_bib44","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1016\/j.rse.2017.12.017","article-title":"The shelf-life of airborne laser scanning data for enhancing forest inventory inferences","volume":"206","author":"McRoberts","year":"2018","journal-title":"Rem. Sens. Environ."},{"issue":"3","key":"10.1016\/j.jenvman.2025.124313_bib45","doi-asserted-by":"crossref","DOI":"10.1088\/1748-9326\/acba31","article-title":"Satellite-based global maps are rarely used in forest reference levels submitted to the UNFCCC","volume":"18","author":"Melo","year":"2023","journal-title":"Environ. Res. Lett."},{"issue":"1\u20132","key":"10.1016\/j.jenvman.2025.124313_bib46","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1007\/s10584-021-03079-z","article-title":"What is the risk of overestimating emission reductions from forests \u2013 and what can be done about it?","volume":"166","author":"Neeff","year":"2021","journal-title":"Climatic Change"},{"issue":"7","key":"10.1016\/j.jenvman.2025.124313_bib49","doi-asserted-by":"crossref","first-page":"371","DOI":"10.3390\/f9070371","article-title":"Effects of plot positioning errors on the optimality of harvest prescriptions when spatial forest planning relies on ALS data","volume":"9","author":"Pascual","year":"2018","journal-title":"Forests"},{"issue":"3","key":"10.1016\/j.jenvman.2025.124313_bib50","doi-asserted-by":"crossref","first-page":"413","DOI":"10.3390\/rs12030413","article-title":"The role of improved ground positioning and forest structural complexity when performing forest inventory using airborne laser scanning","volume":"12","author":"Pascual","year":"2020","journal-title":"Rem. Sens."},{"issue":"1","key":"10.1016\/j.jenvman.2025.124313_bib51","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1080\/01431161.2020.1813346","article-title":"Using enhanced data co-registration to update Spanish National Forest Inventories (NFI) and to reduce training data under LiDAR-assisted inference","volume":"42","author":"Pascual","year":"2021","journal-title":"Int. J. Rem. Sens."},{"key":"10.1016\/j.jenvman.2025.124313_bib52","doi-asserted-by":"crossref","DOI":"10.1016\/j.ecoinf.2023.102092","article-title":"Correction of phenology-induced effects in forest canopy height models based on airborne laser scanning data. Insights from the deciduous mountain forests in Picos de Europa National Park in Spain","volume":"75","author":"Pascual","year":"2023","journal-title":"Ecol. Inf."},{"key":"10.1016\/j.jenvman.2025.124313_bib53","doi-asserted-by":"crossref","DOI":"10.1016\/j.foreco.2023.120975","article-title":"Assessing the performance of NASA's GEDI L4A footprint aboveground biomass density models using National Forest Inventory and airborne laser scanning data in Mediterranean forest ecosystems","volume":"538","author":"Pascual","year":"2023","journal-title":"For. Ecol. Manag."},{"issue":"6","key":"10.1016\/j.jenvman.2025.124313_bib54","doi-asserted-by":"crossref","DOI":"10.1088\/1748-9326\/ab18df","article-title":"Statistical properties of hybrid estimators proposed for GEDI\u2014NASA\u2019s global ecosystem dynamics investigation","volume":"14","author":"Patterson","year":"2019","journal-title":"Environ. Res. Lett."},{"key":"10.1016\/j.jenvman.2025.124313_bib55","series-title":"Validation and Intercomparison Report","article-title":"Planet forest carbon diligence","year":"2024"},{"key":"10.1016\/j.jenvman.2025.124313_bib56","doi-asserted-by":"crossref","DOI":"10.1016\/j.srs.2021.100024","article-title":"The impact of geolocation uncertainty on GEDI tropical forest canopy height estimation and change monitoring","volume":"4","author":"Roy","year":"2021","journal-title":"Science of Remote Sensing"},{"key":"10.1016\/j.jenvman.2025.124313_bib58","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2022.113391","article-title":"Nationwide native forest structure maps for Argentina based on forest inventory data, SAR Sentinel-1 and vegetation metrics from Sentinel-2 imagery","volume":"285","author":"Silveira","year":"2023","journal-title":"Rem. Sens. Environ."},{"key":"10.1016\/j.jenvman.2025.124313_bib59","doi-asserted-by":"crossref","DOI":"10.1016\/j.rse.2023.113571","article-title":"Evaluating and mitigating the impact of systematic geolocation error on canopy height measurement performance of GEDI","volume":"291","author":"Tang","year":"2023","journal-title":"Rem. Sens. Environ."},{"key":"10.1016\/j.jenvman.2025.124313_bib63","first-page":"1155","article-title":"Spatial factor models for high-dimensional and large spatial data: an application in forest variable mapping","volume":"29","author":"Taylor-Rodriguez","year":"2019","journal-title":"Statistica Sinica"},{"issue":"8","key":"10.1016\/j.jenvman.2025.124313_bib60","doi-asserted-by":"crossref","first-page":"530","DOI":"10.1007\/s10661-022-10219-0","article-title":"A spatial and temporal assessment of nonresponse in the national forest inventory of the U.S","volume":"194","author":"Westfall","year":"2022","journal-title":"Environ. Monit. Assess."},{"key":"10.1016\/j.jenvman.2025.124313_bib61","article-title":"ESA WorldCover 10 m 2021 v200 (Version v200)","author":"Zanaga","year":"2022","journal-title":"Zenodo"},{"key":"10.1016\/j.jenvman.2025.124313_bib62","article-title":"Modelling forest volume with small area estimation of forest inventory using GEDI footprints as auxiliary information","volume":"114","author":"Zhang","year":"2022","journal-title":"Int. J. Appl. Earth Obs. Geoinf."}],"container-title":["Journal of Environmental Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0301479725002890?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0301479725002890?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T00:35:15Z","timestamp":1763685315000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0301479725002890"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2]]},"references-count":58,"alternative-id":["S0301479725002890"],"URL":"https:\/\/doi.org\/10.1016\/j.jenvman.2025.124313","relation":{},"ISSN":["0301-4797"],"issn-type":[{"value":"0301-4797","type":"print"}],"subject":[],"published":{"date-parts":[[2025,2]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Calibration of GEDI footprint aboveground biomass models in Mediterranean forests with NFI plots: A comparison of approaches","name":"articletitle","label":"Article Title"},{"value":"Journal of Environmental Management","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jenvman.2025.124313","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Authors. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"124313"}}