{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T03:38:03Z","timestamp":1773200283140,"version":"3.50.1"},"reference-count":89,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2019,4,3]],"date-time":"2019-04-03T00:00:00Z","timestamp":1554249600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010198","name":"Ministerio de Econom\u00eda, Industria y Competitividad, Gobierno de Espa\u00f1a","doi-asserted-by":"publisher","award":["DI-15-08093"],"award-info":[{"award-number":["DI-15-08093"]}],"id":[{"id":"10.13039\/501100010198","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Forest aboveground biomass (AGB) estimation over large extents and high temporal resolution is crucial in managing Mediterranean forest ecosystems, which have been predicted to be very sensitive to climate change effects. Although many modeling procedures have been tested to assess forest AGB, most of them cover small areas and attain high accuracy in evaluations that are difficult to update and extrapolate without large uncertainties. In this study, focusing on the Region of Murcia in Spain (11,313 km2), we integrated forest AGB estimations, obtained from high-precision airborne laser scanning (ALS) data calibrated with plot-level ground-based measures and bio-geophysical spectral variables (eight different indices derived from MODIS computed at different temporal resolutions), as well as topographic factors as predictors. We used a quantile regression forest (QRF) to spatially predict biomass and the associated uncertainty. The fitted model produced a satisfactory performance (R2 0.71 and RMSE 9.99 t\u00b7ha\u22121) with the normalized difference vegetation index (NDVI) as the main vegetation index, in combination with topographic variables as environmental drivers. An independent validation carried out over the final predicted biomass map showed a satisfactory statistically-robust model (R2 0.70 and RMSE 10.25 t\u00b7ha\u22121), confirming its applicability at coarser resolutions.<\/jats:p>","DOI":"10.3390\/rs11070795","type":"journal-article","created":{"date-parts":[[2019,4,4]],"date-time":"2019-04-04T03:13:42Z","timestamp":1554347622000},"page":"795","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Improving Aboveground Forest Biomass Maps: From High-Resolution to National Scale"],"prefix":"10.3390","volume":"11","author":[{"given":"Pilar","family":"Durante","sequence":"first","affiliation":[{"name":"Agresta Sociedad Cooperativa, 28012 Madrid, Spain"},{"name":"Departamento de Agronom\u00eda, Universidad de Almer\u00eda, 04120 Almer\u00eda, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5327-5695","authenticated-orcid":false,"given":"Santiago","family":"Mart\u00edn-Alc\u00f3n","sequence":"additional","affiliation":[{"name":"Agresta Sociedad Cooperativa, 28012 Madrid, Spain"}]},{"given":"Assu","family":"Gil-Tena","sequence":"additional","affiliation":[{"name":"Agresta Sociedad Cooperativa, 28012 Madrid, Spain"}]},{"given":"Nur","family":"Algeet","sequence":"additional","affiliation":[{"name":"Agresta Sociedad Cooperativa, 28012 Madrid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2298-9115","authenticated-orcid":false,"given":"Jos\u00e9 Luis","family":"Tom\u00e9","sequence":"additional","affiliation":[{"name":"Agresta Sociedad Cooperativa, 28012 Madrid, Spain"}]},{"given":"Laura","family":"Recuero","sequence":"additional","affiliation":[{"name":"Departamento de Sistemas y Recursos Naturales, ETSIMFMN, Universidad Polit\u00e9cnica de Madrid, 28040 Madrid, Spain"}]},{"given":"Alicia","family":"Palacios-Orueta","sequence":"additional","affiliation":[{"name":"Departamento de Sistemas y Recursos Naturales, ETSIMFMN, Universidad Polit\u00e9cnica de Madrid, 28040 Madrid, Spain"}]},{"given":"Cecilio","family":"Oyonarte","sequence":"additional","affiliation":[{"name":"Departamento de Agronom\u00eda, Universidad de Almer\u00eda, 04120 Almer\u00eda, Spain"},{"name":"Centro Andaluz para la Evaluaci\u00f3n y Seguimiento del Cambio Global (CAESCG), 04120 Almer\u00eda, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2019,4,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3955","DOI":"10.1007\/s00024-018-1853-6","article-title":"Assessing Shifts of Mediterranean and Arid Climates Under RCP4.5 and RCP8.5 Climate Projections in Europe","volume":"175","author":"Barredo","year":"2018","journal-title":"Pure Appl. 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