000165258 001__ 165258
000165258 005__ 20251219174252.0
000165258 0247_ $$2doi$$a10.18172/cig.6889
000165258 0248_ $$2sideral$$a146744
000165258 037__ $$aART-2025-146744
000165258 041__ $$aeng
000165258 100__ $$aAlves, Daniel Borini
000165258 245__ $$aPostfire Vegetation Recovery And Spectral Separability Over Amazonian Savanna Ecosystems Using Remote Sensing Time Series And Fuel Loads Measurements
000165258 260__ $$c2025
000165258 5060_ $$aAccess copy available to the general public$$fUnrestricted
000165258 5203_ $$aMonitoring and understanding vegetation responses to fire in Amazonian savanna ecosystems remains a very important scientific challenge to improve the landscape management practices of these areas. In this sense, the present study analyzes the dynamics of spectral separability as well as the postfire vegetation recovery process related to fire experiments carried out in open savanna ecosystems of the Campos Amazônicos National Park (Brazil). For this purpose, a harmonized Landsat and Sentinel-2 dataset was processed and analyzed. The time series of the Normalized Difference Vegetation Index (NDVI) and the Normalized Burned Ratio 2 (NBR2) spectral indices were also generated from this same dataset for the period from 2019 to 2023 and evaluated in combination with fine fuel load in-situ measurements. M-Statistics and mean absolute difference were calculated comparing data from burned and unburned plots, considering different treatments of fire seasonality (Early-Dry Season – EDS; Middle-Dry Season – MDS fires) and time since last fire (2-year-old fuel age; 3-year-old fuel age; and 10-year-old or older fuel age fires). The combined use of Sentinel-2 and Landsat resulted in an availability of cloud-free or partially cloud-free images ≈0.6 times greater than that obtained when using Landsat images exclusively. The potential of the NBR2 stood out, generating statistically significant mean absolute difference values when comparing EDS and MDS fires, and also when comparing 2-year-old fuel age areas with 3-year-old or 10-year-old or older fuel age areas. Satellite and field information converged in the detection of a rapid response of vegetation to fire in these ecosystems, demonstrating that conditions similar to those observed before the fire were reached after three rainy seasons. The results reinforce the potential of Landsat and Sentinel-2 harmonized remote sensing datasets to assess and monitor fire-affected areas over Amazonian savanna ecosystems, providing ecological meaning and establishing connections between remote sensing and field datasets.
000165258 536__ $$9info:eu-repo/grantAgreement/ES/MCIN-AEI/PID2020-118886RB-I00-AEI-10.13039-501100011033
000165258 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000165258 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000165258 700__ $$aLaffayete Pires da Silveira, Antonio
000165258 700__ $$aCambraia, Bruno Contursi
000165258 700__ $$aFalcão Sobrinho, José
000165258 700__ $$aSilva, Thiago Sanna Freire
000165258 700__ $$0(orcid)0000-0003-4831-4060$$aPérez-Cabello, Fernando$$uUniversidad de Zaragoza
000165258 7102_ $$13006$$2010$$aUniversidad de Zaragoza$$bDpto. Geograf. Ordenac.Territ.$$cÁrea Análisis Geográfico Regi.
000165258 773__ $$g51, 2 (2025), 133-154$$pCuad. investig. geogr.$$tGeographical Research Letters$$x0211-6820
000165258 8564_ $$s2119009$$uhttps://zaguan.unizar.es/record/165258/files/texto_completo.pdf$$yVersión publicada
000165258 8564_ $$s2367079$$uhttps://zaguan.unizar.es/record/165258/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000165258 909CO $$ooai:zaguan.unizar.es:165258$$particulos$$pdriver
000165258 951__ $$a2025-12-19-14:43:56
000165258 980__ $$aARTICLE