165258 20251219174252.0 doi 10.18172/cig.6889 sideral 146744 ART-2025-146744 eng Alves, Daniel Borini Postfire Vegetation Recovery And Spectral Separability Over Amazonian Savanna Ecosystems Using Remote Sensing Time Series And Fuel Loads Measurements 2025 Monitoring 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. Access copy available to the general public Unrestricted info:eu-repo/grantAgreement/ES/MCIN-AEI/PID2020-118886RB-I00-AEI-10.13039-501100011033 info:eu-repo/semantics/openAccess by https://creativecommons.org/licenses/by/4.0/deed.es info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Laffayete Pires da Silveira, Antonio Cambraia, Bruno Contursi Falcão Sobrinho, José Silva, Thiago Sanna Freire Pérez-Cabello, Fernando Universidad de Zaragoza (orcid)0000-0003-4831-4060 3006 010 Universidad de Zaragoza Dpto. Geograf. Ordenac.Territ. Área Análisis Geográfico Regi. 51, 2 (2025), 133-154 Cuad. investig. geogr. Geographical Research Letters 0211-6820 2119009 http://zaguan.unizar.es/record/165258/files/texto_completo.pdf Versión publicada 2367079 http://zaguan.unizar.es/record/165258/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:165258 articulos driver 2025-12-19-14:43:56 ARTICLE