Effect of Baseline Definition on Post-Fire Resilience Metrics Derived from Landsat Time Series in Pinus halepensis

Martín-Ortiz, Pedro (Universidad de Zaragoza) ; Iranzo, Cristian (Universidad de Zaragoza) ; Alves, Daniel Borini ; Montorio, Raquel (Universidad de Zaragoza) ; Pérez-Cabello, Fernando (Universidad de Zaragoza)

Resumen: Wildfires have historically shaped Mediterranean ecosystems, fostering the adaptation of fire-resilient species such as Pinus halepensis Mill. Assessing post-fire resilience is essential to understand landscape recovery and guide forest management. This requires evaluating the speed, intensity, and trajectory of vegetation recovery relative to a defined baseline, although the influence of control point selection and baseline configuration remains unclear, despite its critical role in shaping the interpretation of recovery dynamics. This study proposes a methodological framework to assess the resilience of P. halepensis using 14-year Landsat time series following wildfire events, combined with image segmentation algorithms and Object-Based Image Analysis (GEOBIA). The analysis integrates two complementary vectors: (i) temporal evolution of NDVI and (ii) spectral probability of assignment to P. halepensis. Results indicate that NDVI suggests an average vegetation recovery time of seven years; however, spectral probability remains below 40% during this period, indicating slower tree cover recovery. Field inventories confirm that full recovery requires more than 15 years, with early stages dominated by shrublands, mainly Quercus coccifera. These findings show that NDVI alone overestimates resilience and that control selection and baseline configuration strongly influence assessments. GEOBIA enhances the ecological precision of resilience evaluation.

Idioma: Inglés

DOI: 10.3390/rs18091352

Año: 2026

Publicado en: Remote Sensing 18, 9 (2026), 1352 [31 pp.]
ISSN: 2072-4292

Financiación: info:eu-repo/grantAgreement/ES/MCIN-AEI/PID2020-118886RB-I00-AEI-10.13039-501100011033
Financiación: info:eu-repo/grantAgreement/ES/MCIN-AEI/PID2024-160889OA-I00-AEI-10.13039-501100011033

Tipo y forma: Article (Published version)

Área (Departamento): Área Análisis Geográfico Regi. (Dpto. Geograf. Ordenac.Territ.)