Multi-temporal assessment of a wildfire chronosequence by remote sensing.

Autor:	Nájera De Ferrari F; Laboratorio de Conservación y Dinámica de Suelos Volcánicos, Departamento de Ciencias Químicas y Recursos Naturales, Facultad de Ingeniería y Ciencias, Universidad de La Frontera, Chile.; Laboratorio de Geomicrobiología, Facultad de Ingeniería y Ciencias, Departamento de Ciencias Químicas y Recursos Naturales, Universidad de La Frontera, Chile., Duarte E; Facultad de Ciencias Forestales, Universidad de Concepción, Chile., Smith-Ramírez C; Departamento de Ciencias Biológicas y Biodiversidad, Universidad de Los Lagos, Chile.; Instituto de Ecología y Biodiversidad-Chile (IEB), Chile.; Instituto de Conservación, Biodiversidad y Territorio, Facultad de Ciencias Forestales y Recursos Naturales, Universidad Austral de Chile, Chile., Rendon-Funes A; Departamento de Ciencias Biológicas y Biodiversidad, Universidad de Los Lagos, Chile.; Instituto de Ecología y Biodiversidad-Chile (IEB), Chile., Sepúlveda Gonzalez V; Laboratorio de Conservación y Dinámica de Suelos Volcánicos, Departamento de Ciencias Químicas y Recursos Naturales, Facultad de Ingeniería y Ciencias, Universidad de La Frontera, Chile., Sepúlveda Gonzalez N; Laboratorio de Conservación y Dinámica de Suelos Volcánicos, Departamento de Ciencias Químicas y Recursos Naturales, Facultad de Ingeniería y Ciencias, Universidad de La Frontera, Chile., Levio MF; Laboratorio de Conservación y Dinámica de Suelos Volcánicos, Departamento de Ciencias Químicas y Recursos Naturales, Facultad de Ingeniería y Ciencias, Universidad de La Frontera, Chile., Rubilar R; Facultad de Ciencias Forestales, Universidad de Concepción, Chile., Stehr A; Departamento de Ingeniería Civil, Facultad de Ingeniería, Universidad de Concepción, Chile., Merino C; Laboratorio de Geomicrobiología, Facultad de Ingeniería y Ciencias, Departamento de Ciencias Químicas y Recursos Naturales, Universidad de La Frontera, Chile.; Scientific and Biotechnological Resources Nucleus, Universidad de La Frontera (Bioren, UFRO), Chile., Jofré I; Laboratorio de Geomicrobiología, Facultad de Ingeniería y Ciencias, Departamento de Ciencias Químicas y Recursos Naturales, Universidad de La Frontera, Chile.; Scientific and Biotechnological Resources Nucleus, Universidad de La Frontera (Bioren, UFRO), Chile., Rojas C; Instituto de Ciencias Agroalimentarias, Animales y Ambientales de la Universidad de O'Higgins, Chile., Aburto F; Department of Soil and Crop Sciences, AgriLife Research, Texas A&M University, USA.; Departamento de Planificación Territorial y Sistemas Urbanos, Facultad de Ciencias Ambientales, Universidad de Concepción, Chile., Kuzyakov Y; Department of Soil Science of Temperate Ecosystems, Department of Agricultural Soil Science, University of Gottingen, 37077 Gottingen, Germany.; Peoples Friendship University of Russia (RUDN University), 117198 Moscow, Russia., Filimonenko E; University of Tyumen, Volodarskogo str., 6, Tyumen 625003, Russia., Dörner J; Instituto de Ingeniería Agraria y Suelos, Universidad Austral de Chile, Chile. Centro de Investigación en Suelos Volcánicos, Chile., Pereira P; Environmental Management Laboratory, Mykolas Romeris University, Vilnius, Lithuania., Matus F; Laboratorio de Conservación y Dinámica de Suelos Volcánicos, Departamento de Ciencias Químicas y Recursos Naturales, Facultad de Ingeniería y Ciencias, Universidad de La Frontera, Chile.
Jazyk:	angličtina
Zdroj:	MethodsX [MethodsX] 2024 Oct 18; Vol. 13, pp. 103011. Date of Electronic Publication: 2024 Oct 18 (Print Publication: 2024).
DOI:	10.1016/j.mex.2024.103011
Abstrakt:	The study aimed to develop a methodological framework to identify forest ecosystems affected by wildfires and evaluate their recovery chronologically. To do this remote sensing analysis, sites with burn scars were selected based on various criteria (fire severity, affected area, vegetation and soil type, slope, aspect, and one-time occurrence of wildfire in the last 23 years). Spectral vegetation indices (VIs) from satellite imagery were used to estimate burn severity and vegetation cover changes. Images of surface reflectance were obtained from the collection of Landsat 5 ETM, Landsat 7 ETM+, and Landsat 8 OLI/TIRS, available and processed on the Google Earth Engine Platform (GEE). Indices VIs (i) the normalized difference vegetation index (NDVI), (ii) the normalized burn ratio (NBR), and (iii) the differenced normalized burn ratio (dNBR) were calculated to classify burn severity. The one-time occurrence selection was performed using the LandTrendr algorithm to monitor changes in land cover and burned areas. To validate the selection, the chosen sites within the chronosequence were clustered on 4 seasons of soil properties and litter accumulation recovery. Our result can guide methodological comparisons and forest management practices on large surfaces by comparing parches of different time-affected ecosystems. Validation sites of the cluster chronosequence shows consistent recovery of soil properties as soil carbon, bulk density and litter accumulation through the studied years •The study developed a framework to identify wildfire-affected forest ecosystems and evaluate their recovery using remote sensing and local data.•Vegetation indices (NDVI, NBR, dNBR) from Landsat satellite imagery processed on the Google Earth Engine were used to assess burn severity and vegetation changes over time.•Selected sites were validated using the LandTrendr algorithm and monitored for seasonal changes in soil properties and litter accumulation. Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (© 2024 The Authors. Published by Elsevier B.V.)
Databáze:	MEDLINE
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