Using long time series of Landsat data to monitor fire events and post-fire dynamics and identify driving factors. A case study in the Ayora region (eastern Spain)

Burn severity influence on post-fire vegetation cover resilience from Landsat MESMA fraction images time series in Mediterranean forest ecosystems

“…The unburned control plot procedure established an unburned reference to compute VRI for each burn severity level. As the evolution in time of these three VRI time series showed different vegetation cover recovery patterns, it was concluded that burn severity has a great impact on the capability of a system to recover to its initial conditions, as previous studies showed (Covington and Sackett, 1992;Maia et al, 2012;Neary et al, 1999;Röder et al, 2008;Smithwick et al, 2005).…”

“…In terms of post-fire impacts, SMA has been used to analyze post-fire vegetation recovery in several studies (rather fewer than vegetation indices). Notable examples include papers by Riaño et al (2002); Röder et al (2008); Sankey et al (2008); Smith et al (2007); Souza et al (2003); Twele (2004), Vereverbeke et al (2012b) and Vila and Barbosa (2010). Multiple Endmember Spectral Mixture Analysis (MESMA), a modification of SMA, enables the use of multiple endmembers within a scene, making it possible to test different combinations of endmembers for each pixel in the image (Roberts et al, 1998).…”

“…Silva et al, 2011). Nevertheless, among the extrinsic factors that can modify the potential of an ecosystem to recover (resilience), burn severity understood as a measure of fire damage on vegetation cover is one of the most important (Bastos et al, 2011;Covington and Sackett, 1992;Neary et al, 1999;Röder et al, 2008;Smithwick et al, 2005).…”

“…3). Following previous studies (Hostert et al, 2003;Riaño et al, 2002;Röder et al, 2008;Silván-Cárdenas and Wang, 2014), all time series images were unmixed using the same endmember spectra set to avoid variability in the interpretation among all dates. The endmembers spectra were obtained from the first postfire image of time series because vegetation regeneration hampered the definition of ash image endmembers in the last Landsat images.…”

A new approach for land cover classification and change analysis: Integrating backdating and an object-based method

“…Because of the advantage of high temporal frequency, many quite subtle disturbance events of forest, such as defoliation, diseases, insect pests and regeneration, can be captured based on the change of vegetation spectral attribution (Goodwin et al, 2008;Hermosilla, Wulder, White, Coops, & Hobart, 2015;Zhu, Woodcock, & Olofsson, 2012). In addition to its wide applications in forest ecosystems, such method has also been applied to quantify changes of impervious surfaces in urban environments (Powell, Cohen, Yang, Pierce, & Alberti, 2008;Schneider, 2012), coral reef health (Palandro et al, 2008) and fire events (Röder, Hill, Duguy, Alloza, & Vallejo, 2008). Pre-classification change detection techniques, whether using dense time series image data or not, generally only generates "change" vs. "no-change" maps, but do not specify the type of change (Berberoglu & Akin, 2009;Lu et al, 2004;Singh, 1989).…”