Spectral mixture analysis to assess post-fire vegetation regeneration using Landsat Thematic Mapper imagery: Accounting for soil brightness variation

Burned Area Detection and Burn Severity Assessment of a Heathland Fire in Belgium Using Airborne Imaging Spectroscopy (APEX)

“…Fire severity quantifies the immediate short-term fire effects on the local environment, whereas burn severity quantifies both the short and long-term impact as it includes response processes such as vegetation recovery [21,22]. In the last few decades, remote sensing techniques have emerged in wildfire studies thanks to their: (i) synoptic overview [23][24][25][26], (ii) vast coverage [21,[27][28][29]; and (iii) repeated temporal sampling [21,27,30]. Furthermore, (iv) remote and inaccessible parts are easily studied [21,25,31], and (v) remote sensing studies are often cheaper and faster than detailed time-consuming field campaigns [21,24,29,30].…”

“…In the last few decades, remote sensing techniques have emerged in wildfire studies thanks to their: (i) synoptic overview [23][24][25][26], (ii) vast coverage [21,[27][28][29]; and (iii) repeated temporal sampling [21,27,30]. Furthermore, (iv) remote and inaccessible parts are easily studied [21,25,31], and (v) remote sensing studies are often cheaper and faster than detailed time-consuming field campaigns [21,24,29,30]. Various methods have been developed for burn severity assessments, including spectral indices (SIs) [32], simulation techniques [28,29,33], and spectral mixture analysis [34][35][36][37][38][39][40].…”

Advances in Remote Sensing of Post-Fire Vegetation Recovery Monitoring - A Review

“…Where Landsat-based studies allow only a few cloud-free images a year (Ju and Roy 2008), satellite sensors with high temporal frequency permit the construction of continuous time series. More recently, several authors have explored this data type for assessing post-fire effects (Idris et al 2005;Goetz et al 2006;Telesca and Lasaponara 2006;Li et al 2008;van Leeuwen 2008;Alcaraz-Segura et al 2010;Gouveia et al 2010;Lhermitte et al 2010;Segah et al 2010;van Leeuwen et al 2010;Lhermitte et al 2011;Veraverbeke et al 2012a;Veraverbeke et al 2012c). Thanks to this it is possible to discriminate between regeneration patters and seasonal fluctuations (Veraverbeke et al 2010b;Lhermitte et al 2011;Veraverbeke et al 2012b).…”

“…With regards to post-fire effects, rather few studies employed SMA to monitor post-fire vegetation responses (Riaño et al 2002;Peterson and Stow 2003;Roder et al 2008;Sankey et al 2008;Vila and Barbosa 2010;Veraverbeke et al 2012a). Although results of these studies were consistent, most of them were all restricted to simple linear SMA models in which only one spectrum was allowed for each endmember.…”

Quantifying Early-Seral Forest Composition with Remote Sensing

“…However, the spectral signal of early-seral forest regeneration (one to two years) following disturbance is often indistinct and may be confused with other vegetation life forms, coarse woody debris, and soil prior to canopy closure, which complicates the composition and structure mapping process using medium spatial resolution sensors such as Landsat (Veraverbeke et al, 2012). Nevertheless, the ability to map tree species recruitment and structure information so early in a forest's successional state (over large landscapes) would be a valuable asset for forest managers and scientists in providing insight into future forest development patterns in time and space (Veraverbeke et al, 2012).…”