Post-fire vegetation response as a proxy to quantify the magnitude of burn severity in tropical peatland

• Published in: International journal of remote sensing Vol. 34; no. 2; pp. 412 - 433
• Main Authors: Hoscilo, Agata, Tansey, Kevin J, Page, Susan E
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 20.01.2013
• Subjects: aboveground biomass; analysis of variance; Animal, plant and microbial ecology; Applied geophysics; Biological and medical sciences; Borneo; Earth sciences; Earth, ocean, space; ecosystems; Exact sciences and technology; fires; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Internal geophysics; Landsat; landscapes; regrowth; spectral analysis; Teledetection and vegetation maps; tree and stand measurements; trees; tropical forests; Borneo; Southeast Asia; South east Asia; Asia; Kalimantan Indonesia; Far East; Indonesia; Variable; tropical zone; vegetation; Malay Archipelago; measurement sensor; Spatial scale; Image; Spectral data; peat bogs; magnitude; Ratio; landscapes; biomass; Epigeal; Space remote sensing; Landsat; Regrowth; Tropical forest; Landsat satellite; Measurement in situ; Response; fires; correlation; Fire; Above ground plant part; Fire effect
• ISSN: 1366-5901; 0143-1161; 1366-5901
• DOI: 10.1080/01431161.2012.709328

In recent years, fires in tropical forests in Southeast Asia have become more frequent and widespread, resulting in an increased need to evaluate fire impacts at a landscape scale. We examine whether post-fire vegetation regrowth can be used as a proxy to evaluate burn severity in a peatland landscape in Central Kalimantan, Indonesian Borneo, that has been subject to frequent fires. Several single- and bi-temporal indices as well as spectral fraction endmembers derived from either a post-fire image or a combination of pre- and post-fire images obtained by the Landsat sensor were examined. Spectral data were correlated with vegetation variables obtained from in situ measurements collected 4 years after the last fire. Of the tested spectral data, the bi-temporal and single normalized burn ratio (dNBR and NBR) showed the strongest correlations with the sets of vegetation variables (i.e. total woody aboveground biomass, tree density, and number of trees <10 cm diameter at breast height (DBH)). The results of an analysis of variance (ANOVA) and Tukey's multiple comparison of means test confirmed that NBR, dNBR, and the normalized difference water index could delineate four regrowth classes, thus confirming their utility in separating areas subjected to a single fire from those affected by multiple fires (MFs) as well as for discrimination between fires of differing severity. The results (a) provide evidence of the long-lasting impact that MFs have on forest recovery in this ecosystem and (b) confirm that vegetation response can be used as a proxy to quantify burn severity in locations affected by MFs.