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Assessing intra-annual vegetation regrowth after fire using the pixel based regeneration index
Authors:S Lhermitte  J Verbesselt  WW VerstraetenS Veraverbeke  P Coppin
Institution:
  • a Centro de Estudios Avanzados en Zonas Aridas (CEAZA), Universidad de la Serena, La Serena, Chile
  • b M3-BIORES, Biosystems Department, Katholieke Universiteit Leuven, Leuven, Belgium
  • c CSIRO Sustainable Ecosystems, Private Bag 10, Clayton South, VIC 3169, Australia
  • d Department of Geography, Ghent University, Ghent, Belgium
  • e Wageningen University and Research Centre, Droevendaalsesteeg 3, 6708 PB Wageningen, Netherlands
  • Abstract:Several remote sensing studies have discussed the potential of satellite imagery as an alternative for extensive field sampling to quantify fire-vegetation impact over large areas. Most studies depend on Landsat image availability with infrequent image acquisition dates and consequently are limited for assessing intra-annual fire-vegetation dynamics or comparing different fire plots and dates. The control pixel based regeneration index (pRI) derived from SPOT-VEGETATION (VGT) normalized difference vegetation index (NDVI) is used in this study as an alternative to the traditional bi-temporal Landsat approach based on the normalized burn ratio (NBR). The major advantage of the pRI is the use of unburnt control plots which allow the expression of the intra-annual variation due to regeneration processes without external influences. In the comparison of Landsat and VGT data, (i) the inter-annual differences between the bi-temporal and control plot approach were contrasted and (ii) metrics of pRI were derived and compared with the inter-annual dynamics of both VGT and Landsat data. Results of these comparisons, demonstrate the overall similarity between NBR and NDVI data, stress the importance of the elimination of external influences (e.g., phenological variations), and emphasize the failure of including post-fire vegetation responses in bi-temporal Landsat assessments, especially in quickly recovering ecotypes with a strong annual phenological cycle such as savanna. This highlights the importance of using high frequency multi-temporal approaches to estimate fire-vegetation impact in temporally dynamic vegetation types.
    Keywords:Forest fire  Monitoring  Temporal  Spatial  Vegetation
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