EGU2020-15175, updated on 12 Jun 2020
https://doi.org/10.5194/egusphere-egu2020-15175
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Multi-temporal analysis of post-fire vegetation spectral recovery over European forests

Maria Floriana Spatola, Angelo Rita, Marco Borghetti, Francesco Ripullone, Agostino Ferrara, and Angelo Nolè
Maria Floriana Spatola et al.
  • School of Agricultural, Forest, Food and Environmental Sciences, University of Basilicata, Potenza, Italy

The disturbance and recovery of European Forest ecosystems are greatly affected by wildfires, requiring continued monitoring to observe vegetational structure altered over time. One of the most important parameters is “fire severity” defined as magnitude of environmental change caused by wildfires. Due to correlation between severity and post-fire recovery vegetation, fire severity is an  important indicator to define operations in the burned areas. Satellite based-data is becoming a key information for near real-time mapping and monitoring burned area after wildfire disturbances. Moderate resolution Imaging Spectroradiometer (MODIS) time-series data allows for both the capture of the initial disturbance and the ability to monitor the subsequent vegetation regeneration with spectral vegetation indices. In this study, the Google Earth Engine (GEE) platform, was used to analyse post-fire spectral recovery of European forests through the Normalized Difference Vegetation Index (NDVI) and the Relative Recovery Indicator (RRI) based on the Normalized Burn Ratio (NBR). We assessed Normalized Burn Ratio time series in order to determine trends in the short term rates of spectral recovery for three forest land cover classes and European Biogeographic regions disturbed by wildfire (2004-2013), using a series of 5-year post-disturbance time window. NBR pattern of mixed forests showed a lower variability than broadleaved and coniferous forest, indicating high resilience to environmental disturbances. Results indicate different trends of forest recovery according to different spectral indices analysed for European forest ecosystems. During the analysis period (2004-2013) we found that post-fire spectral recovery rates decreased over ten years of observation in each land cover classes and Biogeographic regions. These trends could be related to on-going climate changes affecting the Mediterranean region.

Keywords: Fire severity, Forest, Google Earth Engine, Modis (time series), Recovery, Spectral index, Wildfire.

 

How to cite: Spatola, M. F., Rita, A., Borghetti, M., Ripullone, F., Ferrara, A., and Nolè, A.: Multi-temporal analysis of post-fire vegetation spectral recovery over European forests, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15175, https://doi.org/10.5194/egusphere-egu2020-15175, 2020

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