Recovery of vegetation canopy after severe fire in 2000 at the Black Hills National Forest, South Dakota, USA

Background/Question/Methods Forest fires often result in various degrees of canopy loss in forested landscapes.  The subsequent trajectory of vegetation canopy recovery is important for ecosystem processes as the canopy controls photosynthesis and evapotranspiration. The loss and recovery of canopy are often measured by leaf area index (LAI) and vegetation indices, which are related to canopy photosynthetic capacity. In this study we used time series imagery from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on the Terra satellite over the period of 2000 – 2009 to track the recovery of vegetation canopy after fire. The Black Hills National Forest, South Dakota, USA, experienced an extensive wildfire starting on August 24, 2000 that burned a total area of 33,785 ha, most of which was ponderosa pine forest.

Results/Conclusions The MODIS data show that canopy photosynthetic capacity, as measured by LAI, recovered within 3 years (2001-2003), which was attributed to rapid emergence (recovery) of understory grass species after the fire event.  Satellite-based Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) at the burned sites also recovered within 3 years (2001-2003). Rapid recovery of LAI, NDVI and EVI at the burned sites make it difficult to use these variables for identifying and map burned sites several years after the fire event. In comparison, Land Surface Water Index (LSWI), calculated as a normalized ratio between near infrared and shortwave infrared bands (band 2 and band 6 (1628–1652 nm) in MODIS sensor), was able to identify and track the burned sites over the period of 2000 – 2009 at the recovery stage of understory grass canopy.  This research finding opens a window of opportunity to identify and map disturbances using imagery from those sensors with both NIR and SWIR bands, including Landsat 5 TM (dated back to 1984); furthermore, a longer record of disturbance and recovery help improve our understanding of disturbance regimes, simulations of forest succession and the carbon cycle.