Satellite data track spatial and temporal declines in European beech forest canopy characteristics associated with intense drought events in the Rhön Biosphere Reserve, central Germany.

The increasing intensity and frequency of droughts under climate change demands effective ways to monitor drought impacts. We sought to determine how different satellite remote sensing sources influence our ability to identify temporal and spatial impacts on European beech forest canopy health during intense drought events. Imagery from three satellite series (MODIS, Landsat and Sentinel-2) was used to observe changes in canopy health during the intense droughts of 2003 and 2018 in the Rhön Biosphere Reserve, central Germany. Monthly normalized difference vegetation index (NDVI) anomalies were calculated for each satellite between 2000-2020 and compared against temperature, precipitation and the standardized precipitation evapotranspiration index (SPEI). Severe canopy impacts in 2003 and 2018 were associated with low NDVI in August and September. At the stand-scale, Sentinel-2 data allowed a spatially detailed understanding of canopy-level impacts, while MODIS provided the clearest temporal progression of the drought's impacts on the forest canopy. Low NDVI values were not exclusively associated with extremes of either temperature and precipitation individually; however, low canopy NDVI in August was associated with SPEI values below -1.5. Although the intense drought of 2018, as defined by meteorological parameters, peaked in July, canopy NDVI did not decline until August, highlighting that our ability to detect canopy impact during drought events is sensitive to the timing of image acquisition. No single satellite sensor affords a full picture of the temporal or spatial progression of drought impacts. Consequently, using sensors in tandem provides the best possible representation of canopy health during intense drought events.

Intercomparison of Evapotranspiration Over the Savannah Volta Basin in West Africa Using Remote Sensing Data.

This paper compares evapotranspiration estimates from two complementary satellite sensors - NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and ESA's ENVISAT Advanced Along-Track Scanning Radiometer (AATSR) over the savannah area of the Volta basin in West Africa. This was achieved through solving for evapotranspiration on the basis of the regional energy balance equation, which was computationally-driven by the Surface Energy Balance Algorithm for Land algorithm (SEBAL). The results showed that both sensors are potentially good sources of evapotranspiration estimates over large heterogeneous landscapes. The MODIS sensor measured daily evapotranspiration reasonably well with a strong spatial correlation (R²=0.71) with Landsat ETM+ but underperformed with deviations up to ~2.0 mm day-1, when compared with local eddy correlation observations and the Penman-Monteith method mainly because of scale mismatch. The AATSR sensor produced much poorer correlations (R²=0.13) with Landsat ETM+ and conventional ET methods also because of differences in atmospheric correction and sensor calibration over land.