Abstract:
Woody canopy cover (CC) is the simplesttwo dimensional metric for assessing the presence ofthe woody
component in savannahs, but detailed validated maps are not currently available in southern African
savannahs. A number of international EO programs (including in savannah landscapes) advocate and
use optical LandSAT imagery for regional to country-wide mapping of woody canopy cover. However,
previous research has shown that L-band Synthetic Aperture Radar (SAR) provides good performance at
retrieving woody canopy cover in southern African savannahs. This study’s objective was to evaluate,
compare and use in combination L-band ALOS PALSAR and LandSAT-5 TM, in a Random Forest environment,
to assess the benefits of using LandSAT compared to ALOS PALSAR. Additional objectives saw
the testing of LandSAT-5 image seasonality, spectral vegetation indices and image textures for improved
CC modelling. Results showed that LandSAT-5 imagery acquired in the summer and autumn seasons
yielded the highest single season modelling accuracies (R2 between 0.47 and 0.65), depending on the
year but the combination of multi-seasonal images yielded higher accuracies (R2 between 0.57 and 0.72).
The derivation of spectral vegetation indices and image textures and their combinations with optical
reflectance bands provided minimal improvement with no optical-only result exceeding the winter SAR
L-band backscatter alone results (R2 of ∼0.8). The integration of seasonally appropriate LandSAT-5 image
reflectance and L-band HH and HV backscatter data does provide a significant improvement for CC modelling
at the higher end of the model performance (R2 between 0.83 and 0.88), but we conclude that
L-band only based CC modelling be recommended for South African regions
