This study used remotely-sensed phenology data derived from Advanced Very High Resolution Radiometer (AVHRR), in a fully supervised decision-tree classification based on the new biome map of South Africa. The objectives were: (i) to investigate the long-term spatial patterns and inter-annual variability in satellite-derived vegetation phenology in relation to the recently revised biome map and (ii) to identify the phenological attributes that distinguishes between the different biomes. The long term phenometrics gave ecologically-meaningful results which reflect the authors’ current understanding of the spatial patterns of production and seasonality of vegetation growth in southern Africa. Regression tree analysis based on remotely-sensed phenometrics performed as good as, or better than, previous climate-based predictors of biome distribution.
Reference:
Wessels, K.J., Steenkamp, K.C., Von Maltitz, G.P. et al 2009. Remotely sensed phenology for mapping biomes and vegetation functional types. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Cape Town, South Africa, 12-17 July 2009, pp 1034-1037
Wessels, K. J., Steenkamp, K. C., Von Maltitz, G. P., Archibald, S., Scholes, R., Miteff, S., & Bachoo, A. (2009). Remotely sensed phenology for mapping biomes and vegetation functional types. IEEE. http://hdl.handle.net/10204/4049
Wessels, Konrad J, Karen C Steenkamp, Graham P Von Maltitz, S Archibald, RJ Scholes, S Miteff, and A Bachoo. "Remotely sensed phenology for mapping biomes and vegetation functional types." (2009): http://hdl.handle.net/10204/4049
Wessels KJ, Steenkamp KC, Von Maltitz GP, Archibald S, Scholes R, Miteff S, et al, Remotely sensed phenology for mapping biomes and vegetation functional types; IEEE; 2009. http://hdl.handle.net/10204/4049 .
