The semi-empirical water cloud model can be implemented to derive spatial values of biophysical parameters from remotely sensed radar data for use throughout different disciplines of physical geography. The water cloud model formulation and development are detailed in this review paper, incorporating the major advances and publications related to the model.

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Abstract. The primary objective of this research was to assess changes in global vegetation photosynthesis between 1982 and 1999. Global-scale AVHRR NDVI data from the PAL and GIMMS data sets were analysed for 96% of the nonAntarctic land area of the Earth. The results showed that over 30% of the Earth's surface increased and less than 5% decreased in annual average photosynthesis greater than 4%. Although both the PAL and GIMMS data sets produced broadly similar patterns of change, there were distinct differences between the two data sets. Changes in vegetation photosynthesis were occurring in spatial clusters across the globe and were being driven by climate change, ENSO events and human activity.