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Abstract: Quantifying the above ground biomass of tropical forests is critical for understanding the dynamics of carbon fluxes between terrestrial ecosystems and the atmosphere, as well as monitoring ecosystem responses to environmental change. Remote sensing remains an attractive tool for estimating tropical forest biomass but relationships and methods used at one site have not always proved applicable to other locations. This lack of a widely applicable general relationship limits the operational use of remote sensing as a method for biomass estimation, particularly in high biomass ecosystems. Here, multispectral Landsat TM and JERS-1 SAR data were used together to estimate tropical forest biomass at three separate geographical locations: Brazil, Malaysia and Thailand. Texture measures were derived from the JERS-1 SAR data using both wavelet analysis and Grey Level Co-occurrence Matrix methods, and coupled with multispectral data to provide inputs to artificial neural networks that were trained under four different training scenarios and validated using biomass measured from 144 field plots. When trained and tested with data collected from the same location, the addition of SAR texture to multispectral data showed strong correlations with above ground biomass (r =0.79, 0.79 and 0.84 for Thailand, Malaysia and Brazil respectively). Also, when networks were trained and tested with data from all three sites, the strength of correlation (r =0.55) was stronger than previously reported results from the same sites that used multispectral data only. Uncertainty in estimating AGB from different allometric equations was also tested but found to have little effect on the strength of the relationships observed. The results suggest that the inclusion of SAR texture with multispectral data can go someway towards providing relationships that are transferable across time and space, but that further work is required if satellite remote sensing is to provide robust and reliable methodologies for initiatives such as Reducing Emissions from Deforestation and Degradation (REDD+). [Copyright &y& Elsevier]

Abstract: Topographic mapping from remotely sensed imagery is carried out all over the world, using data from an ever-growing number of sensors. Traditional film cameras are gradually being replaced by digital cameras and scanners, but most topographic mapping still relies on sensors based on airborne platforms. This paper examines the potential of high resolution satellite sensor imagery for the updating of topographic mapping, from the perspective of a national mapping agency. After a review of satellites capable of being used for this purpose, several examples of mapping projects are presented. The paper ends with a look to the future, and asks whether satellite imagery can ever replace airborne (digital or analogue) photography for the makers of maps. It is concluded that high resolution satellite sensor imagery does have a role to play in the update of topographic mapping, especially in the detection of change. [Copyright &y& Elsevier]