This paper presents the Coastal Altimetry Waveform Retracking Expert System (CAWRES), a novel method to optimise the Jason satellite altimetric sea levels from multiple retracking solutions. CAWRES' aim is to achieve the highest possible accuracy of coastal sea levels, thus bringing measurement of radar altimetry data closer to the coast. The principles of CAWRES are twofold. The first is to reprocess altimeter waveforms using the optimal retracker, which is sought based on the analysis from a fuzzy expert system. The second is to minimise the relative offset in the retrieved sea levels caused by switching from one retracker to another using a neural network. The innovative system is validated against geoid height and tide gauges in the Great Barrier Reef, Australia for Jason-1 and Jason-2 satellite missions. The regional investigations have demonstrated that the CAWRES can effectively enhance the quality of 20 Hz sea level data and recover up to 16% more data than the standard MLE4 retracker over the tested region. Comparison against tide gauge indicates that the CAWRES sea levels are more reliable than those of Sensor Geophysical Data Records (SGDR) products, because the former has a higher (≥0.77) temporal correlation and smaller (≤19 cm) root mean square errors. The results demonstrate that the CAWRES can be applied to coastal regions elsewhere as well as other satellite altimeter missions.
The Royal Belum forest reserve is one of the oldest tropical rainforests in the world and it is one of the largest virgin forest reserves in Malaysia. However, not many studies have been conducted to understand the ecology of this forest. In this study we estimated the aboveground biomass (AGB) of the forest using diameter at breast height (DBH) and height of trees (h), tree species and hemispherical photographs of tree canopy. We estimated AGB using five allometric equations. Our results demonstrated that the AGB given by the one tree species specific allometric equation does not show any significant differences from the values given by the non-tree species specific allometric equations at tree and plot levels. The AGB of Intsia bijuga species, Koompassia malaccensis species and Shorea genera were comparatively higher, owing to their greater wood density, DBH and h. This has added importance because some of these species are categorized as threatened species. Our results demonstrated that mean AGB values in this forest (293.16 t ha -1 ) are the highest compared to some studies of other areas in Malaysia, tropical Africa and tropical Bazilian Amazonia, implying that the Royal Belum forest reserve, is an important carbon reservoir.
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