'Lantana camara' L. (lantana) is a major problem globally and has been declared a weed of national significance (WoNS) in Australia due to its significant negative impacts on Australian biodiversity and agriculture. Development of remote sensing techniques and modelling approaches that can map lantana accurately and project its likely future distribution should be useful for formulation of more effective, long-term management plans. The research reported here comprises seven studies based on remote sensing and modelling techniques that should contribute to better mapping and projected modelling of lantana in an era of climate change. Four image fusion techniques, namely Brovey, Hue-Saturation-Value (HSV), Principal Components (PC) and Gram-Schmidt (GS) Spectral Sharpening, were investigated using Quickbird imagery to identify the most effective fusion algorithm for mapping lantana. The results identified GS and PC spectral sharpening techniques as the most effective for this purpose. Brovey transformation and HSV, on the other hand, performed poorly with much lower overall accuracies. Three commonly available satellite images of varying spectral, spatial and radiometric resolutions from Landsat TM, SPOT 5 and Quickbird were assessed for accuracy and cost effectiveness in lantana mapping. The most cost-effective option was provided by Landsat TM with no significant difference in overall accuracies between the three types of imagery.

'Merremia peltata' is a species with uncertain status in the island nations of the Pacific region. It has been designated introduced and invasive in some countries whereas it is considered native in others. Recent increase in its abundance across some island landscapes have led to calls for its designation as an invasive species of environmental concern with biological control being suggested as a control strategy. Climate change will add to the complications of managing this species since changes in climate will influence its range limits. In this study, we develop a process-oriented niche model of 'M. peltata' using CLIMEX to investigate the impacts of climate change on its potential distribution. Information on the climatic requirements of 'M. peltata' and its current geographic distribution were used to calibrate the model. The results indicate that under current climate, 273,132 km2 of the land area in the region is climatically unsuitable or marginal for 'M. peltata' whereas 664,524 km2 is suitable to highly suitable. Under current climate, areas of climatic suitability for 'M. peltata' were identified on the archipelagos of Fiji, Papua New Guinea, Solomon Islands and Vanuatu. By the end of the century, some archipelagos like Fiji, Hawaii, New Caledonia and Vanuatu will probably become more suitable while PNG and Solomon Islands become less suitable for 'M. peltata'. The results can be used to inform biosecurity planning, management and conservation strategies on islands.

Increasing anthropogenic impacts on biodiversity has been a cause for concern in Australia in recent years. Areas that hold high levels of endemic species and also face exceptional threats of destruction have been described as biodiversity hotspots. Ecological research focused on biodiversity hotspots will provide a better understanding of the flora and fauna of these regions and thus inform conservation strategies. Consequently, it is important to understand where biodiversity hotspots are located and how well they have been researched in the past. However, the choice of ecological research sites may be influenced by a variety of factors such as proximity to research institutions. This study utilized a geographic information system to investigate the spatial distribution of ecological research field sites in Australia and its territorial waters, the hotspots of the field sites around research institutions and the proximity of ecological research field sites from the main campus of the research institutions. Furthermore, these hotspots of ecological research were linked to biodiversity hotspots to identify the regions that were commonly depicted in the ecological literature and to identify others that may need more attention. We demonstrated that hotspots of ecological research were concentrated around research institutions, with a large number of field sites being located between 0 km and 500 km from the nearest institution, especially along the eastern coast. This study highlighted areas that have been the focus of much ecological research as well as areas that need more attention from ecologists to add new knowledge to Australian ecological science.

The production of palm oil (PO) is highly profitable. The economies of the principal producers, Malaysia and Indonesia, and others, benefit considerably. Climate change (CC) will most likely have an impact on the distribution of oil palms (OP) ('Elaeis guineensis'). Here we present modelled CC projections with respect to the suitability of growing OP, in Malaysia and Indonesia. A processoriented niche model of OP was developed using CLIMEX to estimate its potential distribution under current and future climate scenarios. Two Global Climate Models (GCMs), CSIRO-Mk3.0 and MIROC-H, were used to explore the impacts of CC under the A1B and A2 scenarios for 2030, 2070 and 2100. Decreases in climatic suitability for OP in the region were gradual by 2030 but became more pronounced by 2100. These projections imply that OP growth will be affected severely by CC, with obvious implications to the economies of (a) Indonesia and Malaysia and (b) the PO industry, but with potential benefits towards reducing CC. A possible remedial action is to concentrate research on development of new varieties of OP that are less vulnerable to CC.

Pacific island countries (PICs) are situated in a highly dynamic ocean-atmosphere interface, are dispersed over a large ocean area, and have highly populated urban centres located on the coastal margin. The built infrastructure associated with urban centres is also located within close proximity to the coastlines, exposing such infrastructure to a variety of natural and climate change-related hazards. In this research we undertake a comprehensive analysis of the exposure of built infrastructure assets to climate risk for 12 PICs. We show that 57% of the assessed built infrastructure for the 12 PICs is located within 500m of their coastlines, amounting to a total replacement value of US$21.9 billion. Eight of the 12 PICs have 50% or more of their built infrastructure located within 500m of their coastlines. In particular, Kiribati, Marshall Islands and Tuvalu have over 95% of their built infrastructure located within 500mof their coastlines. Coastal adaptation costs will require substantial financial resources, which may not be available in developing countries such as the PICs, leaving them to face very high impacts but lacking the adaptive capacity.

The aim of this study was to evaluate the impact of image fusion techniques on vegetation classification accuracies in a complex wetland system. Fusion of panchromatic (PAN) and multispectral (MS) Quickbird satellite imagery was undertaken using four image fusion techniques: Brovey, hue-saturation-value (HSV), principal components (PC), and Gram-Schmidt (GS) spectral sharpening. These four fusion techniques were compared in terms of their mapping accuracy to a normal MS image using maximum-likelihood classification (MLC) and support vector machine (SVM) methods. Gram-Schmidt fusion technique yielded the highest overall accuracy and kappa value with both MLC (67.5% and 0.63, respectively) and SVM methods (73.3% and 0.68, respectively). This compared favorably with the accuracies achieved using the MS image. Overall, improvements of 4.1%, 3.6%, 5.8%, 5.4%, and 7.2% in overall accuracies were obtained in case of SVM over MLC for Brovey, HSV, GS, PC, and MS images, respectively. Visual and statistical analyses of the fused images showed that the Gram-Schmidt spectral sharpening technique preserved spectral quality much better than the principal component, Brovey, and HSV fused images. Other factors, such as the growth stage of species and the presence of extensive background water in many parts of the study area, had an impact on classification accuracies.

The quantification, mapping and monitoring of biomass are now central issues due to the importance of biomass as a renewable energy source in many countries of the world. The estimation of biomass is a challenging task, especially in areas with complex stands and varying environmental conditions, and requires accurate and consistent measurement methods. To efficiently and effectively use biomass as a renewable energy source, it is important to have detailed knowledge of its distribution, abundance, and quality. Remote sensing offers the technology to enable rapid assessment of biomass over large areas relatively quickly and at a low cost. This paper provides a comprehensive review of biomass assessment techniques using remote sensing in different environments and using different sensing techniques. It covers forests, savannah, and grasslands/rangelands, and for each of these environments, reviews key work that has been undertaken and compares the techniques that have been the most successful.

Climate change and invasive species are now seen as two major contributors to global biodiversity change. The combined effects of these two factors have serious implications for biodiversity and agriculture. 'Lantana camara' L. ('sensu lato') (lantana) is a woody shrub that is highly invasive in many countries of the world including South Africa where it has a profound impact on biodiversity, water resources and agriculture. Strategies to manage and control this highly noxious weed will benefit from information on its likely potential distribution under current and future climate. CLIMEX, a species distribution modelling software, was used to develop a process-oriented niche model to estimate its potential distribution under current and future climate scenarios. Model calibration was carried out with phenological observations and geographic distribution records of lantana. The potential distribution of lantana under current climate showed a good match to its current distribution in South Africa. Under future scenarios, the climatically suitable areas for lantana were projected to contract in the northern provinces of Limpopo and Mpumalanga as well as coastal areas of Western Cape Province. However, lantana's potential distribution may expand further inland into new areas in KwaZulu-Natal and Eastern Cape provinces. The results suggest that lantana management initiatives in areas where climatic suitability is likely to decline should focus on controlling the density of invasion rather than curbing range expansion. On the other hand, areas where climatic suitability is projected to increase will require ongoing monitoring to prevent further range expansions.