Biodiversity conservation planning requires spatial data (Ferrier, 2003; Nagendra, 2001). Information on the spatial distribution of wildlife species, as well as the location and extent of their habitat, is essential in developing conservation strategies. However, traditional ground-based survey and mapping methods cannot always deliver the necessary information in a timely and cost-effective fashion (Gottschalk et al., 2005). This is particularly true when the mapping required is at the fine-scale level.
Remote sensing techniques offer solutions to the problems associated with ground-based collection of environmental data over large areas (Mason, et al., 2003). However, many of the contemporary remote sensing applications for habitat mapping have used relatively coarse-resolution imagery, and are therefore incapable of capturing fine-scale variables relevant to some wildlife species.The known habitat of threatened reptiles of the Queensland Brigalow Belt (QBB) includes areas with fallen leaf-litter, branches, hollow logs, rocky outcrops, native trees, old mature trees, soil cracks, and patches of scrub (Wilson, 2003). Such microhabitat attributes entail detailed, fine-resolution mapping. This partly explains why no fine-scale satellite-based habitat mapping has ever been done for threatened reptiles in the Brigalow Belt or elsewhere in Australia. The launch of recent radar (e.g. ALOS) and high spatial resolution (e.g. QuickBird) sensors offers new and exciting possibilities
Many of the habitat predictive models that ulitised satellite imagery have used relatively coarse-grained data (e।g. Boyd, et al., 2006; Pelkey, et al., 2003). Thus, they are only useful where the organism of concern has habitat requirements that can be identified adequately at coarse scales (Mason, et al., 2003). For the threatened reptiles of the Brigalow Belt, the identification and mapping of their habitat requires fine-scale resolution (e.g. 1:10,000) due to their habitat preferences. Reptiles require specific microhabitat characteristics within their preferred broad habitat type (Richardson, 2006).
These microhabitat attributes (e.g. ground cover, rock outcrops, soil cracks, low-lying shrubs, etc.) will need sensors that are capable of providing information about vegetation structure, surface roughness, biomass, micro-topography, etc. at a fine scale. Previous studies using radar imagery have demonstrated that many of these variables can be extracted (e.g. Hill et al., 2005; Held, et al., 2003; Lucas et al., 2006; Hewson and Taylor, 2000). However, as most of these radar sensors are either mounted on airborne systems or on satellite platforms that have implications on imagery costs or spatial resolution, their applications to fine-scale habitat mapping is limited or non-existent.The Advanced Land Observing Satellite (ALOS), launched last year, offers great potential to map reptile habitat. It has an active radar sensor using the L-band frequency (for better canopy penetration and surface rougness characterisation), and with fine spatial resolution (best of 7-10m) (JAXA, 2007). ALOS is also equipped with a 2.5m sensor suitable for generating high resolution digital elevation model (DEM). Coupled with the use of high resolution imagery operating in the optical wavelengths, the use of new generation radar imagery offers exciting new prospects for habitat mapping and monitoring.
Remote sensing techniques offer solutions to the problems associated with ground-based collection of environmental data over large areas (Mason, et al., 2003). However, many of the contemporary remote sensing applications for habitat mapping have used relatively coarse-resolution imagery, and are therefore incapable of capturing fine-scale variables relevant to some wildlife species.The known habitat of threatened reptiles of the Queensland Brigalow Belt (QBB) includes areas with fallen leaf-litter, branches, hollow logs, rocky outcrops, native trees, old mature trees, soil cracks, and patches of scrub (Wilson, 2003). Such microhabitat attributes entail detailed, fine-resolution mapping. This partly explains why no fine-scale satellite-based habitat mapping has ever been done for threatened reptiles in the Brigalow Belt or elsewhere in Australia. The launch of recent radar (e.g. ALOS) and high spatial resolution (e.g. QuickBird) sensors offers new and exciting possibilities
Many of the habitat predictive models that ulitised satellite imagery have used relatively coarse-grained data (e।g. Boyd, et al., 2006; Pelkey, et al., 2003). Thus, they are only useful where the organism of concern has habitat requirements that can be identified adequately at coarse scales (Mason, et al., 2003). For the threatened reptiles of the Brigalow Belt, the identification and mapping of their habitat requires fine-scale resolution (e.g. 1:10,000) due to their habitat preferences. Reptiles require specific microhabitat characteristics within their preferred broad habitat type (Richardson, 2006).
These microhabitat attributes (e.g. ground cover, rock outcrops, soil cracks, low-lying shrubs, etc.) will need sensors that are capable of providing information about vegetation structure, surface roughness, biomass, micro-topography, etc. at a fine scale. Previous studies using radar imagery have demonstrated that many of these variables can be extracted (e.g. Hill et al., 2005; Held, et al., 2003; Lucas et al., 2006; Hewson and Taylor, 2000). However, as most of these radar sensors are either mounted on airborne systems or on satellite platforms that have implications on imagery costs or spatial resolution, their applications to fine-scale habitat mapping is limited or non-existent.The Advanced Land Observing Satellite (ALOS), launched last year, offers great potential to map reptile habitat. It has an active radar sensor using the L-band frequency (for better canopy penetration and surface rougness characterisation), and with fine spatial resolution (best of 7-10m) (JAXA, 2007). ALOS is also equipped with a 2.5m sensor suitable for generating high resolution digital elevation model (DEM). Coupled with the use of high resolution imagery operating in the optical wavelengths, the use of new generation radar imagery offers exciting new prospects for habitat mapping and monitoring.
