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Multi-frequency synthetic aperture radar (SAR) data was acquired over the Macquarie Marshes Nature Reserve in north central New South Wales (NSW), Australia, to demonstrate the potential of imaging radar for mapping and monitoring wetland extent and inundation patterns in an inland, semi-arid wetland environment. A sequence of ALOS PALSAR and TerraSAR-X images acquired between January 2007 and April 2008 captured the wetlands in three successive phases: dry, wet and transitional. Visual observation of multi-temporal and multi-frequency SAR backscatter data confirmed the capacity of SAR to respond to changes in surface water, soil moisture and biomass. Longer wavelength L-band SAR provides a tool for discriminating wetlands, mapping surface water and detecting below-canopy inundation. Shorter wavelength X-band SAR provides a tool for detecting flushes in growth of vegetation in response to higher soil moisture from flooding. PALSAR data demonstrated a high capacity for discrimination of different wetland classes, while TerraSAR-X data was less suited to discriminating between cover types. The integration of X- and L-band data revealed the extent of floodplain inundation and presence of aquatic vegetation in ponded areas. Given a stable, well-calibrated time-series of SAR data, change analysis provides a mechanism for understanding the hydrological and/or ecological change in an area. In the longer term, it is envisioned that radar will provide a valuable tool within an operational system for monitoring the impact of environmental flows in NSW inland wetlands.

Mitchell, A. L., Lucas, R. M., Pfitzner, K., Milne, A. K., Finlayson, M. (2007). A new map of mangroves for Kakadu National Park, Northern Australia, based on stereo aerial photography. Aquatic Conservation-Marine and Freshwater Ecosystems, 17(5), 446-467.

An integrated remote sensing/field ecology project linked the use of synthetic aperture radar (SAR) and aerial photography to studies of landscape spatial heterogeneity and bird community ecology. P-, L-, and C-band SAR data, collected over a section of Kakadu National Park in Australia's Northern Territory during the Joint NASA/Australia DC-8 data acquisition campaign, were analyzed in light of field data integrating vegetation structure and floristics with bird abundances across a heterogeneous study site. Results indicate that SAR data are able to discern structural differences relevant to bird habitat quality within floristically homogeneous stands, while multispectral sensors successfully identified floristic differences among habitat types. Simplifying indices of bird diversity showed ambiguous changes across the site; however, the abundances of individual species were observed to change significantly across both floristic and structural gradients. These results suggest that efforts to map bird diversity should focus on species-specific habitat relationships and that some measure of vegetation structure is needed to understand bird habitat. The approach employed here advances the use of SAR data in the three-dimensional mapping of animal habitats from remotely sensed data, and extends current capabilities for mapping and modeling large-scale patterns in the distribution of biological diversity.

The arid zone of Australia is an environment with ‘boom and bust’ dynamics; where years of drought can be followed by periodic flash flooding. Major floods occurred along 500km of the Paroo River in March 2010 at levels unequaled since 2000. Dual polarization (HH/HV) L-Band synthetic aperture radar (SAR) data was obtained from the Japanese Advanced Land Observing Satellite (ALOS) to evaluate its use for mapping flooding over an area of high conservation value floodplain wetlands. The data were shown to be highly informative for mapping flooded classes and provide an alternative data source to optical imagery in the presence of cloud cover. Due to radar speckle, segmentation was used to partition the scenes within eCognition Developer. Classification was performed on image objects using decision rules based on field verified radar backscatter thresholds of classes and change detection. The methods developed for single and multiple images provide a framework for operational mapping and monitoring water over time, as well as a rapid response strategy for flood emergencies. Future work on image transforms and research on the interoperability of SAR and optical data will aim to improve differentiation of wetland classes.

The Kokoda Track area of Papua New Guinea is geographically diverse, with terrain varying from coastal areas to steep mountains, and biomes that extend from mangroves, to grasslands and savannas, and primary forests. The area is the subject of conservation measures using remotely sensed data in a collaboration between the Australian and Papua New Guinea governments. We describe this Kokoda Track initiative and the land cover mapping to be used as a basis for land use planning. We discuss hydromorphological analysis and land cover classification extracted from Interferometric Synthetic Aperture Radar (SAR) imagery. Our land cover analysis has employed two classification techniques, both object-based, and has included texture measures calculated from SAR imagery. The output is a high resolution classification product, to be used by local government stakeholders.

Landsat digital data is used to map land cover in the Willandra Lakes World Heritage Region in the semi-arid region of New South Wales. An unsupervised classification using a migrating means clustering algorithm followed by a maximum-likelihood classification procedure was found to be the most discriminating method of classifying land cover. The results of applying three change-detection routines to multitemporal data sets of selected sites within the region are presented and discussed.

The great medieval settlement of Angkor in Cambodia [9th–16th centuries Common Era (CE)] has for many years been understood as a “hydraulic city,” an urban complex defined, sustained, and ultimately overwhelmed by a complex water management network. Since the 1980s that view has been disputed, but the debate has remained unresolved because of insufficient data on the landscape beyond the great temples: the broader context of the monumental remains was only partially understood and had not been adequately mapped. Since the 1990s, French, Australian, and Cambodian teams have sought to address this empirical deficit through archaeological mapping projects by using traditional methods such as ground survey in conjunction with advanced radar remote-sensing applications in partnership with the National Aeronautics and Space Administration (NASA)/Jet Propulsion Laboratory (JPL). Here we present a major outcome of that research: a comprehensive archaeological map of greater Angkor, covering nearly 3,000 km 2 , prepared by the Greater Angkor Project (GAP). The map reveals a vast, low-density settlement landscape integrated by an elaborate water management network covering >1,000 km 2 , the most extensive urban complex of the preindustrial world. It is now clear that anthropogenic changes to the landscape were both extensive and substantial enough to have created grave challenges to the long-term viability of the settlement.

The ALOS Kyoto & Carbon Initiative is an international collaborative project led by the JAXA Earth Observation Research Center (EORC). It forms the continuation of JAXA's on-going JERS-1 SAR Global Rain Forest and Global Boreal Forest Mapping project(GRFM/GBFM) into the era of the Advanced Land Observation Satellite (ALOS). The ALOS K & C Initiative has been set up to support the data and information needs required by international environmental Conventions; Carbon Cycle scientists and Environmental Conservation programs (referred below to as the CCCs). Led and coordinated by EORC JAXA, the Initiative is being undertaken by an international Science Team and focuses primarily on defining and optimizing the provision of data products and validated thematic information derived from in-situ and satellite sensors focusing on data acquired from the Phased Array L-band Synthetic Aperture Radar (PALSAR) on-board the Advanced Land Observing Satellite (ALOS). The objective of the ALOS K & C Initiative is to define, develop and validate thematic products derived from ALOS PALSAR data that can be used to meet specific information requirements relating to the CCCs. A key component of this work has been the development of a systematic data acquisition strategy for ALOS which comprises fixed, systematic global observation plans for PALSAR. The strategy is implemented as a top-level foreground mission and with a priority level second only to that of emergency observations. With emphasis on acquiring repetitive and consistent data over continental scales, it ensures that adequate data will be collected to allow the required thematic output products to be developed on a timely basis. The K & C Initiative is based on the three coordinated themes relating to global biomes; Forests, Wetlands, Deserts and Semi-Arid Regions, and a fourth theme dealing with the generation of regional ALOS PALSAR Mosaics. A key word for the Initiative is regional- scale applications and product development, with data requirements in the order of hundreds or thousands of PALSAR scenes for each prototype area. Each theme has identified key products that can be generated from the PALSAR data including land cover, forest change mapping and forest biomass and structure analysis; global wetland inventory compilation and landscape change determination; and freshwater resources and desertification. Each of the products developed will be generated using a combination of PALSAR imagery, in situ measurements and ancillary datasets.An international Scientific Advisory Panel has been established to maintain the scientific relevance of project design and to ensure alignment with other relevant international efforts (e.g. GOFC/GOLD, IGOL, GTOS/TCO). The panel consists of scientists active in the fields of carbon modeling and biophysical parameter retrieval; SAR and image processing, as well as and representatives from GOFC, TCO, FAO, space agencies, universities and public research institutions.

Northern Australia exhibits an extremely seasonal climate and this is reflected in the change in vegetation communities present in a given area of wetland. The monsoonal nature of this climate means a huge variation in the amount of water available to plant life both on and surrounding the floodplains of the major river systems. Kakadu National Park, a heritage listed and Ramsar identified wetland of international significance, has a long history of scientific study an ideal study site on which to conduct studies such as this. Changes within the wetland areas in the park have been noted since the early 1980s, but have been poorly quantified. Many of the changes are related to the timing of the onset of the monsoon, the period of inundation and the location of the major flooding. However neither multispectral or hyperspectral sensors are able to capture information at the onset of the monsoon due to perpetual cloud coverage. Radar has the unique ability to image through cloud and hence 27 Standard and ScanSAR images were collected over the region from 1996 to 2001. The majority of the images were S4 ascending, with ScanSAR narrow collected simultaneously. The images were co-registered allowing comparison of the same geographic location through time. The simultaneous ScanSAR images allowed assessment of the technique over a wider swath, yielding results on a regional rather than local scale. Radar reflection is intimately related to the moisture content of the target due to the influence of moisture upon the dielectric constant. A modified Gaussian Markov Random Field Model Segmentation was used to cluster areas exhibiting similar radar response at each successive date in the time series. The ability to segment and extract reflection statistics for the same geographic location for each image in the series allows the construction of temporal curves, indicating change in the target material's dielectric constant over time.

The aim of this paper is to compare radar backscatter response from imaging SAR systems operating in C-, L- and P-band wavelengths over wetland environments found in the Kakadu World Heritage Region, Northern Territory, Australia. Determining the spatial pattern of inundation in monsoonally domination wetlands and the sequence of floodplain drying is an important first step to understanding the hydrologic, geomorphic and ecological processes operating in these landscapes. SIR-C data acquired in 1994 and AIRSAR multiband imagery obtained over the study site in October 1993 and again in November 1996 were available for analysis along with MOMS-2P optical data. Radarsat imagery was acquired on a near monthly basis during 1998 for the study site. The data were calibrated, geo-referenced and overlain in order to determined water boundaries and to map the pattern of receding water levels. Both Standard Beam 4 and ScanSAR data has been analysis to evaluate the usefulness of C-band horizontally polarised data for wetland mapping. The identification of saturated condition under open canopies commonly found in Australian monsoonal forests can be demonstrated at all three wavelengths. Significantly multirate radarsat imagery proved used in detecting the distribution and extent of water under trees in all seasonal conditions; in mapping the pattern of floodwater recession and in assessing the drying out phases observed in this wetland environment.

Moisture is a major determinant of the dielectric properties of most non-metallic materials and soils and vegetation in particular. Natural surfaces that are subjected to intense wet dry cycles will exhibit a change in dielectric constant and hence reflective capability. An investigation of these changes with time indicates that understanding the topographic setting alone will yield significant data about soil moisture and drainage patterns. Vegetation also exhibits a greater moisture content when in close proximity to the water level. Vegetation laterally separated from the water hays off due to lack of available soil moisture and becomes essentially invisible to radar. Analysis of three multi temporal radar images obtained by Radarsat during the period of 1998-1999 indicates significant lateral drainage of floodplain surfaces in Northern Australia. A region of the South Alligator River floodplain from within Kakadu National Park was surveyed to ascertain soil properties and topography. The images were co-registered and segmented by means of a Gaussian Markov random field model in order to highlight areas of similar reflectance characteristics for each of the three images. Segmentation allowed the comparison of boundaries between flooded and dry areas of the floodplain over the course of the wet dry cycle. The drying effect exhibited in the segments is directly related to the topography of the floodplain surface. Results indicate a novel new method for vegetation, soil and topographic mapping in the wet/dry tropics of Northern Australia.

This paper examines the use of time-series of stereo aerial photographs for quantifying changes in the extent and height of mangrove communities. For the West Alligator River, Kakadu National Park, Australia, black and white and colour stereo aerial photographs of mangroves were acquired in 1950 and 1991 respectively. Digital ortho-images were generated for each date, and maps of mangrove extent were obtained by applying an unsupervised classification to each image. Digital elevation models (DEMs) of the mangrove canopy were derived from the stereo pairs. The comparison of mangrove extent suggested that substantial changes had occurred over the 41-year period, largely in response to saltwater intrusion. Changes in the height of mangroves were also observed but were difficult to quantify due to the poor quality of the 1950 DEM. The study concludes that time-series comparisons of aerial photographs are invaluable for assessing change in mangroves over periods of up to 4-5 decades.

The value of Landsat data for spatial analysis in land cover studies is well known. Potentially as valuable is its use in forecasting and monitoring temporal land cover changes such as those associ...