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Natural hazards and human-made disasters are increasing in magnitude and frequency due to climate change. The increase in response assets across agencies is complicating synchronization and communication during lifesaving operations. Technological advancements in wireless communication systems are improving resource tasking, tracking, and awareness but are vulnerable to interruption from the destruction inflicted by natural hazards. However, satellite technology offers solutions to safeguard lifesaving coordination in austere environments. Through a focused review of the relevant literature and policy documents, this study analyzes disaster response command and control, emerging communication capabilities, and satellite technology related to developing a common operating picture for all actors. The aim is to provide practicing emergency managers with the means to overcome communication gaps in wireless and satellite technology to maintain this common picture, save lives in the wake of disasters, and protect emergency responders during hazardous mass rescue operations. Results indicate that communication technology does aid emergency managers in the highly pressurized response environment but the systems being relied upon are themselves vulnerable to disasters. The existing literature also establishes that response actors are leveraging satellite technology to fill gaps in communications connectivity during disasters to reduce risk, which has both national and international implications.

Since 2008 there have been a limited number of Landsat 5 thematic mapper (TM) images acquired between April and October in Australia. Consequently, TM imagery may not be available at the desired time of year for some monitoring applications. IRS (Indian Remote Sensing) P6 LISS (Linear Imaging and Self Scanner) III imagery has been acquired over Australia since 2008 and represents an alternative, Landsat-like, data source to fill the Landsat 5 TM temporal gap. To be useful for the continuation of long-term monitoring, the LISS III imagery needs to provide similar surface-reflectance estimates to Landsat 5 TM. A time series of spatially averaged sensor-radiance estimates for 2008 was derived from Landsat 5 TM, Landsat 7 enhanced thematic mapper plus (ETM+) and IRS P6 LISS III imagery for two highly reflective, spectrally invariant, claypans in Queensland, Australia. The radiance values were converted to surface reflectance using the atmospheric transfer modelling code 6S. Adjustment factors, to account for ...

A range of programs exist globally that use satellite imagery to derive estimates of vegetation-cover for developing vegetation-management policy, monitoring policy compliance and making natural-resource assessments. Consequently, the satellite imagery must have a high degree of geometric accuracy. It is common for the accuracy assessment to be performed using the root mean square error (RMSE) only. However the RMSE is a non-spatial measure and more rigorous accuracy assessment methods are required. Currently there is a lack of spatially explicit accuracy assessment methods reported in the literature that have been demonstrated to work within operational monitoring programs. This paper reports on the method used by the Statewide Landcover and Trees Study (SLATS) to georegister and assess the registration accuracy of Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced Thematic Mapper (ETM+) imagery in Queensland, Australia. A geometric baseline with high accuracy (a statewide mean RMSE of 4.53 m) was der...

The Statewide Landcover and Trees Study (SLATS) use both Landsat-7 ETM+ and Landsat-5 TM imagery to monitor short-term woody vegetation changes throughout Queensland, Australia. In order to analyse more subtle long-term vegetation change, time-based trends resulting from artefacts introduced by the sensor system must be removed. In this study, a reflectance-based vicarious calibration approach using high-reflectance, pseudo-invariant targets in western Queensland was developed. This calibration procedure was used to test the existing calibration models for ETM+ and TM, and develop a consistent operational calibration procedure which provides calibration information for the MSS sensors. Ground based data, sensor spectral response functions and atmospheric variables were used as input to MODTRAN radiative transfer code to estimate top-of-atmosphere radiance. The estimated gains for Landsat-7 ETM+ (1999–2003), -5 TM (1987–2004), -5 MSS (1984–1993) and -2 MSS (1979–1982) are presented. Results confirm the stability and accuracy of the ETM+ calibration, and the suitability of this data as a radiometric standard for cross-calibration with TM. Vicarious data support the use of the existing TM calibration model for the red and two shortwave-infrared bands. However, alternative models for blue, green and near-infrared bands are presented. The models proposed differ most noticeably at dates prior to 1995, with differences in estimated gains of up to 9.7%, 10.8% and 6.9% for the blue, green and near-infrared bands respectively. Vicarious gains for Landsat-2 MSS and Landsat-5 MSS are presented and are compared with those applied by the on-board calibration system. Updated calibration coefficients to scale MSS data to the SLATS vicarious measurements are given. The removal of time based calibration trends in the SLATS data archive will enable the measurement of vegetation changes over the 26 year period covered by Landsat -2, -5 and -7.

The FA composition of the pelagic jellyfish Aurelia sp. collected from off-shore Western Australia waters was determined by capillary GC and GC-MS, with confirmation of PUFA structure performed by analysis of 4,4-dimethyloxazoline derivatives. PUFA constituted 47.6% of the total FA, with the essential PUFA eicosapentaenoic acid (EPA), arachidonic acid, and DHA accounting for 34%. Of particular interest, the unusual very long chain PUFA 6,9,12,15,18,21-tetracosahexaenoic acid (THA, 24:6n-3) was present at 9.3%, and the rarely reported 6,9,12,15,18-tetracosapentaenoic acid (24:5n-6) also was detected at 0.8%. To our knowledge, this represents the first report of THA as a major PUFA in a pelagic marine organism.

Data from 57 permanent monitoring sites are used to document the growth in woody vegetation and estimate the carbon sink in 27Mha of eucalypt woodlands (savannas), contained withii c. 6OMha of grazed woodlands in Queensland (northeast Australia). The study sites are shown to be representative of the environment and structure of the eucalypt woodlands in the defined study area. Mean basal area increment for all live woody plants in 30 long-tenn sites, with an average initial basal area of 11.86 + 1.38 (SE)m2ha-', was 1.06m2ha-' over a mean 14years timeframe. The majority of the measurement period, commencing between 1982 and 1988, was characterized by belowaverage rainfall. The increase in live tree basal area was due primarily to growth of existing trees (3.1Zm2ha-'1 rather than establishment of new plants (0.25m2ha-I) qd was partly offset by death (2.31m2ha-'1. A simple but robust relationship between stand basal area and stand biomass of all woody species was developed for the eucalypt dominant woodlands. Analysis of above-ground carbon stocks in live and standing dead woody plants gave a mean net above-ground annual carbon increment for all 57 sites of 0.53 t C ha-' y-l, similar to values estimated elsewhere in world savannas. Published root: shoot ratios were used to infer C flux in woody mot systems on these sites. This results in an estimated sink in above- and below-ground biomass of 18MtCy-' over the eucalypt woodlands studied, and potentially up to 35MtCy-I if extended to all grazed woodlands in Queensland. It is suggested that introduction of livestock grazing and altered fire regimes have triggered the change in tree-grass dominance in these woodlands. Thus, change in carbon stocks in the grazed woodlands of Queensland is identified as an important component of human-induced greenhouse gas flux in Australia, equivalent in magnitude to c. 25% of the most recently published (1999) total estimated national net emissions. The latter inventory takes into account emissions from land clearing, but does not include the sink identified in the pment study. This sequestration also represents a small but significant contribution to the global terrestrial carbon sink.

LiDAR remote sensing can be considered a key instrument for studies related to quantifyingthe vegetation structure. We utilised LiDAR metrics to estimate plot-scale structuralparameters of subtropical rainforest and eucalyptus dominated open forest in topographicallydissected landscape, in North-eastern Australia. This study is considered an extremeapplication of LiDAR technology for structurally complex subtropical forests in complexterrain. Thirty-one LiDAR metrics of vegetation functional parameters were examined.Multiple linear regression models were able to explain 62% of the variability associated withbasal area, 66% for mean dbh, 61% for dominant height and 60% for foliage projective coverin subtropical rainforest. In contrast, mean height (adjusted R2 = 0.90) and dominant height(adjusted R2 = 0.81) were predicted with highest accuracy in the eucalyptus dominated opencanopy forest. Nevertheless, the magnitude of error for predicting structural parameters ofvegetation was much higher in subtropical rainforest than those documented in the literature.Our findings reinforced that obtaining accurate LiDAR estimates of vegetation structure is afunction of the complexity of horizontal and vertical structural diversity of vegetation.

There are many remote sensing studies where it is desirable to have a radiometrically matched time series of images or image mosaics., This paper examines the use of bi-directional reflectance distribution function (BRDF) models for radiometric correction of Landsat 7 ETM+ imagery. It describes a simple radiometric correction method which combines: a top-of-atmosphere reflectance adjustment with an empirical BRDF model. The model parameters were derived from an overlapping sequence of Landsat 7 images.

Landsat TM imagery is being used to monitor landcover change in a number of operational projects in Australia. Most recently, the Australian Greenhouse Office (AGO) has undertaken a project to provide historical monitoring of changes in woody vegetation across the continent. In order to map and monitor landcover changes in a consistent and comparable manner across broad areas, it is highly desirable to have a consistently calibrated numerical base. To this end, the AGO has supported the creation of a rectification and calibration base for Australia, using Landsat TM data; 369 Landsat 7 images from the period July 1999 to September 2000 were purchased from the Australian Centre for Remote Sensing (ACRES). This paper describes the processing and production of the calibration base from these images.

Concern about the risk of harmful human-induced climate change has resulted in international efforts to reduce greenhouse gas emissions to the atmosphere. We review the international and national context for consideration of greenhouse abatement in native vegetation management and discuss potential options in Queensland. Queensland has large areas of productive or potentially productive land with native woody vegetation cover with approximately 76 million ha with woody cover remaining in 1991. High rates of tree clearing, predominantly to increase pasture productivity, continued throughout the 1990s with an average 345,000 ha/a estimated to have been cleared, including non-remnant (woody regrowth) as well as remnant vegetation. Estimates of greenhouse gas emissions associated with land clearing currently have a high uncertainty but clearing was reported to contribute a significant proportion of Australia's total greenhouse gas emissions from 1990 (21%) to 1999 (13%). In Queensland, greenhouse emissions from land clearing were estimated to have been 54.5 Mt CO2-e in 1999. Management of native vegetation for timber harvesting and the proliferation of woody vegetation (vegetation thickening) in the grazed woodlands also represent large carbon fluxes. Forestry (plantations and native forests) in Queensland was reported to be a 4.4 Mt CO2-e sink in 1999 but there are a lack of comprehensive data on timber harvesting in private hardwood forests. Vegetation thickening is reported for large areas of the c. 60 million ha grazed woodlands in Queensland. The magnitude of the carbon sink in 27 million ha grazed eucalypt woodlands has been estimated to be 66 Mt CO2-e/a but this sink is not currently included in Australia's inventory of anthropogenic greenhouse emissions. Improved understanding of the function and dynamics of natural and managed ecosystems is required to support management of native vegetation to preserve and enhance carbon stocks for greenhouse benefits while meeting objectives of sustainable and productive management and biodiversity protection.

This paper describes the development of a regression model for predicting foliage projective cover (FPC) using an extensive set of over 2000 field observations for Queensland, Australia. The model includes Landsat TM and ETM+ imagery and a climatological ancillary variable, vapour pressure deficit. The resulting model was validated using independent site data and preliminary validation against FPC estimates from airbourne laser scanner data is presented. Results suggest the model is robust and performing well over a range of soil types and vegetation communities. This regression-based methodology is currently included in the process of monitoring annual woody vegetation change over Queensland and will form the basis of new products for monitoring longer term trends in FPC

The Statewide Landcover and Trees Study (SLATS) has used both Landsat-5 TM and -7 ETM+ imagery to monitor short-term woody vegetation changes throughout Queensland. In order to analyse long-term vegetation change, time-based trends that are an artifact of the sensor system must be removed. Although the calibration trends of TIM and ETM+ are well described, information on the calibration of the older Landsat-2 and -5 MSS sensors is relatively scarce. This paper describes the use of three pseudo-invariant target sites in western Queensland to achieve an operational calibration of TM and ETM+ data. Following the success of the current study, these targets will be used in the near future to achieve sensor specific calibrations for the Landsat-2 and -5 MSS SLATS data