Remotely sensed data for ecosystem analyses: Combining hierarchy and scene models

Remotely sensed data have been used extensively for environmental monitoring and modeling at a number of spatial scales; however, a limited range of satellite imaging systems often. constrained the scales of these analyses. A wider variety of data sets is now available, allowing image data to be selected to match the scale of environmental structure(s) or process(es) being examined. A framework is presented for use by environmental scientists and managers, enabling their spatial data collection needs to be linked to a suitable form of remotely sensed data. A six-step approach is used, combining image spatial analysis and scaling tools, within the context of hierarchy theory. The main steps involved are: (1) identification of information requirements for the monitoring or management problem; (2) development of ideal image dimensions (scene model), (3) exploratory analysis of existing remotely sensed data using scaling techniques, (4) selection and evaluation of suitable remotely sensed data based on the scene model, (5) selection of suitable spatial analytic techniques to meet information requirements, and (6) cost-benefit analysis. Results from a case study show that the framework provided an objective mechanism to identify relevant aspects of the monitoring problem and environmental characteristics for selecting remotely sensed data and analysis techniques.

Assessment of relationships between precipitation and satellite derived vegetation condition in South Australia

The normalised difference vegetation index (NDVI) has evolved as a primary tool for monitoring continental-scale vegetation changes and interpreting the impact of short to long-term climatic events on the biosphere. The objective of this research was to assess the nature of relationships between precipitation and vegetation condition, as measured by the satellite-derived NDVI within South Australia. The correlation, timing and magnitude of the NDVI response to precipitation were examined for different vegetation formations within the State (forest, scrubland, shrubland, woodland and grassland). Results from this study indicate that there are strong relationships between precipitation and NDVI both spatially and temporally within South Australia. Differences in the timing of the NDVI response to precipitation were evident among the five vegetation formations. The most significant relationship between rainfall and NDVI was within the forest formation. Negative correlations between NDVI and precipitation events indicated that vegetation green-up is a result of seasonal patterns in precipitation. Spatial patterns in the average NDVI over the study period closely resembled the boundaries of the five classified vegetation formations within South Australia. Spatial variability within the NDVI data set over the study period differed greatly between and within the vegetation formations examined depending on the location within the state. ACRONYMS AVHRR Advanced Very High Resolution Radiometer ENVSAEnvironments of South Australia EOS Terra-Earth Observing System EVIEnhanced Vegetation Index MODIS Moderate Resolution Imaging Spectro-radiometer MVC Maximum Value Composite NDVINormalised Difference Vegetation Index NIRNear Infra-Red NOAANational Oceanic and Atmospheric Administration SPOT Systeme Pour l’Observation de la Terre. [ABSTRACT FROM AUTHOR]

Mapping water quality and substrate cover in optically complex coastal and reef waters: an integrated approach

Sustainable management of coastal and coral reef environments requires regular collection of accurate information on recognized ecosystem health indicators. Satellite image data and derived maps of water column and substrate biophysical properties provide an opportunity to develop baseline mapping and monitoring programs for coastal and coral reef ecosystem health indicators. A significant challenge for satellite image data in coastal and coral reef water bodies is the mixture of both clear and turbid waters. A new approach is presented in this paper to enable production of water quality and substrate cover type maps, linked to a field based coastal ecosystem health indicator monitoring program, for use in turbid to clear coastal and coral reef waters. An optimized optical domain method was applied to map selected water quality (Secchi depth, Kd PAR, tripton, CDOM) and substrate cover type (seagrass, algae, sand) parameters. The approach is demonstrated using commercially available Landsat 7 Enhanced Thematic Mapper image data over a coastal embayment exhibiting the range of substrate cover types and water quality conditions commonly found in sub-tropical and tropical coastal environments. Spatially extensive and quantitative maps of selected water quality and substrate cover parameters were produced for the study site. These map products were refined by interactions with management agencies to suit the information requirements of their monitoring and management programs. (c) 2004 Elsevier Ltd. All rights reserved.

Mud, algae or seagrass: An assessment of remote sensing techniques for mapping inter-tidal seagrass cover and composition in turbid tropical environments

Large areas of tropical sub- and inter-tidal seagrass beds occur in highly turbid environments and cannot be mapped through the water column. The purpose of this project was to determine if and how airborne and satellite imaging systems could be used to map inter-tidal seagrass properties along the wet-tropics coast in north Queensland, Australia. The work aimed to: (1) identify the minimum level of seagrass foliage cover that could be detected from airborne and satellite imagery; and (2) define the minimum detectable differences in seagrass foliage cover in exposed intertidal seagrass beds. High resolution spectral-reflectance data (2040 bands, 350 – 2500nm) were collected over 40cm diameter plots from 240 sites on Magnetic Island, Pallarenda Beach and Green Island in North Queensland at spring low tides in April 2006. The seagrass species sampled were: Thalassia hemprechii, Halophila ovalis, Halodule uninerivs; Syringodium isoetifolium, Cymodocea serrulata, and Cymodoea rotundata. Digital photos were captured for each plot and used to derive estimates of seagrass species cover, epiphytic growth, micro- and macro-algal cover, and substrate colour. Sediment samples were also collected and analysed to measure the concentration of Chlorophyll-a associated with benthic micro-algae. The field reflectance spectra were analysed in combination with their corresponding seagrass species foliage cover levels to establish the minimum foliage projective cover required for each seagrass to be significantly different from bare substrate and substrate with algal cover. This analysis was repeated with reflectance spectra resampled to the bandpass functions of Quickbird, Ikonos, SPOT 5 and Landsat 7 ETM. Preliminary results indicate that conservative minimum detectable seagrass cover levels across most the species sampled were between 30%- 35% on dark substrates. Further analysis of these results will be conducted to determine their separability and satellite images and to assess the effects epiphytes and algal cover.

Monitoring the condition of savanna riparian zones in Northern Australia using high spatial resolution imagery and a field based rapid assessment method

Government agencies responsible for riparian environments are assessing the combined utility of field survey and remote sensing for mapping and monitoring indicators of riparian zone condition. The objective of this work was to compare the Tropical Rapid Appraisal of Riparian Condition (TRARC) method to a satellite image based approach. TRARC was developed for rapid assessment of the environmental condition of savanna riparian zones. The comparison assessed mapping accuracy, representativeness of TRARC assessment, cost-effectiveness, and suitability for multi-temporal analysis. Two multi-spectral QuickBird images captured in 2004 and 2005 and coincident field data covering sections of the Daly River in the Northern Territory, Australia were used in this work. Both field and image data were processed to map riparian health indicators (RHIs) including percentage canopy cover, organic litter, canopy continuity, stream bank stability, and extent of tree clearing. Spectral vegetation indices, image segmentation and supervised classification were used to produce RHI maps. QuickBird image data were used to examine if the spatial distribution of TRARC transects provided a representative sample of ground based RHI measurements. Results showed that TRARC transects were required to cover at least 3% of the study area to obtain a representative sample. The mapping accuracy and costs of the image based approach were compared to those of the ground based TRARC approach. Results proved that TRARC was more cost-effective at smaller scales (1-100km), while image based assessment becomes more feasible at regional scales (100-1000km). Finally, the ability to use both the image and field based approaches for multi-temporal analysis of RHIs was assessed. Change detection analysis demonstrated that image data can provide detailed information on gradual change, while the TRARC method was only able to identify more gross scale changes. In conclusion, results from both methods were considered to complement each other if used at appropriate spatial scales.

Integrating spatial optimization and cellular automata for evaluating urban change

Urban growth and change presents numerous challenges for planners and policy makers. Effective and appropriate strategies for managing growth and change must address issues of social, environmental and economic sustainability. Doing so in practical terms is a difficult task given the uncertainty associated with likely growth trends not to mention the uncertainty associated with how social and environmental structures will respond to such change. An optimization based approach is developed for evaluating growth and change based upon spatial restrictions and impact thresholds. The spatial optimization model is integrated with a cellular automata growth simulation process. Application results are presented and discussed with respect to possible growth scenarios in south east Queensland, Australia.

A synthesis of dominant ecological processes in intensive shrimp ponds and adjacent coastal environments in NE Australia

One of the key environmental concerns about shrimp farming is the discharge of waters with high levels of nutrients and suspended solids into adjacent waterways. In this paper we synthesize the results of our multidisciplinary research linking ecological processes in intensive shrimp ponds with their downstream impacts in tidal, mangrove-lined creeks. The incorporation of process measurements and bioindicators, in addition to water quality measurements, improved our understanding of the effect of shrimp farm discharges on the ecological health of the receiving water bodies. Changes in water quality parameters were an oversimplification of the ecological effects of water discharges, and use of key measures including primary production rates, phytoplankton responses to nutrients, community shifts in zooplankton and delta(15)N ratios in marine plants have the potential to provide more integrated and robust measures. Ultimately, reduction in nutrient discharges is most likely to ensure the future sustainability of the industry. (C) 2003 Elsevier Ltd. All rights reserved.

Assessing the seasonal influence of sewage and agricultural nutrient inputs in a subtropical river estuary

A combination of physical and chemical measurements and biological indicators identified nutrient impacts throughout an Australian subtropical river estuary. This was a balance of sewage inputs in the lower river and agricultural inputs in the mid-upper river, the combined influence being greater in the wet season due to greater agricultural surface runoff. Field sampling in the region was conducted at 6 sites within the river, over 5 surveys to encapsulate both wet and dry seasonal effects. Parameters assessed were tissue nitrogen (N) contents and delta(15)N signatures of mangroves and macroalgae, phytoplankton nutrient addition bioassays, and standard physical and chemical variables. Strong spatial (within river) and temporal (seasonal) variability was observed in all parameters. Poorest water quality was detected in the middle (agricultural) region of the river in the wet season, attributable to large diffuse inputs in this region. Water quality towards the river mouth remained constant irrespective of season due to strong oceanic flushing. Mangrove and macroalgal tissue delta(15)N and %N proved a successful combination for discerning sewage and agricultural inputs. Elevated delta(15)N and %N represented sewage inputs, whereas low delta(15)N and elevated %N was indicative of agricultural inputs. Phytoplankton bioassays found the system to be primarily responsive to nutrient additions in the warmer wet season, with negligible responses observed in the cooler dry season. These results indicate that the Tweed River is sensitive to the different anthropogenic activities in its catchment and that each activity has a unique influence on receiving water quality.

Assessing the influence and distribution of shrimp pond effluent in a tidal mangrove creek in north-east Australia

Effluent from a land based shrimp farm was detected in a receiving creek as changes in physical, chemical and biological parameters. The extent and severity of these changes depended on farm operations. This assessment was conducted at three different stages of shrimp-pond maturity, including (1) when the ponds were empty, (2) full and (3) being harvested. Methods for assessing farm effluent in receiving waters included physical/chemical analyses of the water column, phytoplankton bioassays and nitrogen isotope signatures of marine flora. Comparisons were made with an adjacent creek that served as the farms intake creek and did not directly receive effluent. Physical/chemical parameters identified distinct changes in the receiving creek with respect to farm operations. Elevated water column NH4+ (18.5+/-8.0 muM) and chlorophyll a concentrations (5.5+/-1.9 mug/l) were measured when the farm was in operation, in contrast to when the farm was inactive (1.3+/-0.3 muM and 1.2+/-0.6 mug/l, respectively). At all times, physically chemical parameters at the mouth of the effluent creek, were equivalent to control values, indicating effluent was contained within the effluent-receiving creek. However, elevated delta(15)N signatures of mangroves (up to similar to8parts per thousand) and macroalgae (up to similar to5parts per thousand) indicated a broader influence of shrimp farm effluent, extending to the lower regions of the farms intake creek. Bioassays at upstream sites close to the location of farm effluent discharge indicated that phytoplankton at these sites did not respond to further nutrient additions, however downstream sites showed large growth responses. This suggested that further nutrient loading from the shrimp farm, resulting in greater nutrient dispersal, will increase the extent of phytoplankton blooms downstream from the site of effluent discharge. When shrimp ponds were empty water quality in the effluent and intake creeks was comparable. This indicated that observed elevated nutrient and phytoplankton concentrations were directly attributable to farm operations. (C) 2003 Elsevier Ltd. All rights reserved.

Moreton Bay, Queensland, Australia: An example of the co-existence of significant marine mammal populations and large-scale coastal development

Recent analyses assert that large marine vertebrates such as marine mammals are now 'functionally or entirely extinct in most coastal ecosystems'. Moreton Bay is a large diverse marine ecosystem bordering the fastest growing area in Australia. The human population is over 1.6 million and increasing yearly by between 10% and 13% with resultant impacts upon the adjoining marine environment. Nonetheless, significant populations of three species of marine mammals are resident within Moreton Bay and a further 14 species are seasonal or occasional visitors. This paper reviews the current and historical distributions and abundance of these species in the context of the current management regime and suggests initiatives to increase the resilience of marine mammal populations to the changes wrought by the burgeoning human population in coastal environments. (C) 2004 Elsevier Ltd. All rights reserved.