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The Medical Radiation Practice Board of Australia (MRPBA) minimum competency framework requires all Australian radiographers to identify significant pathology in radiological images and take appropriate action to alert these urgent findings and ensure patient safety. Despite professional bodies endorsing the provision of preliminary image evaluations (PIE) in written format, radiographer image interpretation often remains inconsistent, informal, or undocumented. The purpose of this narrative review was to assess the literature to determine if PIE in the form of written radiographer comments is of value to the Australian healthcare system. A structured search was completed using four health research databases: CINAHL, Medline, Scopus and Web of Science. Studies have suggested that there is a contextual need for commenting due to increased imaging service pressures, radiologist shortages and subsequent reporting delays. Radiographers appear well placed and willing to provide accurate initial input with evidence that this would be valued and appreciated within the multidisciplinary team. Radiographer commenting has also been shown to reduce diagnostic and communicative errors with the potential to improve patient management. Finally, it was shown that participation in image interpretation practices can enhance recruitment, retention and job satisfaction among radiographers. Therefore, the current literature supports implementation of radiographer commenting within the Australian healthcare system. [ABSTRACT FROM AUTHOR]

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Introduction: The use of diagnostic imaging services is increasing worldwide. This has important impacts on healthcare resource allocation and potential risks to the population. This study aimed to quantify trends in medical imaging in Australia over the past two decades. Methods: Data were extracted from the Australian Medicare Benefits Schedule (MBS) between 2000 and 2021. Simple linear regression analyses were performed to assess changes in absolute utilisation and utilisation rate per 100,000 population of total imaging services as well as by each imaging modality. Logistic regression analysis was performed to assess changes in total imaging services as a proportion of total Medicare services over time. Chi‐squared test was used to assess for change in modality composition of imaging services. Results: There were 436,255,500 imaging studies performed between 2000 and 2021. The absolute utilisation of total imaging services increased annually by an average of 864,404 (95% CI: 808,235–920,573, p < 0.001). For each consecutive year, the proportion of total Medicare services attributed to total imaging services increased by 0.01% (95% CI: 0.01–0.01, p < 0.01). There was also a statistically significant increase in the utilisation rates of imaging services per 100,000 population for each imaging modality. The number of imaging services per radiologist increased on average by 74 (95% CI: 26–122, p < 0.05) annually. Conclusion: The utilisation of diagnostic imaging services has increased in Australia between 2000 and 2021, outpacing the population growth, total healthcare services, and the radiologist workforce. [ABSTRACT FROM AUTHOR]

Plastics are now ubiquitous in the environment and have been studied in wildlife and in ecosystems for more than 50 years. Measurement of size, shape and colour data for individual fragments of plastic is labour‐intensive, unreliable and prone to observer bias, particularly when it comes to assessment of colour, which relies on arbitrary and inconsistently defined colour categorisations. There is a clear need for a standard method for data collection on plastic pollution, particularly one that can be readily automated given the number of samples involved.This study describes a new method for standardised photography of marine plastics in the 1–100 mm size range (meso‐ and macro‐plastics), including colour correction to account for any image‐to‐image variation in lighting that may impact colour reproduction or apparent brightness. Automated image analysis is then applied to detect individual fragments of plastic for quantitative measurement of size, shape, and colour.The method was tested on 3793 fragments of debris ingested by Flesh‐footed Shearwaters (Ardenna carneipes) on Lord Howe Island, Australia, and compare results from photos taken in two separate locations using different equipment. Photos were acquired of up to 250 fragments at a time with a spatial resolution of 70 μm/pixel and were colour‐corrected using a reference chart to ensure accurate reproduction of colour. The automated image analysis pipeline was found to have a 98% success rate at detecting fragments, and the different size and shape parameters that can be outputted by the pipeline were compared in terms of usefulness.The evidence shown in this study should strongly encourage the uptake of this method for cataloguing macro‐scale plastic pollution, as it provides substantially higher quality data with accurate, reliable measurements of size, shape and colour for individual plastics that can be readily compared between disparate datasets. [ABSTRACT FROM AUTHOR]

Increased demand for sustainable timber products has resulted in large investments in agroforestry in Australia, with plantations growing various Pinus species, selected to suit a plantation's environment. Juvenile Pinus species have a low fire tolerance. With Australia's history of wildfires and the likelihood of climate change exacerbating that risk, the potential for a total loss of invested capital is high unless cost-effective targeted risk minimisation is part of forest management plans. Based on the belief that the understory profiles within the juvenile plantations are a major factor determining fuel hazard risks, an accurate assessment of these profiles is required to effectively mitigate those risks. At present, assessment protocols are largely reliant on ground-based observations, which are labour-intensive, time consuming, and expensive. This research project investigates the effectiveness of using geospatial analysis of drone-derived photographic data collected in the commercial pine plantations of south-eastern Queensland as a cost-saving alternative to current fuel hazard risk assessment practices. Understory composition was determined using the supervised classification of orthomosaic images together with derivations of canopy height models (CHMs). The CHMs were subjected to marker-controlled watershed segmentation (MCWS) analysis, isolating and removing the plantation pine trees, enabling the quantification of understory fuel profiles. The method used proved highly applicable to immature forest environments with minimal canopy closure, but became less reliable for close canopied older plantations. [ABSTRACT FROM AUTHOR]

The use of drones and remote sensing in combination with geospatial analysis is a cost-efficient way to monitor energy distribution networks, especially those in fire-prone areas. This study investigated the use of image and photogrammetric analysis together with segmentation algorithms to assess vegetation height and volume in power line corridors in Southeast Queensland, Australia. Various fuel reduction techniques, including mega-mulching, spot sprays and cool mosaic burns, were implemented, and drone-generated models were employed to evaluate their effectiveness. The fuel hazard reduction and regrowth in terms of vegetation height and volume were recorded and analysed. Importantly, the study demonstrates a robust correlation (R2 = 0.9073; df = 1,16; F = 156; p <.001) between field observations and drone-derived models, affirming the efficacy of this method in assessing fuel heights. This validation suggests that the approach could represent a viable, cost-efficient option for future monitoring and management of energy distribution networks in fire-prone areas. [ABSTRACT FROM AUTHOR]

The Nullarbor Plain is a ~200,000 km2 planar karst surface in southern Australia, underlain by Cenozoic shallow‐water limestones. During the Miocene the area was uplifted, and although the plain is generally considered extremely flat, locally, the geomorphology of the Nullarbor Plain retains evidence of earth surface processes across a long, middle Miocene‐to‐present time span. The accessibility of the recent 0.4 arc‐second TanDEM‐X digital elevation model (DEM) by the German Aerospace Centre motivated the search for other possible fine‐scale landforms that would previously have been unresolvable. The analysis of DEM images revealed an enigmatic annular landform with an outer diameter between 1200 m and 1300 m. It consists of a circular elevated rim and a central dome. Its morphology is distinct from other landforms observed on the plain, and cannot be readily explained as a part of known active or inferred/expected processes on the plain (e.g., fluvial, aeolian, karst, tectonic or extra‐terrestrial impact processes). More recent karst processes (dayas formation) overprinting the landform indicates the presence of the annular structure prior to dayas formation. A unique microbial boundstone facies sampled from the bed‐rock of the annular structure supports an interpretation of long‐lived, at least partial retention of a primary depositional structure. Differential carbonate deposition, especially bioherm growth, was a likely origin of the annular topographical expression of the present‐day landform and is comparable to biogenic structures in the modern day deeper Great Barrier Reef. [ABSTRACT FROM AUTHOR]

Coastal wetlands are restored to regenerate lost ecosystem services. Accurate and frequent representations of the distribution and area of coastal wetland communities are critical for evaluating restoration success. Typically, such data are acquired through laborious, intensive and expensive field surveys or traditional remote sensing methods that can be erroneous. Recent advances in remote sensing techniques such as high-resolution sensors (<2 m resolution), object-based image analysis and shallow learning classifiers provide promising alternatives but have rarely been applied in a restoration context. We measured the changes to wetland communities at a 200 ha restoring coastal wetland in eastern Australia, using remotely sensed Worldview-2 imagery, object-based image analysis and random forest classification. Our approach used structural rasters (digital elevation and canopy height models) and a multi-temporal technique to distinguish between spectrally similar land cover. The accuracy of our land cover maps was high, with overall accuracies ranging between 91 and 95%, and this supported early detection of increases in the area of key ecosystems, including mixed she-oak and paperbark (10 ha), mangroves (0.91 ha) and saltmarsh (4.31 ha), over a 5-year monitoring period. Our approach provides coastal managers with an accurate and frequent method for quantifying early responses of coastal wetlands to restoration, which is essential for informing adaptive management in the regeneration of ecosystem services. [ABSTRACT FROM AUTHOR]

Photographs of sediment cores are an important dataset, often containing visual evidence for environmental change via sediment composition and structure. These photographs may be used to stratigraphically correlate adjacent cores or for automated image analysis, and can facilitate collaboration amongst researchers through sharing and annotation of the image files. Here we describe the use of computational photogrammetry (also known as Structure from Motion–Multi-View Stereo) to generate orthographic imagery of sediment cores. Computational photogrammetry is a rapid and economical technique, typically requiring only a few minutes for each metre of core, using consumer-grade digital camera equipment. The photogrammetric methodology corrects for topographic distortion caused by sediment surfaces that are not perfectly flat, and can also record features of the scene surrounding the core, such as notes, colour reference cards and measurement tapes or rulers. As the photogrammetric process also generates a three-dimensional reconstruction of the sediment core, spatial-based analysis can be used to identify damaged or non-representative sections of the core that are to be avoided during image analysis. Using an intermittently laminated sediment core from Lake Surprise, Australia, we tested 22 scenarios using control points in a variety of configurations, as well as calibrated and uncalibrated cameras, to identify techniques that can reconstruct the core accurately and generate orthophotos. Multiple techniques were able to achieve suitable accuracy. In particular, targets placed on the table alongside the core, combined with a calibrated camera, achieved high accuracy and enabled a simple, rapid, and repeatable method for generating high-quality sediment core images. [ABSTRACT FROM AUTHOR]

Perennial ryegrass (Lolium perenne L.) is considered the most important pasture species in temperate agriculture, with over six million hectares of sown area in Australia alone. However, perennial ryegrass has poor persistence in some environments because of low tolerance to a range of both abiotic and biotic stresses. To breed perennial ryegrass, cultivars with greater persistence and productivity may require evaluation of genotypes over a number of years. Persistence assessment in pasture breeding depends on manual ground cover estimation or counting the number of surviving plants or tillers in a known area. These methods are subjective and labour intensive, which may limit data collection in large‐scale breeding programs. With the rapid development of sensors and image processing algorithms, image‐based high‐throughput phenotyping (HTP) is becoming commonplace in the breeding of major food crops. Image‐based HTP approaches consist of the deployment of a wide range of sensors on ground‐based or airborne platforms and data analysed through image processing pipelines. Image‐based HTP shows high potential for use in pasture phenotyping in breeding programs and may be able to reduce timeframes for releasing new cultivars. Moreover, existing image‐based HTP approaches could be further developed to include precise tools for phenotyping pasture persistence traits such as pasture senescence, botanical composition, pathogen and pest resistance. In this study, we reviewed existing image‐based HTP approaches in precision agriculture and discussed their feasibility for perennial ryegrass persistence estimation in pasture breeding. Although the paper focuses on application in perennial ryegrass, the principles equally apply to other perennial forage species. [ABSTRACT FROM AUTHOR]

Southern Bluefin Tuna (SBT), Thunnus maccoyii, is ranched off Port Lincoln, South Australia and is Australia's second largest economic finfish aquaculture industry. The biggest threats to SBT health identified by the industry are the blood flukes Cardicola forsteri and C. orientalis (Trematoda: Aporocotylidae). Melanomacrophage centres (MMCs) are aggregations of pigmented macrophage like cells present in spleen, kidney and liver of teleost fish. The aim of this study was to quantify MMCs in SBT anterior kidney, liver and spleen to investigate changes in relation to Cardicola spp. Infection. Samples were collected at the end of ranching from pontoons where SBT were treated with PZQ and pontoons with untreated SBT. SBT MMC percentage of surface area cover was highest in SBT spleen and lowest in the liver. Significant positive correlations were identified between SBT MMC area and SBT size in all three organs (p < 0.05). MMC area and parasite infection showed significant positive correlations in the kidney and spleen for Cardicola spp. gill egg counts, and in the kidney for C. forsteri DNA from SBT hearts and gills (p < 0.05). MMCs area increased with increased intensity of Cardicola spp. Infection and MMCs have the potential to be used as an indicator to assess health effects that Cardicola spp. have on SBT. • Melanomacrophage centres (MMCs) had a larger area and darker pigmentation in the kidney and spleen compared to the liver. • Positive correlations were identified between MMC area and SBT size. • Positive correlations were found between SBT MMC area and Cardicola spp. DNA and egg counts. • Some parasite eggs were encapsulated in hepatic MMCs. [ABSTRACT FROM AUTHOR]

Postage stamps act as 'tiny transmitters' of nationalist and colonial ideology due both to their capacity for movement and as sites of official, statesanctioned visual propaganda. The representation of Aboriginal people and motifs on stamps in mid-twentieth-century Australia are visual clues that reference shifts in thinking about nation-building from the interwar to the postwar period. Stamps provide a concentrated visual snapshot of the tense and unstable positioning of Aboriginal people both within settler imagination and the Australian nation during this period of change. Changing understandings of the place of Aboriginal people within Australia resulted in the proliferation of visual representations that drew upon earlier colonial visual language, and hence images of Aboriginal Australians form their own moving historical trajectory, as mobile as the postage stamps on which they came to feature. This article seeks to trace the genealogy of this representational flux through analysis of the images of Aboriginality that featured on postage stamps, as well as exploring the unique interaction of government and popular influence on the postage stamp as form. It uncovers a previously unknown image of the historically significant Aboriginal Australian man Gwoja Tjungurrayi, whose likeness features on the Australian two dollar coin. [ABSTRACT FROM AUTHOR]

Introduction: Radiographer image evaluation methods such as the preliminary image evaluation (PIE), a formal comment describing radiographers' findings in radiological images, are embedded in the contemporary radiographer role within Australia. However, perceptions surrounding both the capacity for Australian radiographers to adopt PIE and the barriers to its implementation are highly variable and seldom evidence-based. This paper systematically reviews the literature to examine radiographic image interpretation by Australian radiographers and the barriers to implementation. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses were used to systematically review articles via Scopus, Ovid MEDLINE, PubMed, ScienceDirect and Informit. Articles were deemed eligible for inclusion if they were English language, peer-reviewed and explored radiographic image interpretation by radiographers in the context of the Australian healthcare system. Letters to the editor, opinion pieces, reviews and reports were excluded. Results: A total of 926 studies were screened for relevance, 19 articles met the inclusion criteria. The 19 articles consisted of 11 cohort studies, seven crosssectional surveys and one randomised control trial. Studies exploring radiographers' image interpretation performance utilised a variety of methodological designs with accuracy, sensitivity and specificity values ranging from 57 to 98%, 45 to 98% and 68 to 98%, respectively. Primary barriers to radiographic image evaluation by radiographers included lack of accessible educational resources and support from both radiologists and radiographers. Conclusion: Australian radiographers can undertake PIE; however, educational and clinical support barriers limit implementation. Access to targeted education and a clear definition of radiographers' image evaluation role may drive a wider acceptance of radiographer image evaluation in Australia. [ABSTRACT FROM AUTHOR]

This project looks at the intersection between gunshot damage to road signs and the use of geographic information systems (GIS) for forensic intelligence. The project has surveyed several distinct regions in Victoria Australia (residential, semi-rural and rural) in order to establish the level and distribution of gunshot damage to signs. The study assesses the correlation between population densities, land use and road type and the types of gunshot damage associated with road signs. The study includes a temporal aspect with the aid of backdated GIS image data and assessment is made on the potential benefits for crime scene information gathering. Further, a software tool has been established that enables photographic analysis of the gunshot impact points to be used to help determine the scale of damage associated with the signs in order to help establish the types of weapons used. This information is presented in the context of the typical registered guns in the community to correlate the key types of weapons used in this type of activity. [ABSTRACT FROM AUTHOR]

• Background of insect images can reveal microhabitat information of species. • Machine learning approaches benchmarked against manual algorithm for microhabitat classification. • Insect image backgrounds classified as natural or anthropogenic microhabitats. • Thorough experimentations with three insect species are performed. • Automated algorithms proved to be better approach with 97.4% accuracy. Habitat fragmentation under increased urbanisation, industrial agriculture and land clearing, are changing the way insects occupy habitat. Some species are highly adaptable and may occupy urbanised areas, utilising anthropogenic microhabitat-scale features. Other species are dependent on natural elements of their habitats, having to locate small regions of natural microhabitat within increasingly hostile landscapes. Consequently, humans are encountering insects in new settings. Identifying and analysing insects' use of natural and anthropogenic microhabitats is therefore important to assess their responses to a changing environment, for instance to improve pollination or manage invasive pests. But such studies are labour-intensive. Traditional studies of insect microhabitat use can now be supplemented by machine learning-based insect image analysis. Typically, research has focused on automatic insect classification, but valuable data appearing in image backgrounds has been ignored. In this research, we analysed the backgrounds of insect images available in the Atlas of Living Australia database to determine the microhabitats in which they were commonly photographed. We analysed the image backgrounds of three globally distributed insect species that are common across Australia: Drone flies (Eristalis tenax), European honey bees (Apis mellifera), and European wasps (Vespula germanica). Image backgrounds were classified broadly as either natural or anthropogenic using computer vision and machine learning tools benchmarked against a manual classification algorithm. Our automated image background classification achieved 97.4 % accuracy when compared against manual classification. Mis-classifications were scarce, usually less than 1 % , and primarily for backgrounds of wood and soil or bare ground. Our results indicate that drone flies and European honey bees were predominantly photographed against natural backgrounds (flies manual classifier 95 ± 3 % , automated classifier 94 % , bees 89 ± 2 % , 87 %), implying frequent observations by humans in natural microhabitat. European wasps were less frequently photographed against natural backgrounds (70 ± 6 % , 63 %). Within this data set, observations of the wasps in anthropogenic microhabitats were more common than for flies and bees. Our results are aligned with the expectation that the wasps are relatively well-suited to urban environments, and that European honey bees and drone flies utilise natural features of their environment. In general, although biases in data collected without formal protocols limits their application, our new automated approach for image background analysis can provide valuable data about insects' interactions with humans, our artefacts, and natural features of their environments. [ABSTRACT FROM AUTHOR]

The development of hatchery technology for spiny lobsters has promoted interest in the establishment of a commercial on shore lobster aquaculture industry in Australia. Cannibalism in culture is extensive with cannibalistic interactions occurring during a relatively brief vulnerability while moulting. Therefore, pre-ecdysis characterisation would create an opportunity to intervene and disrupt cannibalism. Detecting pre-ecdysis with a sensor would open the scope of research into cannibalism reducing culture environments. During this study, three markers that have the potential to indicate ecdysis are assessed: growth of the new integument, formation of suture lines, and pigment changes. These markers were assessed using high frequency imaging ultrasound, computer vision, and digital image analysis in the HSV colour space, respectively. For individual animals, carotenoid pigment shift is an early and clear marker of pre-ecdysis, however variability between individuals excludes pigmentation being useful in characterising pre-ecdysis. Suture line definition was problematic under visible light because its definition was reduced by similarly coloured pigments, therefore using suture lines as a pre-ecdysis characteriser requires better definition. A logical research approach to enhance suture line clarity in images is to image them with light outside the visible spectrum. Growth of the new integument was visible on sonographs beneath the branchiostegites indicating that ultrasound may be a useful tool for sensing pre-ecdysis in lobsters. Ultrasonic investigation using a single element transducer may be a lower cost and robust sensing solution to detect new integument growth and is a high priority future research pathway. [ABSTRACT FROM AUTHOR]

High spatio-temporal resolution optical remote sensing data provide unprecedented opportunities to monitor and detect forest disturbance and loss. To demonstrate this potential, a 12-year time series (2000 to 2011) with an 8-day interval of a 30 m spatial resolution data was generated by the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) with Landsat sensor observations and Moderate Resolution Imaging Spectroradiometer (MODIS) data as input. The time series showed a close relationship over homogeneous forested and grassland sites, with r 2 values of 0.99 between Landsat and the closest STARFM simulated data; and values of 0.84 and 0.94 between MODIS and STARFM. The time and magnitude of clearing and re-clearing events were estimated through a phenological breakpoint analysis, with 96.2% of the estimated breakpoints of the clearing event and 83.6% of the re-clearing event being within 40 days of the true clearing. The study highlights the benefits of using these moderate resolution data for quantifying and understanding land cover change in open forest environments. [ABSTRACT FROM AUTHOR]

The aim of the present study was to evaluate the application of image analysis for Japanese Black cattle in Australia (Australian JB). Therefore, we assessed meat quality using an image analysis method to estimate the heritability of this trait in Australian JB. We photographed the cross-section of the 5th-6th ribs and calculated image analysis traits of 473 and 539 head of Australian JB and Australian JB sire crosses with other breeds (F1), respectively. Least square means of grading and image analysis traits were calculated. We further estimated the heritability of grading and image analysis traits of 414 head of Australian JB. The Australian Meat Industry Classification System (AUS-MEAT) marbling score (6.8) and percentage marbling area (29.2%) for Australian JB were significantly (P < 0.01) higher than those for F1 (4.7% and 19.3%, respectively). Percentage marbling area strongly correlated with the AUS-MEAT marbling score (r = 0.88), indicating that marbling can be improved using percentage marbling area as a substitute for AUS-MEAT marbling score. The head counts of AUS-MEAT marbling score increased in the Australian JB (mode value = 9). The result indicated that the AUS-MEAT marbling score lacks a sufficient range of values to evaluate a high marbling beef breed such as the Australian JB. Further, the heritability of percentage marbling area was 0.54, which is higher than the heritability of AUS-MEAT marbling score (0.23). Therefore, we conclude that determining percentage marbling area using image analysis may prove to be an effective method for improving the marbling of the Australian JB. The aim of this study was to evaluate the application of image analysis for Japanese Black cattle in Australia (Australian JB). Image analysis traits showed favourable characteristics for data analysis and indicated possibility of improving for marbling. We conclude that image analysis could be an effective method for improving the marbling of the Australian JB. [ABSTRACT FROM AUTHOR]

Mono-disperse droplet generation and subsequent drying in a spray-drying chamber, i.e., mono-disperse droplet spray dryer (MDDSD), provides a better-defined “flight experience” for liquid droplets. The related particle formation can be investigated more easily than that in the usual poly-disperse droplet spray dryer (PDDSD). Previously, skim milk, which is of high protein and high lactose content and is one of the two main dairy fluids that are processed into powder form for consumer markets, was subjected to this kind of investigation in Australia. Here, whole milk, which is the other main dairy fluid, has been spray-dried in a MDDSD set-up at Xiamen University (China). Because the initial droplet size is uniform, measurable, and the particle morphology after drying is consistent, it was possible to investigate the initial solids content effect upon shrinkage and inlet air temperature effect upon shrinkage. In contrast to what had been found for skim milk particles, the formation of the fat-containing (whole milk) particles does not follow the perfect shrinkage model as the skim milk does. This work has improved our quantitative understanding of the whole milk drying process. A fundamental analysis invoked with a modified one-dimensional modeling of spray drying has been given that has shown some further insight about the process. [ABSTRACT FROM AUTHOR]

• Machine vision can reduce labour in plot monitoring for variety and research trials. • Image analysis algorithms developed to assess crop development in multiple plots from single, fixed, infield colour camera. • Algorithms combined perspective transformation, lighting detection, feature tracking and colour segmentation. • Height and canopy cover slightly more accurate for soybean than maize. Hundreds of crop variety trial sites are operated across Australia with up to 100 small plots (20 m2) that require manual, labour-intensive monitoring for emergence, height, canopy cover and flowering status. Machine vision systems can reduce labour in monitoring, and infield fixed cameras are most suitable to provide low-cost continuous sensing without requiring labour of travelling to sites. Height is commonly detected using stereo cameras; however, a low-cost single camera system is preferable for broad scale use at variety trial sites. Existing low-cost fixed camera systems assess multiple plots in the image's field of view from a fixed mask that needs to be manually updated as the crop grows. Perspective transformation could be applied automatically to identify plot locations in the image. Existing systems also analyse multiple images independently and filter results to remove impacts from lighting variations. An alternative approach is to only analyse images in the same lighting conditions each day to reduce the need for filtering. In addition, a series of daily images can be used to track multiple leaf positions to monitor plant growth. A machine vision system has been developed that combines these technologies to track plant height from a series of daily images selected in the same lighting conditions, in combination with perspective transformation, in multiple plots in the camera's field of view. Emergence, canopy cover and flowering status were also identified at the canopy surface in each plot using colour segmentation and/or shape analysis. The algorithms were evaluated on 5 and 10 m towers monitoring randomised trials of 16 maize and soybean plots and detected maize flowering date within one day, soybean height (RMSE = 18.38 cm; R2 = 0.880), maize height (RMSE = 47.73 cm; R2 = 0.838), soybean canopy cover (RMSE = 22.14%; R2 = 0.818) and maize canopy cover (RMSE = 14.01%; R2 = 0.750). The larger error in maize height detection was due to the flowers being tracked by the algorithm instead of vegetation. Further work is required to transfer the algorithms to other crops and varieties. [ABSTRACT FROM AUTHOR]

The ∼5 ka Mt. Gambier Volcanic Complex in the Newer Volcanics Province, Australia is an extremely complex monogenetic, volcanic system that preserves at least 14 eruption points aligned along a fissure system. The complex stratigraphy can be subdivided into six main facies that record alternations between magmatic and phreatomagmatic eruption styles in a random manner. The facies are (1) coherent to vesicular fragmental alkali basalt (effusive/Hawaiian spatter and lava flows); (2) massive scoriaceous fine lapilli with coarse ash (Strombolian fallout); (3) bedded scoriaceous fine lapilli tuff (violent Strombolian fallout); (4) thin-medium bedded, undulating very fine lapilli in coarse ash (dry phreatomagmatic surge-modified fallout); (5) palagonite-altered, cross-bedded, medium lapilli to fine ash (wet phreatomagmatic base surges); and (6) massive, palagonite-altered, very poorly sorted tuff breccia and lapilli tuff (phreato-Vulcanian pyroclastic flows). Since most deposits are lithified, to quantify the grain size distributions (GSDs), image analysis was performed. The facies are distinct based on their GSDs and the fine ash to coarse+fine ash ratios. These provide insights into the fragmentation intensities and water-magma interaction efficiencies for each facies. The eruption chronology indicates a random spatial and temporal sequence of occurrence of eruption styles, except for a 'magmatic horizon' of effusive activity occurring at both ends of the volcanic complex simultaneously. The eruption foci are located along NW-SE trending lineaments, indicating that the complex was fed by multiple dykes following the subsurface structures related to the Tartwaup Fault System. Possible factors causing vent migration along these dykes and changes in eruption styles include differences in magma ascent rates, viscosity, crystallinity, degassing and magma discharge rate, as well as hydrological parameters. [ABSTRACT FROM AUTHOR]

This article investigates the implications of Australia’s prohibition of ‘child-abuse material’ (including cartoons, animation, drawings and text) for Australian fan communities of animation, comics and gaming (ACG) and slash fiction. It is argued that current legislation is out of synch with the new communicative environment brought about by the internet since a large portion of the fans producing and trading in these images are themselves minors and young people. Habermas’s analysis of the conflict between instrumental and communicative rationality is deployed to demonstrate that legislators have misrecognized the nature of the communicative practices that take place within the ‘lifeworlds’ of fan communities, resulting in an unjust ‘juridification’ of their creative works. Drawing on Japanese research into the female fandom surrounding ‘boys’ love’ (BL) manga, it is argued that current Australian legislation not only forecloses the fantasy lives of young Australian fans but also harms them by aligning them with paedophile networks. Finally, drawing upon Jean Cohen’s paradigm of ‘reflexive law’ the article considers a possible way forward that opens up channels of communication between regulators, fans, domain host administrators and media studies professionals that would encourage a more nuanced approach to legislation as well as a greater awareness of the need for self-regulation among fan communities. [ABSTRACT FROM AUTHOR]

Providing accurate maps of coral reefs where the spatial scale and labels of the mapped features correspond to map units appropriate for examining biological and geomorphic structures and processes is a major challenge for remote sensing. The objective of this work is to assess the accuracy and relevance of the process used to derive geomorphic zone and benthic community zone maps for three western Pacific coral reefs produced from multi-scale, object-based image analysis (OBIA) of high-spatial-resolution multi-spectral images, guided by field survey data. Three Quickbird-2 multi-spectral data sets from reefs in Australia, Palau and Fiji and georeferenced field photographs were used in a multi-scale segmentation and object-based image classification to map geomorphic zones and benthic community zones. A per-pixel approach was also tested for mapping benthic community zones. Validation of the maps and comparison to past approaches indicated the multi-scale OBIA process enabled field data, operator field experience and a conceptual hierarchical model of the coral reef environment to be linked to provide output maps at geomorphic zone and benthic community scales on coral reefs. The OBIA mapping accuracies were comparable with previously published work using other methods; however, the classes mapped were matched to a predetermined set of features on the reef. [ABSTRACT FROM AUTHOR]

Herbicide usage in weed control represents a significant economic cost and environmental risk in Australian sugarcane production. Weed spot spraying has potential to increase sugarcane production while reducing chemical usage and environmentally damaging runoff. However, weed spot spraying is traditionally a laborious manual task. This paper reports on a precision machine vision system that was developed to automatically identify and target the difficult to control weed Panicum spp. (Guinea Grass) in sugarcane crops. The infield machine vision system comprised a camera and artificial illumination to enable day and night trials. Image analysis algorithms were developed to discriminate Guinea Grass and sugarcane based on colour and textural differences between the species. A positive weed identification from the image analysis activated solenoid-controlled spray nozzles. Evaluations of the system in a sugarcane crop established that the image analysis algorithm parameters required frequent recalibration during the day but that the requirement for recalibration was reduced at night with constant artificial illumination. The algorithm was only effective at detecting mature Guinea Grass. The developed technology is considered a viable alternative to manual spot spraying of mature Guinea Grass in sugarcane at night. A cost benefit analysis of the new weed control system indicated potential grower savings of $170/ha by adopting the technology. [ABSTRACT FROM AUTHOR]

Abstract: Mapping, monitoring and managing the environmental condition of riparian zones are major focus areas for local and state governments in Australia. New remotely sensed data techniques that can provide the required mapping accuracies, complete spatial coverage and processing and mapping transferability are currently being developed for use over large spatial extents. The research objective was to develop and apply an approach for mapping riparian condition indicators using object-based image analysis of airborne Light Detection and Ranging (LiDAR) data. The indicators assessed were: streambed width; riparian zone width; plant projective cover (PPC); longitudinal continuity; coverage of large trees; vegetation overhang; and stream bank stability. LiDAR data were captured on 15 July 2007 for two 5km stretches along Mimosa Creek in Central Queensland, Australia. Field measurements of riparian vegetation structural and landform parameters were obtained between 28 May and 5 June 2007. Object-based approaches were developed for mapping each riparian condition indicator from the LiDAR data. The validation and empirical modelling results showed that the object-based approach could be used to accurately map the riparian condition indicators (R 2 =0.99 for streambed width, R 2 =0.82 for riparian zone width, R 2 =0.89 for PPC, R 2 =0.40 for bank stability). These research findings will be used in a 26,000km mapping project assessing riparian vegetation and physical form indicators from LiDAR data in Victoria, Australia. [Copyright &y& Elsevier]

The objectives of this research were to (a) develop a geo-object-based classification system for accurately mapping riparian land-cover classes for two QuickBird images, and (b) compare change maps derived from geo-object-based and per-pixel inputs used in three change detection techniques. The change detection techniques included post-classification comparison, image differencing, and the tasseled cap trans- formation. Two QuickBird images, atmospherically corrected to at-surface reflectance, were captured in May and August 2007 for a savanna woodlands area along Mimosa Creek in Central Queensland, Australia. Concurrent in-situ land-cover identification and lidar data were used for calibration and validation. The geo-object-based classification results showed that the use of class-related features and membership functions could be standardized for classifying the two QuickBird images. The geo-object-based inputs provided more accurate change detection results than those derived from the pixel-based inputs, as the geo-object-based approach reduced mis-registration and shadowing effects and allowed inclusion of context relationships. [ABSTRACT FROM AUTHOR]

An original questionnaire was used to investigate the available types of reference and treatment image verification equipment and specific practices related to image analysis. A section on treatment site-specific imaging was included. The questionnaire was distributed to all radiation oncology facilities in Australia and New Zealand. A response rate of 87% (40/46) was achieved. Most facilities (90%) in Australia and New Zealand reported the availability of electronic portal imaging devices. Use of computer software to assist with image interpretation was indicated by 92% of centres. Frequency of image acquisition and tolerance levels used for radical treatment sites were variable, but palliative treatment site protocols were more consistent between treatment facilities. In conclusion, departments should strive to use evidence-based protocols and guidelines to ensure acceptable accuracy in treatment delivery. [ABSTRACT FROM AUTHOR]

Remotely sensed vegetation classification would be performed more effectively if the areas of interest, such as forest canopies, could be isolated from the rest of the image (i.e. the background). This background is typically made up of features such as soil, understorey vegetation, shadows, trails and manmade structures. In order to discriminate between Eucalyptus canopies and background features from high resolution airborne linescanner data collected over the Mount Eccles national park (south-eastern Australia), a supervised Markovian texture modelling approach was developed. To account for the spatially random nature of eucalypt canopies, the texture corresponding to the canopy area was modelled using a parametric Markov random field. The band used for this processing was the near infrared channel which proved useful in highlighting the vegetation owing to its photosynthetic activity. A probability map locating all textures in the image, which were similar to that of a training sample, was produced and then thresholded. The simulations and the validation procedure suggest that the extraction of the entire eucalypt canopy is possible using the algorithm. This provides a means of pre-processing high resolution airborne data to create masks for further image analysis, and in particular for forest health mapping applications. [Copyright &y& Elsevier]

Recent advances in remote sensing technologies and image analysis provide a realistic opportunity to develop a reliable, robust indicator of forest health for Australian eucalypt forests. Using these technologies we present the development of a conceptual framework for a new indicator based on eucalypt canopy condition. The indicator, termed the Eucalypt Canopy Condition Index (ECCI), is derived from an assumed hierarchy of canopy decline symptoms, both physiological and structural. Our objective is to identify and discuss possible combinations of spectral, radiometric and spatial (scale) features from remotely sensed data that theoretically and practically correlate with each hierarchical phase of severity in canopy decline. Some of the issues associated with the development and application of the ECCI are discussed, and finally, how the ECCI could be integrated into existing or future operational systems is illustrated. [ABSTRACT FROM PUBLISHER]

To facilitate the simplification, visualisation and communicability of satellite imagery classifications, this study applied visual analytics to validate a colourimetric approach via the direct and scalable measurement of hue angle from enhanced false colour band ratio RGB composites. A holistic visual analysis of the landscape was formalised by creating and applying an ontological image interpretation key from an ecological-colourimetric deduction for rainforests within the variegated landscapes of south-eastern Australia. A workflow based on simple one-class, one-index density slicing was developed to implement this deductive approach to mapping using freely available Sentinel-2 imagery and the super computing power from Google Earth Engine for general public use. A comprehensive accuracy assessment based on existing field observations showed that the hue from a new false colour blend combining two band ratio RGBs provided the best overall results, producing a 15 m classification with an overall average accuracy of 79%. Additionally, a new index based on a band ratio subtraction performed better than any existing vegetation index typically used for tropical evergreen forests with comparable results to the false colour blend. The results emphasise the importance of the SWIR1 band in discriminating rainforests from other vegetation types. While traditional vegetation indices focus on productivity, colourimetric measurement offers versatile multivariate indicators that can encapsulate properties such as greenness, wetness and brightness as physiognomic indicators. The results confirmed the potential for the large-scale, high-resolution mapping of broadly defined vegetation types. [ABSTRACT FROM AUTHOR]

This is a follow-up study to assess growth in the number of cone beam computed tomography (CBCT) and panoramic radiography (PR) machines in Australia. It is also the first study to evaluate the current status of both CBCT and PR education in Australia. CBCT and PR machine numbers were obtained from the radiation regulators across Australia. Australian dental schools were surveyed via email. The number of machines relative to population size and the number of dentists were calculated. In 2020, there were 706 CBCT machines and 3,059 PR machines, representing a 204.3% increase in the number of CBCT machines and an 82.0% increase in the number of PR machines over six years. Majority of Australian dental schools owned PR and CBCT machines. Most taught PR acquisition and interpretation, however only one-third taught CBCT image acquisition and interpretation to predoctoral students. CBCT machine numbers increased by nearly three-fold while PR machines only increased by 1.6 times over a six-year period relative to population size and number of dentists. Only very few Australian dental schools provide CBCT education to predoctoral students, raising concern as to whether graduates are adequately trained upon program completion. [ABSTRACT FROM AUTHOR]

Mangroves are highly susceptible to oil exposure. Depending on the severity, oil exposure can result in initial defoliation and eventual recovery through to mass mortality and complete loss of habitat. Some aspects of the impact of oil on mangroves and their recovery are well studied, but the focus has been on short-term responses, and the understanding of the longer-term trajectory of mangrove recovery from oiling is very limited. Here, we combine field results from sampling in the two years following a significant oiling event, with analysis of canopy cover in aerial images from before the event to 26 years afterwards. Approximately 100 ha of a monospecific stand of Avicenna marina mangroves were oiled as a result of a spill from the Era tanker in Spencer Gulf in southern Australia in September 1992. While lightly oiled trees made a full recovery, trees in heavily oiled areas experienced mass defoliation and ultimately mortality within several months of the oiling event. An analysis of aerial images indicated that there was no recovery in heavily oiled areas for 10 years following the oiling event. Between 10 and 25 years, seedling establishment and growth saw canopy cover increase to 35% of pre-oiling cover within heavily oiled areas. Predictive modelling estimates that complete recovery of mangroves to pre-oiling cover will take 55 years (median prediction in 2047). Our findings indicate that although mangroves can recover following a heavy oiling event, the rate of recovery can be slow, with full recovery in the order of half a century, much longer than has previously been anticipated. • An oil spill caused mass mangrove mortality within weeks in southern Australia. • After 25 years, the mangrove canopy is patchy, with <50% recovery. • Complete mangrove recovery is predicted to take 55 years, longer than anticipated. [ABSTRACT FROM AUTHOR]

Routine flood inundation mapping is important for flood management and response. The 24-hour all-weather capability of Synthetic Aperture Radar (SAR) technology makes it a perfect choice for this application, except the backscattered microwave pulses at oblique angles can be difficult to interpret. Radar backscatter is mainly a function of surface roughness and thus smooth water surfaces and rough water-free areas generally have different responses. Nevertheless, a number of event-related and catchment-related factors can alter the backscatter characteristics and hinder accurate SAR image interpretations, particularly when the inundated areas have vegetation above the water. The electromagnetic interaction phenomena between microwaves, horizontal and vertical surfaces are highly complex and detection of flooded vegetation has been identified as one of the biggest challenges for accurate flood mapping. In this context, image interpretation algorithms usually make use of detailed field data and reference image(s) to implement electromagnetic models or change detection techniques. However, field data are rare, and, despite the increasing availability of SAR acquisitions, adequate reference image(s) might not be readily available, especially for fine resolution images. To bypass this problem, this study presents an algorithm for automatic flood mapping in vegetated areas which makes use of single SAR acquisitions and commonly available ancillary data. First, probability binning was used for statistical analysis of the backscatter response of wet and dry vegetation for different land cover types. This analysis was then complemented with information on land use, morphology and contextual information within a fuzzy logic approach. The algorithm was applied to three fine resolution images (one ALOS-PALSAR and two COSMOSkyMed) acquired during the January 2011 flood in the Condamine-Balonne catchment in Queensland, Australia. The results were validated using flood extent layers derived from optical images. In these case studies, state-of-the-art operational interpretation algorithms focusing solely on open water areas led to large omission errors with the Producer's Accuracy (PA) for the class water as low as 10.1%, 33.3% and 16.5% and the Overall Accuracy (OA) of 77%, 65%, and 75%, respectively. Notwithstanding the difficulty to fully discriminate between dry vegetation backscatter heterogeneity and backscatter variation due to flooding using a single SAR image, the use of probability binning allowed the omission errors to be reduced and the PA for the class water to have an increase of +75.2%, +62.2%, and +115.1%, respectively. Incorporation of land use, contextual, and morphological information allowed further refinement of the classification thus achieving a final OA of 83.7%, 81.5%, and 85.7%, respectively.The main benefit of the proposed algorithm is its ability to automatically detect flooded vegetation using one single SAR acquisition and commonly available ancillary data (ie. land cover, land use, and digital elevation models). This approach can support both real time flood monitoring and the analysis of historical acquisitions within proof of concept studies investigating the use of SAR data to improve flood modelling skill. Finally, to disclose the potential of current and upcoming SAR satellite missions, future work will feature the inclusion of time-series and multi-polarization SAR data analysis in the proposed algorithm. [ABSTRACT FROM AUTHOR]

In August 2011, a 2D facial approximation was undertaken of remains discovered in Australia's Belanglo State Forrest; in October 2015, the young woman was identified. Referencing three photographs of the young woman as she appeared in life and a database of 64 sex, age, head pose and population matched images, the facial approximation is evaluated for relative shape accuracy through the application of geometric morphometrics. The results are that the facial approximation is significantly similar to the images of the young woman in facial morphology (p=0.002) when most of the variance due to depicted head pose is removed from the analyses. The geometric morphometric analyses, however, also highlight the facial approximation's face and feature discrepancies, some of which would have likely disrupted familiar face recognition. Although predominantly verified methods were applied in 2011, they are limited in their predictive accuracy, not every feature of the face has a verified method to apply, and practitioner errors as well as photographic distortions are apparent. Furthermore, an assumption that the verified methods require inter-feature agreement (in this instance eye spacing and mouth width) was proved to be false. Overall this study shows that it is possible to assess the morphological accuracy of a forensic facial approximation when a number of antemortem images are available, though the influence of photographic distortion within 2D photographs will always preclude a precise metric assessment. [ABSTRACT FROM AUTHOR]