Training sensor-agnostic deep learning models for remote sensing: Achieving state-of-the-art cloud and cloud shadow identification with OmniCloudMask

Deep learning models are widely used to extract features and insights from remotely sensed imagery. However, these models typically perform optimally when applied to the same sensor, resolution and imagery processing level as used during their training, and are rarely used or evaluated on out-of-domain data. This limitation results in duplication of efforts in collecting similar training datasets from different satellites to train sensor-specific models. Here, we introduce a range of techniques to train deep learning models that generalise across various sensors, resolutions, and processing levels. We applied this approach to train OmniCloudMask (OCM), a sensor-agnostic deep learning model that segments clouds and cloud shadow. OCM demonstrates robust state-of-the-art performance across various satellite platforms when classifying clear, cloud, and shadow classes, with balanced overall accuracy values across: Landsat (91.5 % clear, 91.5 % cloud, and 75.2 % shadow); Sentinel-2 (92.2 % clear, 91.2 % cloud, and 80.5 % shadow); and PlanetScope (96.9 % clear, 98.8 % cloud, and 97.4 % shadow). OCM achieves this accuracy while only being trained on a single Sentinel-2 dataset, employing spectral normalisation and mixed resolution training to address the spectral and spatial differences between satellite platforms. This approach allows the model to effectively handle imagery from different sensors within the 10 m to 50 m resolution range, as well as higher resolution imagery that has been resampled to 10 m. The OCM library is available as an open source Python package on PyPI

BEN Signage Installation Map – City of Kwinana

BEN Signage Installation Map – City of Kwinanahttps://library.dpird.wa.gov.au/gis_bens/1010/thumbnail.jp

The first Australian co-invasion of Euwallacea fornicatus, Fusarium sp. [AF18] and Graphium euwallaceae

As international trade and travel increase around the world, invasive species detections and incursions are increasing in frequency. Here we document the first detection and incursion within Australia by the Polyphagous shot-hole borer (PSHB), Euwallacea fornicatus (Eichhoff, 1868) (Coleoptera: Curculionidae: Scolytinae), an ambrosia beetle, and two of the associated fungal species; Fusarium sp. [AF18], and Graphium euwallaceae. All three exotic species were detected in a confined region within Perth, Western Australia, and represent a co-invasion. This multispecies incursion into one of the world’s most remote cities highlights the rapid increase in biological invasions globally and the pressures that urban, agricultural, and native environments face from invasive species

Adaptive water body detection: Integrating deep learning, normalised difference water index, and vector data for farm dam water monitoring with OmniWaterMask

Farm dams are important water security features supporting both agricultural production and the natural environment. In Australia alone, over two million farm dams provide the water resources underpinning rural and regional primary industries with an annual export value of $80 billion. However, monitoring these water bodies to understand water security and vulnerability is challenging, primarily because of their large quantity, size and highly variable spectral signatures. These characteristics result in difficulty determining thresholds for index-based water detection methods and add to the difficulty of creating adequate training datasets for deep learning methods. We present an adaptive approach named OmniWaterMask (OWM) that uses existing mapped water features to optimise the combination of deep learning outputs and a common water index (Normalised Difference Water Index, NDWI) to achieve robust water detection, for both agricultural and other water resources. OWM demonstrates strong performance across multiple datasets and spatial scales, achieving Intersection over Union (IoU) scores of 96.9 % (Sentinel-2), 73.8 % (Landsat) and 90.9 % (National Agriculture Imagery Program, NAIP). When applied to farm dam monitoring in Western Australia using Sentinel-2 imagery, the approach successfully tracks water extent across a range of dam sizes, with Mean Absolute Error (MAE) of 587 m2 when using Sentinel-2 and 785 m2 when using PlanetScope. Our two case studies demonstrate the practicality and scalability of this approach by monitoring water levels in both a single dam and across 7,172 farm dams at monthly intervals over an 8-year period. This methodology enables reliable monitoring of small water bodies at scale, supporting rural water security assessment in increasingly uncertain climatic conditions. The open source OWM library is made available as a Python package on PyPI

Resource assessment report no. 2: West Coast Demersal Scalefish Resource 2025 assessment

The West Coast Demersal Scalefish Resource (WCDSR) comprises over 100 species inhabiting inshore (20-250 m deep) and offshore ( \u3e 250 m deep) waters of the West Coast Bioregion (WCB; north of Kalbarri to east of Augusta). The WCDSR is primarily targeted by commercial, charter and recreational boat-based line fishers, including the commercial West Coast Demersal Scalefish (Interim) Managed Fishery (WCDSIMF). Indicator species selected for monitoring and assessing the status of the inshore suite of the WCDSR include Snapper, WA Dhufish and Baldchin Groper, while indicators for the offshore suite include Hapuku, Bass Groper and Blue-eye Trevalla. The WCDSR is more than halfway through a 20-year recovery plan to recover stocks by 2030. As outlined in the WCDSR harvest strategy, the recovery of the resource is currently monitored through annual reviews of total removals (including retained catches and estimates of post-release mortality) against specific recovery benchmarks for each sector, as well as periodic stock assessments of each indicator species (DPIRD 2021). The 2025 WCDSR assessment presented in this report incorporates catch and effort information collected up to 2024 (inclusive), as well as biological data on the sizes and ages of fish sampled from commercial and recreational catches in each management area (Kalbarri, Mid-West, Metropolitan and South-West) up until 2021-22 (inclusive). Total removals of demersal scalefish by commercial fisheries in the WCB in 2024 (291 t) were well above the 240 t recovery benchmark in place for that year. The total removals of key demersal scalefish species collectively caught by boat-based recreational and charter fishers in the WCB in 2023-24 (217 t), derived from the 2023-24 survey of private boat-based fishing and reported charter catches in the same year, were also well above the 135 t recovery benchmark for this sector. These data show that the substantial management changes implemented in 2023 have not been effective at reducing fishing mortality to the level required to support recovery. The WCDSR provides a high social amenity to fishers, with the indicator species representing primary targets for recreational fishers in the WCB. The estimated gross value of product (GVP) of the commercial WCDSIMF was $1-5 million in 2024

Sheep production, profitability and greenhouse gas emission of mixed farming systems in Western Australia\u27s Wheatbelt

The south-western agricultural area of Western Australia is a vital contributor to Australia\u27s agricultural output. It generates over $10 billion annually in agricultural production from 2017–18 to 2021–22 and more than$8 billion in export value over the same period. Mixed farming systems characterise the region, producing broadacre crops (primarily wheat, barley, and canola) and livestock. The region\u27s livestock industry is dominated by sheep production for meat and wool, and the state’s share of the national sheep flock in 2020–21 was at 18%. This report provides a comprehensive review and industry analysis of sheep production in WA, its economic significance, and associated greenhouse gas emissions. It examines the unique characteristics of WA\u27s mixed farming systems, their key economic and environmental drivers, and the innovative practices that underpin the sector\u27s productivity and profitability in a changing climat

An economic analysis of cell-fencing in semi-arid rangelands

In Australia, livestock predation by dingoes (Canis familiaris) has contributed to what some livestock producers consider a dire situation for rangeland pastoralism, driving demand for cooperative regional-scale exclusion (‘cell’) fencing (i.e. pest-proof fences that encompass one or more individual properties) and landscape-scale predator control. The present case study predicted the effect of four cell-fences in the state of Western Australia (WA) on the gross margin of sheep (for meat or meat and wool) and cattle pastoral enterprises. We modelled the potential effects of the following four key variables: (1) four levels of commodity prices, (2) five levels of livestock weaning rate (based on livestock records collected 1985–1995; weaning rate is defined as number of lambs or calves that are born and survive to weaning, expressed as percentage of total mated females), (3) three predicted levels of time required to remove dingoes from within the fenced area, and (4) five levels of macropod (mainly kangaroo) response as competitive grazers, with a total of 3600 scenarios representing all combinations of these factors. Each scenario was assessed for profitability (i.e. net present value (NPV) over 25 years) and benefit of fencing (i.e. NPV compared with an unfenced enterprise of the same livestock type, region, and commodity prices). Finally, the benefit–cost ratio (BCR) of investment in cell fencing was calculated for each fenced scenario. The majority (67%) of scenarios representing continuation of current management (i.e. no cell fencing) returned a negative NPV (i.e. livestock enterprises were projected to make a loss). However, only 37.4% of cell-fenced scenarios returned a positive NPV, meaning that even with a cell-fence and successful removal of dingoes, the enterprise was still unlikely to be profitable. Only 43.4% of cell-fenced scenarios returned a BCR of cell fencing greater than one. Weaning rate following dingo removal was the most important factor determining return on investment for cell-fencing. Survival and reproduction of small livestock, particularly wool sheep, benefit most from cell-fencing, whereas cell-fencing and dingo removal did not result in greater profits for cattle enterprises. Running sheep for wool and meat within cell fencing coupled with removal of dingoes would maximise the likelihood of achieving a positive return on investment in cell fencing (although the enterprise may remain unprofitable overall); otherwise, unfenced enterprises affected by dingoes should run cattle as this will be more profitable

How to find a skeleton weed

Pollen and pappus trapping and eDNA are two techniques that could compliment on-ground surveillance. Labour availability and occupational health and safety are impacting on-ground surveillance of skeleton weed in Western Australia. To compensate passive surveillance techniques are being developed

Predator management with a single bait? Use of Eradicat for the simultaneous management of feral cats, red foxes, and wild dogs

Context In Western Australia, there are three invasive predators that require management for agriculture and biodiversity protection, feral cats, wild dogs, and red foxes. These three predators often coexist in the same locality, suggesting potential efficacy gains can be made via simultaneous control. While Western Australian native species have evolved a high tolerance to poison baiting (1080), invasive predators have not. Therefore, landscape-scale baiting is commonly used for predator management. Aims Eradicat baits designed for feral cat control have also been known to be consumed and control wild dogs and foxes. In this trial, we aimed to evaluate Eradicat as an all-predator bait, determine if there is a preferential time for the use of the bait and assess non-target impact(s) of baiting. Methods We aimed to control all three predators on an agricultural property adjacent to a conservation reserve over 16 months with eight baiting events using Eradicat as an all-predator bait. Twenty one Reconyx camera traps monitored some of the baits deployed. Key results A total of 300 baits had a known outcome with minimal uptake by all three predators. Many issues were encountered when working on a smaller-scale including interference with farming activities and management, flash flooding, and non-target uptake of the Eradicat baits. Wetter than anticipated environmental conditions likely increased alternate prey availability, negatively impacting bait uptake. Conclusions More work is required to determine if Eradicat baits can be used as an all-predator bait

West Coast Demersal Scalefish Resource recovery support package: 2023-24 report

The West Coast Demersal Scalefish Resource (WCDSR) includes over 100 species in inshore (20–250 m deep) and offshore ( \u3e 250 m) demersal habitats of the West Coast Bioregion. These species are caught by charter, commercial and recreational fishers. The WCDSR is in recovery and managed under a 20-year recovery plan (2010–2030). DPIRD tracks recovery progress through scientific stock assessments of the indicator species (snapper, WA dhufish, and baldchin groper) every 3 years. The 2021 WCDSR stock assessment showed limited recovery and additional management action was required. In December 2022, the Minister for Fisheries announced commercial and recreational (including charter) sector management packages and a $10 million recovery package to support recovery