Significant changes in mangroves have occurred across large areas of Australia over the last decade, including extensive mangrove dieback and cyclone damage. Such changes need to be detected and quantified as they occur, and post-event recovery monitored over extended periods, to ascertain effectiveness of management strategies.
This paper discusses key aspects of the formulation, development and implementation of a monitoring system for mangrove surveillance (e.g., extent, health, species) within the Terrestrial Environment Research Network (TERN) AusCover using dense time-series of optical satellite data from the Australian Geoscience Data Cube (AGDC), high resolution MiniSat data, and C- and L-band Synthetic Aperture Radar (SAR) observations jointly gathered with global forest and mangrove monitoring systems; collation of publicly available field, drone and aircraft observations; and the collection of new datasets under common protocols. Inventory of existing multi-scale and multi-source datasets facilitates planning and targeted acquisition of new remote sensing missions to generate key high-resolution baselines against which to quantify extent and magnitude of mangrove change overtime. Engagement of communities of practice (scientists and practitioners) is essential through avenues such as the Australian Mangrove and Saltmarsh Network (AMSN) and the Australian Earth Observation Community Coordination Group (AEOCCG).

Grass pollens are a major source of aeroallergens globally and afflict over three million Australians at a societal cost estimated at $30 billion. Pollen exposure, including the frequency of high pollen concentration days and thunderstorm pollen events, is projected to intensify with climate and land cover changes, escalating the risks for allergic respiratory diseases and raising threats of severe public health problems. Conventional pollen monitoring is restricted to sparse sampling locations and pollen forecast methods are site-specific and rely on empirical or meteorological relationships that lack consideration of landscape ecology. Here we investigated the utility of satellite observations of greenness phenology for predicting airborne grass pollen concentrations in contrasting urban environments located in Australia and France. Satellite phenology of grass cover sources was significantly correlated with in situ atmospheric grass pollen concentrations at all locations. Sites dominated by temperate grasses showed short and pronounced pollinating periods, with pollen peaks lagging behind greenness peaks. At the Sydney site, broader and multiple peaks in pollen and greenness coincided with flowering of more diverse grasses including subtropical species. Our results demonstrated the potential of satellite sensing to augment pollen forecast models as a tool to reduce the health burden of pollen-sensitive allergic diseases.

Long-term biophysical monitoring has contributed substantially towards advancements in theoretical and applied environmental science and conservation. However, the costs to maintain a long-term monitoring site are huge, particularly when collecting data at high spatial and temporal resolutions. Lightweight unmanned aerial vehicles (UAVs or drones) have been rapidly emerging as a cost-effective tool for local-scale monitoring. Here, we present a series of case studies to showcase the advantages and challenges of collecting spatial hyper-resolution data using drones. We found that the increased spatial or temporal resolution of collected datasets is of great benefit for most applications, such as microhabitat characterisation or terrain analysis. Nevertheless, hyper-resolution brings larger data volumes, longer processing times and limits spatial extent which can compromise the effectiveness of monitoring programs.