The Sentinel-1 satellite constellation is enabling large-scale ground surface deformation products to be generated in Australia. In this paper, we present our workflow to generate interferometric products leveraging the amassing archive of Sentinel-1 data and to subsequently derive the displacement time series at pixels on the ground. Our objective, a continent wide ground surface deformation map for Australia, will be used as a deformation reconnaissance tool in the future to detect areas of ongoing ground deformation in Australia and assist decision makers to assess the impact of land use on society and the environment. In this paper, we will outline our progress in generating the nationwide product, the challenges encountered, and our solutions to those challenges.

Remotely sensed data and updated DEM and radiometric datasets, combined with existing surface material and landform mapping were used to map regolith landform units for the Ti Tree, Western Davenport and Tennant Creek regions of the SSC project. This report describes the methods used and outlines the new mapping.

Remotely sensed data and updated DEM and radiometric datasets, combined with existing surface material and landform mapping were used to map regolith landform units for the Alice Springs study area of the SSC project. This report describes the methods used and outlines the new mapping.

This GIS data layer shows the frequency of coastal upwelling along the south-eastern coast of Australia. The higher data values indicate areas of persistent and semi-persistent upwelling; while, the medium data values indicate areas of seasonal upwelling. The data was generated using 14 years of monthly MODIS SST data. Please refer to this publication: "Huang, Z., & Wang, X.H. (2019). Mapping the spatial and temporal variability of the upwelling systems of the Australian south-eastern coast using 14-year of MODIS data. Remote Sensing of Environment, 227, 90-109" (https://doi.org/10.1016/j.rse.2019.04.002) for details of the MODIS data and the upwelling mapping method.

Wetlands around the world provide crucial ecosystem services and are under increasing pressure from multiple sources including climate change, changing flow and flooding regimes, and encroaching human populations. The Landsat satellite imagery archive provides a unique observational record of how wetlands have responded to these impacts during the last three decades. Information stored within this archive has historically been difficult to access due to its petabyte-scale and the challenges in converting Earth observation data into biophysical measurements that can be interpreted by wetland ecologists and catchment managers. This paper introduces the Wetlands Insight Tool (WIT), a workflow that generates WIT plots that present a multidecadal view of the biophysical cover types contained within individual Australian wetlands. The WIT workflow summarises Earth observation data over 35 years at 30 m resolution within a user-defined wetland boundary to produce a time-series plot (WIT plot) of the percentage of the wetland covered by open water, areas of water mixed with vegetation (‘wet’), green vegetation, dry vegetation, and bare soil. We compare these WIT plots with documented changes that have occurred in floodplain shrublands, alpine peat wetlands, and lacustrine and palustrine wetlands, demonstrating the power of satellite observations to supplement ground-based data collection in a diverse range of wetland types. The use of WIT plots to observe and manage wetlands enables improved evidence-based decision making. <b>Citation:</b> Dunn, B., Ai, E., Alger, M.J. et al. Wetlands Insight Tool: Characterising the Surface Water and Vegetation Cover Dynamics of Individual Wetlands Using Multidecadal Landsat Satellite Data. <i>Wetlands</i><b> 43</b>, 37 (2023). https://doi.org/10.1007/s13157-023-01682-7

<div>The city of Sydney, Australia has been growing rapidly over the last decades, with rapid development of residential and transportation infrastructure. Land subsidence associated with the urban development can lead to serious issues which should be thoroughly understood and carefully managed. Hence&nbsp;this study developed an enhanced multi-polarisation time-series InSAR (Pol-TS-InSAR) processing framework to address this challenging application.&nbsp;This is done by integrating the information from different polarimetric channels with different weighting during the TS-InSAR analysis. Ninety&nbsp;dual polarization Sentinel-1 images&nbsp;acquired from&nbsp;2019 to 2022 are analysed using the developed&nbsp;Pol-TS-InSAR to map the land subsidence in Sydney with the assistance of the GPS measurements. Improvement of measurement points density from Pol-TS-InSAR is observed compared to the single polarimetric TS-InSAR counterpart for all land use types (ranging between 21% and 99%). The comparison between the Pol-TS-InSAR measurements and GPS measurements shows an&nbsp;absolute mean difference and RMS difference of 0.7 mm/yr and 0.9 mm/yr, respectively, in line-of-sight (LoS) direction. The ground subsidence results obtained have been investigated.&nbsp;It is found that the main subsidence factors in Sydney are related to groundwater extraction, mining activities, underground tunnel construction and landfill, which the latter two factors are less aware previously. In additional to these factors, land subsidence related to high-rise building construction has also been observed, even though the impact seems to be less significant than other factors. <b>Citation:</b> Alex Hay-Man Ng, Ziyue Liu, Zheyuan Du, Hengwei Huang, Hua Wang, Linlin Ge, A novel framework for combining polarimetric Sentinel-1 InSAR time series in subsidence monitoring - A case study of Sydney,<i>Remote Sensing of Environment</i>, Volume 295, <b>2023</b>, 113694, ISSN 0034-4257. https://doi.org/10.1016/j.rse.2023.113694.

1. Tongatapu Bathymetric LiDAR 2. Tongatapu Topographic LiDAR

This is a collection of aerial photography captured from 5 November 2010 to 29 March 2012 and coinciding with a low-water tide occurrence for the purpose of defining the low-water coastline of Tasmania.

The implementation of a wide-land deformation monitoring program in eastern states of Australia, characterized by an extensive landmass and extensive coastlines, necessitates the generation of deformation maps with a significantly larger spatial extent. A pragmatic approach for achieving such coverage involves the integration of multiple interferometric synthetic aperture radar (InSAR) time series results encompassing various tracks and frames. The Sentinel-1 satellite constellation is facilitating the generation of expansive ground surface deformation, while the initial challenge in obtaining such a product arises from the varying spatial coverage of the Sentinel-1 data. To overcome this obstacle, we proposed a novel Sentinel-1 image definition to facilitate consistent interferometric processing. Before the formation of any large displacement map, the inconsistency between different synthetic aperture radar (SAR) image scenes must, nevertheless, be addressed. Several factors contribute to these inconsistencies in observations, such as differences in the angle of observation at the overlapping regions of adjacent image tracks and imprecise estimations within the dataset itself (e.g., burst or swath discontinuities). This study delves into solutions for these challenges, specifically: 1) introducing a computer-vision-based algorithm for InSAR dataset quality assessment and 2) proposing a global least square mosaicking procedure for the amalgamation of tiles from multitracks and frames. Statistical analyses show that better accuracy can be achieved. The mosaicking InSAR product demonstrates the capacity to quantify ground surface changes, which also exhibits a correlation with other geological layers, and the subsidence range of [−7, 10] mm/year shows a strong association with clay content levels ranging from 10% to 30% along the Darling River. <b>Citation:</b> Z. Du et al., "Toward a Wide-Scale Land Subsidence Product in Eastern States of Australia," in <i>IEEE Transactions on Geoscience and Remote Sensing</i>, vol. 61, pp. 1-12, 2023, Art no. 5213312, doi: 10.1109/TGRS.2023.3299928.

Combining observations of open water, wet vegetation, and vegetation fractional cover allows us to observe the spatiotemporal behaviour of wetlands. We developed a Wetlands Insight Tool (WIT) using Analysis-Ready Data available through Digital Earth Australia that combines Water Observations from Space (WOfS), the Tasseled Cap Wetness Transform (TCW) and Fractional Cover into an asset drill. We demonstrate the tool on three Australian wetlands, showing changes in water and vegetation from bush fires, sand mining and planned recovery. This paper was submitted to/presented at the 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2019) - https://igarss2019.org/