A5005042455- Flood Risk Assessment and Management
- Hydrology and Watershed Management Studies
- Remote Sensing and LiDAR Applications
- Soil erosion and sediment transport
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Hydrology and Sediment Transport Processes
- Remote Sensing in Agriculture
- Hydrology and Drought Analysis
- Remote-Sensing Image Classification
- Forest ecology and management
- Hydrological Forecasting Using AI
- Soil Geostatistics and Mapping
- Coastal wetland ecosystem dynamics
- Sugarcane Cultivation and Processing
- Soil Moisture and Remote Sensing
- Land Use and Ecosystem Services
- Remote Sensing and Land Use
- Groundwater and Watershed Analysis
- Coastal and Marine Dynamics
- Geological formations and processes
- Automated Road and Building Extraction
- Water resources management and optimization
- Geophysical Methods and Applications
- Geological and Geophysical Studies
- Geophysics and Gravity Measurements
Health Sciences and Nutrition
2019-2025
Commonwealth Scientific and Industrial Research Organisation
2005-2024
CSIRO Land and Water
2011-2022
ACT Government
2015-2021
UNSW Sydney
1997-2005
Mangrove ecosystems are in serious decline around the world and various initiatives underway to assess their current coverage loss cover. These occur as thin strips along coastlines or rivers and, due strong environmental gradients present, mangroves show high spatial variability short transects. Remote sensing tools that offer resolution mapping information content needed provide good differentiation of mangrove zones types. The added complexities tropical atmospheric conditions further...
1. The Japan Aerospace Exploration Agency's (JAXA) Advanced Land Observing Satellite (ALOS) L-band Phased Array Synthetic Aperture Radar (PALSAR), launched successfully in January 2006, will provide new data sets for coastal ecosystems mapping and change monitoring at local to global scales. 2. To evaluate capability mangrove applications, acquired by the NASA airborne SAR (AIRSAR) Japanese Earth Resources (JERS-1 SAR) over sites Australia, French Guiana Malaysia were used demonstrate...
With the increasing availability of high-resolution satellite imagery it is important to improve efficiency and accuracy image indexing, retrieval classification. Furthermore, there a need for utilizing all available in identifying general land cover types monitoring their changes through time irrespective spatial, spectral, temporal radiometric resolutions. Therefore, this study, we developed deep learning models able efficiently accurately classify cloud, shadow scenes different (<10 m)...
Mangroves globally provide a diverse array of ecosystem services but these are impacted upon by both natural and anthropogenic drivers change. In Australia, mangroves protected law hence the predominate. To determine annual national level changes in between 1987 2016, their extent (by canopy cover type) dynamics were quantified using dense time-series (nominally every 16 days cloud permitting) 25 m spatial resolution Landsat sensor data available within Digital Earth Australia (DEA). The...
Abstract A full understanding of radar backscatter from urban areas is necessary in order to develop a robust methodology for monitoring and classifying characteristics using remotely sensed Synthetic Aperture Radar images.This paper examines the dominant backscattering mechanisms such as single bounce roofs, double wall-ground structures possibly triple wall-wall-ground structures, their relative contributions backscatter. With use quad-polarized image data those acquired by NASA/JPL AirSAR...
Abstract Surface water connectivity between waterbodies in a river–floodplain system is considered one of the key determinants habitat quality, biodiversity and ecological integrity. This manuscript presents results from an investigation into potential changes floodplain inundation wetlands rivers under projected future climates, large river catchment Western Australia. The study was conducted using two‐dimensional hydrodynamic model (MIKE 21), modelling domain included reaches encompassing...
Abstract Across their range, mangroves are responding to coastal environmental change. However, separating the influence of human activities from natural events and processes (including that associated with climatic fluctuation) is often difficult. In Gulf Carpentaria, northern Australia (Leichhardt, Nicholson, Mornington Inlet, Flinders River catchments), changes in assumed be result drivers as impacts minimal. By comparing classifications time series Landsat sensor data for period...
Daily, or more frequent, maps of surface water have important applications in environmental and resource management. In particular, derived from remote sensing imagery play a useful role the derivation spatial inundation patterns over time. MODIS data provide most realistic means to achieve this since they are daily, although often limited by cloud cover during flooding events, their resolutions (250–1000 m pixel) not always suited small river catchments. This paper tests suitability sensor...
Small water storages (≤ 500 ha surface area) enhance supply for agricultural, human and livestock consumption. Their oftentimes large numbers wide geographic spread, plus inaccurate or absent in situ metering, make their inclusion resource management difficult. This research assessed the capabilities of satellite optical remote sensing LiDAR altimetry to characterise small used irrigation, so they can be included resources assessments. Landsat Sentinel-2 maps were integrated with airborne...
In this study, independent classifications of Landsat Thematic Mapper imagery and Jet Propulsion Laboratory AirSAR were combined to create an integrated classification pasture other vegetation types for a study area in the agricultural zone Western Australia. The resulting combines greenness brightness information from optical data with structure water content synthetic aperture radar (SAR). Field observations type, botanical composition, ground cover percentage, wet dry biomass, canopy...
Predicting floodplain inundation under a changing climate is essential for adaptive management of water resources and ecosystems worldwide. This study presents framework combining satellite observations hydrological modeling to explore changes in inundation. We examine variability, trends, frequency across the Murray-Darling Basin (MDB), Australia's largest river system, over past 35 years (1988-2022). Our analysis shows that annual maximum 30-day runoff primary factor influencing Using this...
Mapping surface water extent is important for managing supply agriculture and the environment. Remote sensing technologies, such as Landsat, provide an affordable means of capturing with reasonable spatial temporal coverage suited to this purpose. Many methods are available mapping including modified Normalised Difference Water Index (mNDWI), Fisher’s index (FWI), Observations from Space (WOfS), Tasseled Cap Wetness (TCW). While these can discriminate water, they have their strengths...
Abstract Simple models continue to be important for continental‐scale floodwater depth mapping due the prohibitively expensive cost of calibrating and applying hydrodynamic models. This paper investigates accuracy three simple estimation from remote sensing derived water extent and/or Digital Elevation Models (DEMs) in semiarid regions. The are Height Above Nearest Drainage (HAND; Nobre et al., 2011, https://doi.org/10.1016/j.jhydrol.2011.03.051 ), Teng Vaze Dutta (TVD; 2013,...
Abstract With growing concerns over water management in rivers worldwide, researchers are seeking innovative solutions to monitor and understand changing flood patterns. In a noteworthy advancement, stakeholders interested the patterns of Murray Darling Basin (MDB) Australia, covering an area 1 million km 2 , can now access consistent timeseries depth maps for entire basin. The dataset covers period from 1988 2022 at two-monthly timestep was developed using remotely sensed imagery estimation...
Motivated by the increasing availability of high-resolution satellite imagery, we developed deep learning models able to efficiently and accurately classify atmospheric conditions dominant classes land cover/land use in commercial PlanetScope imagery acquired over Amazon rainforest. In specific, trained convolutional neural network (CNN) perform multi-label scene classification (<;10 m) imagery. We also discuss challenges opportunities training CNN for classification. Finally, investigate...
A research alliance between the Commonwealth Scientific and Industrial Research Organization Geoscience Australia was established in relation to Digital Earth Australia, develop a Synthetic Aperture Radar (SAR)-enabled Data Cube capability for Australia. This project has been developing SAR analysis ready data (ARD) products, including normalized radar backscatter (gamma nought, γ0), eigenvector-based dual-polarization decomposition interferometric coherence, all generated from European...
A method for the decomposition of radar polarization signatures is developed. The backscattering model assumed to consist odd, double, Bragg, and cross components, Mueller matrix sum matrices these four scattering mechanisms. technique least squares (LS) then used find best combination components. Using NASA/Jet Propulsion Laboratory (JPL) AirSAR data, results agree with general understanding backscatter. In most cases, accuracy more than 95% linear polarizations 85% any other polarizations.
Abstract. Accounting for groundwater recharge from overbank flooding is required to reduce uncertainty and error in river-loss terms sustainable-yield calculations. However, continental- global-scale models of surface water–groundwater interactions rarely include an explicit process account flood (OFR). This paper upscales previously derived analytical equations a continental scale using national soil atlas data satellite imagery inundation, resulting maps seven hydrologically distinct...