Research Projects

The Queensland Earth Observation Hub (EO Hub) is driving the growth of Queensland’s space industry by providing financial, in-kind and business support to companies and academic institutions in developing innovative Earth observation technologies. The EO Hub facilitates research projects through three programs:

• Calibration & Validation Projects
• Mobility Scheme
• Partnering Program

Supported by SmartSat CRC and the Queensland, these projects are accelerating the growth of the Earth observation industry, supporting commercialisation of research, and EO product and service development.

COASTS:  COASTAL CHANGE OBSERVATION AND ANALYTICS(MULTI-) SCALE (MULTI-)TECHNOLOGY SYSTEM

PARTNERING PROGRAM

Understanding complex coastal processes and interactions between land, sea and human communities is of primary concern at all levels of government, as well as industry. The rapidly increasing population along Queensland’s extensive coastline of low-lying areas and sandy beaches is particularly vulnerable to exposure from wave and climate events, including cyclones and storms, that can lead to extensive coastal erosion, inundation and changes in the shallow water bathymetry and habitats. Frequent, high-quality spatial information across the coastal zone is required to monitor, manage and predict coastal change and its associated hazards. However, these data are seldom available. An example would be the need for timely data immediately prior, during, and after a storm event. Building an understanding of coastal response to both gradual and extreme events is especially critical in an era of progressively rising sea levels which are likely to exacerbate already existing trends.

The Coastal Change Observation and Analytics (multi-) Scale (multi-) Technology System (COASTS), will directly address the issue of the lack of coastal monitoring data and thus fill gaps in our understanding of coastal change, including responses to storm events, by developing a state-of-the-art coastal monitoring system that will facilitate coastal adaptation to climate change and build resilience against coastal hazards. The novel project approach will leverage the use of satellite imagery, drones, numerical modelling, artificial intelligence-based analytics and cloud-based portal technology to cost-effectively derive and deliver information and tools that fill the gaps in our understanding of coastal processes, coastal hazards and beach safety. The outcomes of this project are key to both government and industry in building expertise and improving evidence-based strategic planning and adaptive coastal management.

P6.02

Project Leader:
Dr Javier Leon, University of the Sunshine Coast

Participants:

LIVING AND PLAYING TOGETHER: AN INTERACTIVE INFORMATION AND VISUALISATION INTERFACE FOR THE SUSTAINABILITY OF MULTIPLE USES AND VALUES OF MORETON BAY

PARTNERING PROGRAM

Moreton Bay (the ‘Bay’), in Quandamooka Country, is one of Australia’s most intensively used coastal systems, offering economic, environmental, cultural, and social/recreational values. It also includes important marine ecosystems, supporting a diversity of marine wildlife and habitats. Economically, Moreton Bay supports key industries (e.g., fishing, aquaculture, tourism, recreational boating), contributing more than an estimated ~$950+ million to the region annually. These multiple uses of Moreton Bay, and the various threats to such values and uses (including from climate change and increased usage by a growing urban population), must be managed to ensure long term sustainability of values, marine biodiversity, and industries.

The project will combine remotely sensed EO and underwater data to develop key outputs for diverse Moreton Bay stakeholders, across government, industry, research and the public.

Key aims, activities, and expected outputs and benefits of this project are to:

1. Use Earth Observation (EO) and underwater data to create an interactive “Living Together” interface and associated machine learning (ML) algorithms and information visualisation related to recreational boating activity and marine biodiversity in the Bay;
2. Enable a wide range of Moreton Bay stakeholders (including industry, marine and maritime authorities, Government (local, state, and national), researchers, and the public) as end-users of the project outputs, and information products and services based on these outputs;
3. Through end-user uptake and use of the project outputs, achieve: (i) improved knowledge amongst Moreton Bay stakeholders of its marine diversity, marine (recreational boating) activities, and social values; (ii) evidence-based management and safe use of Moreton Bay;
4. Provide a springboard for a larger project and as a contribution and interface with other EO projects such as the CSIRO led Aquawatch program.
   

P6.03

Project Leader:
Professor Kerrie Mengersen, Queensland University of Technology

Participants:

WHAT IF SATELLITES ARE WRONG? HOW DRONES CAN UNCOVER THE HIDDEN TRUTHS

CALIBRATION & VALIDATION PROJECT

Every day, scientists and environmental managers around the world rely on satellite derived products to make data-driven decisions. But what if those data are wrong? Calibrating and validating these products is costly, time consuming, and often limited by the geographic reach of field teams. As a result, some products have limited or no accuracy metrics available.

This project will use the vast coverage of drone data available on GeoNadir to build a comprehensive library of data labels suitable for calibrating and validating satellite data products. The library will meet the formats and metadata requirements to enable users to ingest into their machine learning analytics or GIS platforms of choice. This will ultimately allow users to achieve greater accuracy with their products through high quality calibration, and to have greater confidence in their validation metrics.

P6.04

Project Leader:
Associate Professor Karen Joyce, James Cook University

Participants:

RISKSSMART: DIGITAL TOOL FOR DE-RISKING SORGHUM PRODUCTION DECISIONS

PARTNERING PROGRAM

Sorghum is the third largest grain crop and the main dryland summer crop in north-eastern Australia, with Dryland sorghum producers progressively confronted by the effects of climate change, including increasing frequency of droughts, floods and days of extreme heat. Initial starting soil moisture (ISW) at sowing can explain up to 50% of the variability in harvested sorghum yield in Queensland, but measuring ISW using soil core samples and/or ground sensor measurements is a manual and expensive process.

This project will utilize high-temporal-spatial-spectral resolution satellite data to derive surrogate and calibrated sensing metrics for estimating ISW status (dry to wet) at 5-day temporal and 20m temporal scales.

The specific objectives of the project are:

• Deriving and exploring the algorithms for estimating relative soil moisture status from earth observation data and sensing metrics through AI and digital technologies.
• Mapping of relative soil moisture status (%) across different sorghum cropping regions and seasons within fields (sub-paddock) scales and specific genotype, environment, and management combinations.
• Determining early-season crop management zones derived from the relative soil moisture status (%) utilising an integrated approach through machine learning and remote sensing at field and farm scales.
• Simulating sorghum crop yield for different specific genotype, environment, and management combination crop management options for the sorghum study farms.
• Validating a prototype risk tool for optimising sorghum production at field scales before sowing.
  

P6.05

Project Leader:
Associate Professor Andries Potgieter, The University of Queensland / Queensland Alliance for Agriculture and Food Innovation

Participants:

DEVELOPING CAPABILITY TO ASSESS LIVE CORAL COVER AND SEAGRASS SPECIES USING SATELLITE BASED HYPERSPECTRAL IMAGERY

PARTNERING PROGRAM

Live coral cover and seagrass species composition are key indicators for scientists and managers to assess the health of coral reef habitats. The ability to differentiate between live and dead coral, seagrass species and other bottom features is driven by the density of cover and the spectral characteristics of the features. Research into the ability to detect live coral cover and differentiate seagrass species based on spectral reflectance properties has demonstrated that hyperspectral information (opposed to multispectral) is required.

Currently there have not been any successful attempts to map seagrass species composition across very large spatial extents (e.g. regional to global) nor live coral, with only a handful of examples at local scales (single reefs/meadows to small groups). As part of the Allen Coral Atlas, the UQ team mapped coral habitat globally but were not able to differentiate seagrass species and density, nor live coral cover. This mapping was constrained by the availability of only multispectral sensors (e.g. Sentinel 2, Landsat, Planet Dove) that cover large spatial extent and provide feasible complete global coverage of the world’s coral reef habitats. The increasing numbers of hyperspectral satellites being launched since 2021, including public good and private-industry systems, capable of global coverage provide the opportunity to investigate these challenges and there is now a need to develop remote sensing frameworks to assess their capability for live coral and seagrass cover mapping. This work aims to acquire very high quality archived hyperspectral data for reef and seagrass environments, in conjunction with field data to test the coral and seagrass properties that can be differentiated from different spatial-spectral-radiometric dimensions to inform processing from current and future hyperspectral satellites, such as Australia’s Kanyini satellite. Findings from this study may also provide the roadmap for a follow-up phase, to map live coral on shallow coral reefs and seagrass in Australia and globally, providing essential information to coral reef scientist and managers.

P6.07

Project Leader:
Associate Professor Chris Roelfsema, The University of Queensland

Participants:

VALIDATION OF SATELLITE-DERIVED IN-LAND WATER TOPOGRAPHY MAPS USING KURLOO MASS DEPLOYABLE GLOBAL NAVIGATION SATELLITE SYSTEM (GNSS) PRECISE POSITIONING TECHNOLOGY.

CALIBRATION & VALIDATION PROJECT

There is a growing dependence of satellite Earth Observation data for decision making both in Australia and Globally. Increasingly corporate and government decision making rely in some way on EO services to inform decisions. It is therefore critical that EO-derived products are validated to ensure they are fit for this purpose.

In this 12-month project the partners will seek to evaluate Kurloo technology as a suitable solution for retrieving absolute water height time series data that can be used for Earth Observation product validation. This will be achieved by further developing the Kurloo innovative low-cost GNSS positioning system and service so that it can be applied in a new application area within Earth Observation Satellite calibration and validation.

The evaluation of Kurloo will leverage the existing CSIRO calibration facility at Googong reservoir, New South Wales, where Kurloo data will be collected over an 8-month period as part of this project. The output of this activity will support CSIRO in planning an Earth Observation satellite calibration and validation national facility – “AusCalVal”.

Future activities could see Kurloo apply this method more broadly to utilise absolute positioning to validate and calibrate other earth observation systems more simply and economically than ever before, lowering risks for earth observation research and development by increasing consistency across science and research and improving the reliability and accuracy of location analytics and spatial analysis.

P6.08

Project Leader:
Lee Hellen, Kurloo Technology

Participants:

QUANTIFICATION OF THE CLIMATE RISK ON THE CROP PRODUCTIVITY OF THE DOMINANT SOIL TYPES IN QUEENSLAND UNDER FUTURE CLIMATE CHANGE SCENARIOS

MOBILITY SCHEME

This project will support a secondment of a UniSQ researcher to NGIS to develop a prototype toolkit to integrate satellite data with Agricultural Production Systems Simulator (APSIM) to calibrate and validate the model at a given geolocation for different crops and apply climate change scenarios projected by the emission scenarios of different Representative Concentration Pathways.

Development through the secondment will be supervised by NGIS Data Scientists and allow the secondee to help develop this data product, upskill on Google Earth Engine and Google products, and develop connections with relevant valuable industry contacts.

P6.09

Project Leader:
Associate Professor Keith Pembelton, University of Southern Queensland

Participants:

A ROBUST AND SCALABLE DISTRIBUTED DRONE DATA MANAGEMENT PIPELINE TO SHARE DRONE DATA PROCESSING

MOBILITY SCHEME

Due to their ability to collect large amounts of high-resolution data, the use of drones is rapidly growing in environmental monitoring. For drone technologies to realise their full potential in supporting improved understanding and management of landscapes, systems are needed to support the storage, analysis and sharing of this data.

TERN, Australia’s land ecosystem observatory, has trialled collecting drone data at ecosystem surveillance sites, along with detailed field collected data on vegetation and soil attributes including specimen collection. Drones will now be routinely flown at all of TERN’s 900 sites (sites are revisited every 3-10 years to allow the detection of environmental change). In addition, drones will be used to collect data for calibration and validation of remote sensing data products. This usage will result in large volumes of drone data collected that need on-time processing, visualisation and FAIR (findable, accessible, interoperable and reusable).

GeoNadir provides a platform and tools for users to store, process, and share drone mapping data around the globe. GeoNadir is the only Earth observation platform focusing on FAIR drone data, and the only FAIR drone data platform focusing on environmental Earth observation. As of November 2023, the platform hosts 860K+ images from 68 countries.

The aim of this project collaboration between TERN and GeoNadir is to build a robust and scalable distributed drone data management pipeline to share drone data processing and publication activities between GeoNadir and TERN. In addition, the processing pipeline will be aligned with the TERN data management practices that support researchers and environmental managers. The project would aim to leverage GoeNadir’s capability to process drone data for TERN and publish them in TERN’s repository, and build a federated model to search and discover TERN drone data from GeoNadir and vice versa.

P6.10

Project Leader:
Paul Mead, GeoNadir

Participants:

SMARTCOAST: COASTAL MANAGEMENT DIGITAL TWIN PILOT IN TORRES STRAIT, QUEENSLAND BASED ON LIDAR AND SATELLITE EO DATA FUSION, WITH A FOCUS ON MANGROVES

Partnering Program

Mangrove conservation is vital in supporting carbon reduction measures. In addition, through the development of validated methodologies to measure and monitor their health, there is the potential for blue carbon credit markets to generate private investment, such as through innovative financial products provided by Queensland based EcoMarkets Australia. This would potentially support the adaptation of our coastal communities to climate change via the protection and restoration of these vital ecosystems, whilst reducing cost risk exposure of state and local governments to growing physical climate risk.
Several islands in the Torres Strait are predominantly made up of intertidal swamps, which are home to mangroves. The Torres Strait Rangers have partnered with MangroveWatch to monitor mangroves and shorelines around the Torres Strait, highlighting the importance of these habitats to the local community.

SmartCoast’s 3D digital twin pilot will facilitate science communication for coastal management to non-technical users (decision-makers or coastal community members) in the Torres Strait. Through a Queensland based research-industry collaboration between James Cook University, EOMAP and Fugro this project will apply world-leading scientific information on mangroves to support coastal management from remote sensing data and generate a positive socioeconomic impact for Queensland. This project will develop a new methodology to detect and monitor mangroves using satellite and LiDAR fused techniques which will then be applied to mangroves in Torres Strait. This will be the input for a co-designed coastal management digital twin pilot: a digital lab that can be used to perform rapid prototyping design with key stakeholders to develop a robust and viable digital decision-making tool for coastal ecosystem management in Queensland.
This pilot project demonstrates the application of earth observations and complementary technologies for identifying, monitoring and ultimately conserving coastal natural capital that is impacted by climate change. A successful pilot will drive the demand for more EO data for other coastal management and planning projects.

P6.11

Project Leader:
Paul Seaton, Fugro Australia

Participants:

CALIBRATION AND VALIDATION OF SAR AND STEREO/TRI-STEREO SATELLITE DATA FOR ASSESSING VEGETATION CONDITION

CALIBRATION & VALIDATION PROJECT

Local councils urgently require evidence-based rapid evaluation of vegetation to evaluate current management practices (restoration action), monitoring vegetation condition (state of environment reporting), carbon accounting and fire risk assessment.

The use of Synthetic Aperture Radar (SAR) data for vegetation assessment by local councils in Queensland has been constrained by a lack of development and use of accessible analytical tools. To understand the complex relationships between the variables and developing algorithms, deep learning algorithms are evolving, which can fill the gap in accurate model development, calibration, and validation. Similarly with new advanced sensors the vegetation indices and biomass estimation power can be increased significantly. Additionally, it is now possible to integrate multi-sensors from multiple orbiting satellites for better integration and development of models. Thus, it can provide a synergistic evaluation of sensors and algorithms for different forest products development in real or near real time for implementation in environmental management.

The Queensland based collaboration between the University of the Sunshine Coast, Geoimage and the Council of the City of Gold Coast aims to create, calibrate and validate the analytical tools needed to interpret satellite-based Tri-Stereo Optical (multi-spectral) and SAR data sets to assess vegetation structure within the Council of the City of Gold Coast – Restoration Dynamics Project (RDP). The RDP is investigating the success of restoration through time (chrono-sequencing) covering a wide range of vegetation structures (from open grassland through to remnant forest). The vegetation metrics derived from the satellite imagery will be compared with LiDAR and on-ground vegetation BioCondition measures and used to inform these success measures. The outcomes and technical tools developed will be used to analyse vegetative response to management actions, with a broad range of benefactors (local government, NGO and industry).

P6.12

Project Leader:
Dr Jean-Marc Hero, City of Gold Coast

Participants: