FunGIS Geospatial Excellence Awards Categories

2025 Winner: David Kettle

Email: david@fft.ai

Project Name: Seascape – Unlocking regional data-driven insights from marine baseline studies

Organisations : Flying Fish Technologies and CocoTell

 

Citation / Media Statement: Developed in collaboration with Flying Fish Technologies (FFT) and CocoTell, the Seascape project visualises over 350 km of underwater survey data collected via autonomous gliders along the Red Sea and Gulf of Aqaba. Using ArcGIS Hub, dynamic web maps, Experience Builder, and themed story maps, CocoTell transformed FFT's high-resolution observations of fish, coral, and reef topography into an intuitive platform, enabling clients to explore marine ecosystem health at scale and in detail.

 

Nomination: The Seascape project was delivered through a collaboration between Flying Fish Technologies (FFT) and CocoTell. FFT conducted a large-scale, autonomous underwater survey along ~356 km of the Red Sea and Gulf of Aqaba, capturing 2.9 million geotagged images. This dataset was processed into a geospatial dataset consisting of approximately 105M individual points covering coral reef health, fish populations, reef age, bathymetry, and marine megafauna. CocoTell’s role focused on transforming this high-volume dataset into an interactive, research-ready geospatial platform.  The complexity of the project stemmed from integrating diverse spatial data types including still imagery, transect data, biological observations, and classification metrics, and the need to create a web-based platform that would scale visually and functionally for research, exploration, and communication. The challenge was heightened by the need for spatial tools that could support millions of point data, images, species classifications, and habitat attributes in an accessible and intuitive format. This project directly supports evolving marine ecological research by enabling users to explore underwater glider-collected data through a highly accessible, spatially driven platform. The system supports fine- and broad-scale spatial analysis of fish assemblages, coral health, and anthropogenic threats such as fish traps, providing a new way to visualise and interpret subtidal marine ecosystems at scale. The platform turns raw, often inaccessible glider data into actionable insights for researchers, policymakers, and marine managers. It breaks down technical barriers by embedding research-grade data into dynamic web maps, heatmaps, and interactive dashboards, supporting new discoveries and research questions. This positions the project as a true geospatial enabler of knowledge creation. FFT used its Vertigo3 autonomous underwater glider, equipped with high-resolution cameras and navigation systems, to conduct extensive visual transects. The glider’s consistent altitude and overlap settings ensured accurate spatial referencing and ecological comparability across regions.

FFT processed the dataset using a combination of tools including:

·        Processing habitat and fish data using proprietary machine learning models built in PyTorch

·        Coral health classification using the CoralNet platform

·        Geospatial preprocessing (aggregations, binning, filtering) using Postgres, GeoPandas, Python, and the Parquet format

·        Microsoft Azure cloud storage and GPU to parallelise processing on 40+ GPUs

·        Principal components analysis in R

CocoTell processed the data into a multi-tiered ArcGIS environment through the use of clustering and heat maps, Experience Builder dashboards, integrated image popups, charts, and filters for temporal and spatial analysis, and story maps to communicate thematic findings (e.g. fish traps, sea cucumbers, turtles).Verification was achieved through image-based annotations, glider path validation, and spatial QA/QC during platform buildout. Reporting was facilitated through embedded dashboards and story-driven summaries that communicated key patterns and findings. The Seascape project demonstrates how emerging survey technologies, like autonomous underwater gliders, can be integrated with modern geospatial platforms to bridge the gap between data collection and research application. It showcases:

·        The fusion of marine robotics and GIS to support ecosystem-level insight

·        Scalable web-based delivery of complex data previously locked in imagery and spreadsheets

·        A user-first approach to visualising large datasets that promotes transparency, accessibility, and research

Seascape pushes the boundaries of what spatial storytelling and marine research can look like when paired with robust GIS tools. It provides a replicable model for future marine data visualisation efforts, especially where long-term monitoring and policy support intersect.

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2025 Winner: Jennah Williams

Email: jennah@esriaustralia.com.au

Project Name: Tiger Sharks of Norfolk Island

Organisations : Esri Australia

 

Citation / Media Statement: Jennah Williams and the Flinders University shark science team used stable isotope analysis and GIS tracking to research tiger sharks around Norfolk Island, ensuring the apex predator survived and thrived. This research is a compelling example of how GIS can be applied in marine science to address real-world sustainability challenges. It demonstrates how technology, science, and local knowledge can work together to support biodiversity and guide responsible human activity.

 

Nomination: The project spanned 4 years, with data still being collected today. The project was funded by Flinders University and Esri Australia. The Norfolk Island tiger shark project, led by Jennah Williams and the Flinders University shark science team, exemplifies how geospatial technologies can directly contribute to solving environmental challenges. By combining stable isotope analysis with satellite tracking and advanced GIS methodologies, the team mapped the movement patterns and feeding behaviours of tiger sharks around the island. This spatial insight helped address a critical environmental issue: the disposal of abattoir waste, and the risk to the population of Norfolk Island. Traditionally, discarded cow carcasses were released into the ocean, unintentionally attracting tiger sharks and altering their natural behaviour and ecosystem dynamics. Through geospatial analysis, the team identified key migratory routes and feeding zones, allowing them to recommend alternative waste disposal strategies that would protect both the marine environment and its apex predators.

This innovative, science-based solution helped ensure the long-term sustainability of the shark population and the broader ecosystem, demonstrating how spatial thinking and GIS can drive practical, impactful environmental outcomes. This project required years of data collection, tagging tiger sharks, undertaking advanced scientific processes such as isotope analysis and brave researchers to protect this misunderstood creatures. This research has been published in scientific journals, and presented as a StoryMap. By integrating satellite telemetry, stable isotope analysis, and cutting-edge GeoAI, the team was able to gain unprecedented insight into species behaviour and environmental impact. GeoAI played a pivotal role in species identification and ecological analytics by processing vast datasets—such as movement patterns, habitat use, and prey detection—with speed and accuracy beyond human capacity. This enabled the team to detect behavioural shifts in the tiger sharks in response to the island’s waste disposal practices, identifying spatial and temporal trends that were previously invisible.

 

At its core, this project reflects the "Grass Roots and Green" ethos by using sophisticated technologies to address a hyper-local environmental concern—safeguarding Norfolk Island’s apex predators and marine biodiversity, that can be transferred into a nationwide project. By grounding advanced GIS and AI capabilities in community-focused conservation outcomes, the project exemplifies how innovative tools can empower sustainable decision-making at the grassroots level.

2025 Winner: Lil Cornish

Email: lil.cornish@hotmail.com

Project Name: Statewide Indicator Framework Mapping and Monitoring Setup (SMMS) Tool

Organisations: CocoTell & NQ Dry Tropics

 

Citation / Media Statement: The SMMS Tool empowers non-GIS professionals to consistently map, monitor, and report environmental outcomes using the State-wide Indicator Framework. Developed collaboratively by NQ Dry Tropics and CocoTell, this ArcGIS-based tool automates spatial workflows, ensuring credible, standardised data capture across Queensland’s natural resource projects, transforming how ecological change is planned, tracked, and communicated.

 

Nomination: The SMMS Tool (State-wide Indicator Framework Mapping and Monitoring Setup) project commenced in 2024 and continues in active rollout through 2025. Developed collaboratively by NQ Dry Tropics and CocoTell, the project was funded under Queensland Government programs supporting regional NRM bodies. This project addresses a high degree of complexity. It harmonises statewide monitoring requirements across varied landscapes and stakeholders with automated spatial workflows, attribute logic, and user guidance, delivered via ArcGIS tools. The tool pushes the limits of Esri’s platform, particularly through its use of ArcGIS Tasks, a capability withy limited documentation and community support, requiring extensive customisation and testing. The result is a standardised environmental monitoring tool that scales, from isolated paddock sites to regional and statewide program-level reporting. The SMMS Tool is directly benefiting Far North Queensland by enabling NRM organisations, landholders, and project officers in tropical regions to accurately map, monitor, and report environmental outcomes in complex and remote landscapes. By automating workflows through ArcGIS Tasks, Survey123, Python scripting, and structured monitoring plans, the tool drastically reduces the GIS knowledge barrier for frontline staff across the tropical north. The ability to apply the tool to riparian restoration, wetland health, gully erosion, and vegetation improvement in diverse tropical ecosystems makes it locally adaptable yet consistently reportable across projects in FNQ. The SMMS Tool is built on the State-wide Indicator Framework, an established logic model used in Queensland NRM programs. The tool automates that framework through a series of Esri Tasks and scripted processes in ArcGIS Pro.

It includes:

·       Outcome polygons coded with domain-linked deliverables and outcomes•            Randomised monitoring plots assigned based on outcome type

·       Integrated Survey123 forms for activity and monitoring data capture

·       Field verification workflows for accuracy and confidence

·       A central ArcGIS Hub site with dashboards for filtering, reviewing, and reporting. Validation occurs via in-field data checks using Field Maps, verification steps within the Task system, and automated rule enforcement (e.g. overlap checks, stratification, ID generation).

Final data is aggregated via consistent geodatabase schemas and monitoring scores (e.g. VegCAT, LCAT), enabling quantifiable environmental reporting. The SMMS Tool represents a novel integration of Esri’s platform capabilities into a single, guided process that non-specialists can follow. Innovations include:

·       A clear step-by-step ArcGIS Task interface to support users with limited GIS experience

·       Python-scripted automation for unique IDs, layer statuses, plot assignment

·       Cross-org reusability via AGOL-hosted templates

·       A dynamic, structured ArcGIS Hub site built with Experience Builder to enable filtering by project status, location, or monitoring outcome

By embedding logic, structure, and reportability into a streamlined geospatial package, the SMMS Tool bridges the gap between GIS expertise and regional environmental project delivery, a major need in resource-limited areas like Far North Queensland.

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