Upload & QAC
Data and metadata problems are identified while they can still be resolved.
RAW EVIDENCEReef-scale AI · human judgement
Turn reef imagery into trusted evidence.
COTSpotter connects AI analysis, human validation and integrated reef data to help us see crown-of-thorns starfish sooner and act with greater confidence.
ObserveAnalyse
ValidateDecide
Begin the dive
01 / NATIVE PREDATOR
The challenge
Native to the Reef.
Destructive at outbreak scale.
Crown-of-thorns starfish naturally feed on coral. The management problem begins when their abundance reaches outbreak levels and coral loss outpaces recovery.
Why do we need COTSpotter?
Cryptic
Often hidden within complex reef structure
Mobile
Outbreaks can spread across connected reef systems
Cyclical
Outbreaks recur, making earlier detection especially valuable
Resource-limited
Surveillance and control effort must be directed where it has most impact
From balance to outbreak
Outbreaks are cyclical. Earlier detection provides more time to target surveillance and control before coral predation accelerates.
Three complementary views
Each method sees the Reef differently.
Manta tow provides broadscale surveillance. ReefScan imagery creates persistent, reviewable evidence. Cull operations provide direct observations during targeted control. Each method answers a different question, with different constraints in coverage, timing and effort.
Different purpose. Different resolution. Different effort. COTSpotter helps connect these observations without treating them as equivalent.
Why COTSpotter
More observations must not create an unmanageable review burden.
Image-based surveys create persistent evidence, but manual review of thousands of images does not scale. COTSpotter combines on-the-fly quality checks, AI-assisted detection and focused human validation to reduce the time from collection to usable evidence.
The COTSpotter workflow
Machines review the volume.
People provide the judgement.
COTSpotter reduces the time between image collection and reviewable evidence while preserving human judgement, provenance and uncertainty.
AI detection
AI identifies COTS observations across large image collections.
MACHINE ASSISTEDHuman validation
People confirm, reject or flag uncertain detections.
REVIEWEDIntegrated products
Traceable evidence returns as maps, reports, data and APIs for planning and control.
DECISION READY
Human validation
Review likely evidence—not every frame.
COTSpotter presents candidate detections in a focused review workflow. Validators can quickly confirm a COTS, reject a false detection, or flag an uncertain case for expert review.
Validation workflow
Evidence across scales
Where surveys overlap, the signals align.
Image-derived detections show promising spatial agreement with established manta tow and cull evidence. The comparison is encouraging—and still needs more matched data.
Read with care: blank areas are often gaps in effort or timing—not evidence that methods disagree. Robust comparison requires calibration for differences in method, detectability, coverage, location and timing. That calibration is also necessary before using image-derived evidence for historical trends, time-series inference or operational thresholds within COTS integrated pest management.
The current constraint
Collection must scale. Processing time must not scale with it.
The June 2026 snapshot covers approximately 30 months of data from January 2024. Image surveys covered about one-tenth the measured distance of the established manta tow record. The smaller evidence footprint reflects lower deployment effort, while conventional image review remains labour-intensive. Automated QAC, AI triage and focused validation make expanded image collection more operationally feasible.
Measured survey distance
9.04× gap
Manta tow8,184 km
Image survey905 km
8,184 km ÷ 905 km = 9.04
| Method | COTS evidence | Survey / records | Effort | What it contributes |
|---|---|---|---|---|
| Cull | ~125,000 | ~28,000 | 1,444 days | Direct control evidence and a large operational record |
| Manta tow | ~3,000 | ~41,000 | 8,184 km | Long-running, broadscale visual surveillance |
| Image | 251 | 618 | 905 km | Persistent, reviewable, high-detail evidence |
What comes next
Expand matched image collection and calibration to support defensible density estimates, time series and decision thresholds—not just promising spatial agreement.
Built through collaboration
Every partner closes a different gap.
Reef evidence often sits across organisational, technical and operational boundaries. Important context can be delayed or lost when field observations, imagery, analysis and management systems remain disconnected.
Shared evidence closes gaps between institutions.
COTSpotter and its cloud infrastructure can provide a traceable evidence layer across those boundaries—connecting provenance, review decisions, maps and reusable data products while preserving each partner's responsibilities and data governance.
GBRF
Funding, COTS Control Innovation leadership and coordination.
GBRMPA + QPWS
Management context, RJFMP field operations and workflow collaboration.
AIMS
ReefScan platforms, image generation, provenance and deployment of edge AI.
TensorFlow/Kaggle origins, large-scale data collection support, and cloud, Vertex AI and Gemini technology.
CSIRO
AI research, integration, validation, analytics and data products.
Information for Sea Country
Better reef evidence can support understanding of Sea Country health and condition.
COTSpotter data can help Traditional Custodians see where and when COTS surveys have occurred and what was observed. Initial engagement is planned for the coming months, with the project fact sheet providing a practical starting point for those conversations.
Download the project fact sheetThe workflow is built
Now scale the evidence.
Help expand matched image collection, calibration and operational adoption for the people protecting the Reef.