Earth Observation Early Warning & Response
An open, contributor-friendly project to turn Earth observation into earlier warnings and better response decisions for catastrophic risk.
Introduction & Rationale
Earth observation (EO) systems already monitor floods, fires, drought, storms, conflict-related destruction, and more.
But in many high-stakes scenarios, the limiting factor is not "more imagery". It is the end-to-end chain from
sensing to decision-ready signals: clear definitions of what to detect, how quickly, at what spatial scale,
with what confidence, and how those signals translate into actions.
This project aims to produce an open, practical early-warning and response framework for catastrophic risk.
The unique contribution is a decision-first EO architecture: start from the response decisions that matter,
derive the minimum viable signals and latency requirements, then map to feasible sensing and processing pipelines.
What makes this project new
- Decision-first requirements. We start from concrete response decisions and work backwards to sensing requirements (latency, coverage, resolution, confidence, false alarm tolerance).
- Multi-hazard, multi-signal. We treat EO as a portfolio of signals (optical, SAR, thermal, RF, atmospheric) rather than a single sensor type.
- Failure-mode aware. We explicitly design for degraded infrastructure: cloud cover, comms disruption, model drift, adversarial conditions, and data access constraints.
- Contributor-friendly task packaging. Work is broken into discrete, mergeable tasks with dependencies and clear outputs.
Research Objectives
- Define a short list of catastrophic-risk scenarios where EO can realistically change outcomes in days-to-weeks timescales.
- Specify decision-ready signals and requirements (what to detect, by when, and with what confidence).
- Map those requirements onto feasible architectures (sensors, orbits, ground segment, processing, dissemination).
- Produce an open reference playbook: signals, pipelines, evaluation protocol, and a pathway to pilots.
Methodology (high level)
- Scenario selection: pick 3–5 scenarios with clear decision points and credible data sources.
- Signal specification: define the minimal signals and their requirements (coverage, revisit, latency, spatial scale, uncertainty).
- Pipeline design: propose an end-to-end pipeline from raw data to alert product.
- Evaluation: define metrics and backtesting approach against historical events and open datasets.
- Operationalisation: produce a pilot plan and partner map.
EO Early-Warning Scenarios: Use-Case Shortlist
CompletedInputs:
- MPIL mission and catastrophic risk framing
- Existing EO capabilities and public datasets
- Response decisions that plausibly change outcomes (days-to-weeks)
Process:
- Select 3–5 scenarios and define the key decision points and stakeholders for each.
- Write a 1-page brief per scenario: what to detect, why it matters, and the rough decision timeline.
- Explicitly flag limits where EO can’t support a scenario without overclaiming.
Outputs:
- eoew_use_cases.md (scenario briefs + rationale)
Decision-Ready Signal Requirements (Latency, Coverage, Confidence)
CompletedInputs:
- Selected scenarios from the use-case shortlist
- Examples of EO alert products (public)
Process:
- For each scenario, define minimal signals and requirements: revisit, latency, spatial scale, false alarm tolerance, uncertainty reporting.
- Make requirements decision-first: tie each requirement to a real action that can be taken.
Outputs:
- eoew_requirements.md (requirements table + narrative)
Dataset & Sensor Inventory (Open Sources First)
OutstandingInputs:
- Selected scenarios from the use-case shortlist
- Public EO data catalogues (Sentinel, Landsat, MODIS/VIIRS, etc.)
Process:
- Build an inventory of candidate datasets/sensors per scenario, prioritising open access.
- For each source, record modality, latency, coverage, resolution, and key limitations.
Outputs:
- eoew_dataset_inventory.md (inventory table + notes)
Coverage/Revisit Simulation + Chart
OutstandingInputs:
- Decision-ready latency and revisit targets from requirements
- First-order constellation assumptions
Process:
- Run a lightweight revisit model to estimate feasibility bands for revisit/latency.
- Produce a chart for fast communication and a CSV for reproducibility.
Latency Budget (End-to-End)
OutstandingInputs:
- Scenario deadlines and operational needs
- Typical EO product delays and processing stages
Process:
- Decompose end-to-end latency into stages and identify dominant terms.
- Define target latency bands and minimum metadata requirements (timestamps, caveats).
Reference Architecture Sketches (End-to-End Pipeline)
OutstandingInputs:
- Decision-ready requirements
- eoew_dataset_inventory.md (completed inventory table)
Process:
- Sketch an end-to-end pipeline per scenario: ingest – preprocess – model/heuristics – alert product – dissemination.
- Include failure modes and degraded-ops assumptions.
Outputs:
- eoew_architecture_sketches.md (diagrams + narrative)
Evaluation Protocol (Backtesting + Metrics)
OutstandingInputs:
- eoew_architecture_sketches.md (agreed reference architecture)
- Historical event data for selected scenarios
Process:
- Define metrics: time-to-detect, false alarms, spatial accuracy, uncertainty calibration, operational latency.
- Specify a reproducible backtesting approach using open data where possible.
Outputs:
- eoew_evaluation_protocol.md (protocol + metrics)
Pilot Plan + Partner Map
OutstandingInputs:
- eoew_architecture_sketches.md (agreed reference architecture)
- Candidate stakeholders and implementers
Process:
- Propose a realistic pilot: scope, timeline, data access, success criteria, and governance.
- Map credible partners: existing EO programmes, NGOs, research groups, and operational agencies.
Outputs:
- eoew_pilot_plan.md (pilot outline + partner map)
Project Repository
This repository contains materials generated from the project.
- eoew_overview.md - Project overview and framing
- eoew_use_cases.md - Scenario shortlist (decision-first briefs)
- eoew_requirements.md - Signal requirements table
- eoew_dataset_inventory.md - Dataset and sensor inventory
- eoew_latency_budget.md - End-to-end latency model
- eoew_modelling_notes.md - Modelling scope and artifacts
- eoew_revisit_sim.py - Revisit/coverage simulation
- eoew_revisit_results.csv - Simulation results
- eoew_revisit_chart.svg - Chart (SVG)
- eoew_architecture_sketches.md - Reference architectures
- eoew_evaluation_protocol.md - Backtesting and metrics
- eoew_pilot_plan.md - Pilot outline and partner map