Remote Sensing for Disaster Response Training Course

Participants can combine hazard, exposure and vulnerability information for spatial assessment planning.

• Hazard footprints distinguished from exposure and vulnerability layers
• Administrative boundaries, settlements and facilities prepared for response mapping
• Population datasets assessed for resolution, currency and displacement limitations
• Critical infrastructure inventories matched to likely disaster impacts
• Baseline maps established before events for post-event comparison
• Data dictionaries define attributes, sources, dates and confidence ratings

Participants can select sensor types and acquisition options against an incident information need.

• Optical, thermal, LiDAR and SAR sensors compared for disaster tasks
• Spatial, spectral, temporal and radiometric resolution matched to requirements
• Cloud cover, revisit intervals and tasking windows assessed systematically
• Drone, aircraft and satellite platforms selected using operational constraints
• Acquisition plans specify area of interest, dates and priority outputs
• Open, commercial and emergency imagery sources evaluated before procurement

Participants can interpret optical imagery features relevant to disaster impacts and conditions.

• True-colour and false-colour composites reveal land and water conditions
• Visual interpretation uses tone, texture, pattern, shape and association
• Normalized Difference Vegetation Index identifies vegetation disturbance and recovery
• Normalized Difference Water Index supports surface-water identification
• Shadow, haze and cloud effects distinguished from actual damage
• Image interpretation keys document observable features and likely meanings

Participants can interpret core SAR backscatter patterns for flood and surface-change assessment.

• SAR backscatter explained through wavelength, roughness, moisture and geometry
• Sentinel-1 acquisition modes, polarization and orbit direction selected appropriately
• Speckle, layover, foreshortening and shadow identified in radar scenes
• Pre-event and post-event SAR scenes aligned for change analysis
• Coherence products indicate surface disturbance after earthquakes and landslides
• Radar interpretation limits stated clearly in operational reporting

Participants can prepare imagery for analysis and identify processing issues affecting conclusions.

• Coordinate reference systems checked before combining imagery and vector layers
• Georeferencing accuracy assessed using control points and residual errors
• Atmospheric correction improves comparability between optical image dates
• Cloud masking and shadow masking remove unreliable optical pixels
• SAR calibration, terrain correction and filtering prepared in SNAP
• Metadata records source, acquisition time, processing steps and limitations

Participants can apply and interpret change detection methods for event impact assessment.

• Image differencing compares calibrated pre-event and post-event observations
• Band ratios highlight water, vegetation loss and burn impacts
• Change Vector Analysis identifies magnitude and direction of spectral change
• Coherence change detection identifies disturbed surfaces after ground movement
• Thresholds selected using reference samples and visual inspection
• False changes traced to seasonality, illumination and registration errors

Participants can create classified impact layers using suitable reference data and accuracy checks.

• Supervised classification uses representative training samples and defined classes
• Random Forest classification applied to multispectral disaster imagery
• Object-based image analysis groups pixels into meaningful mapped features
• Building footprints, roads and water bodies extracted from available data
• Confusion matrices report producer, user and overall accuracy
• Class definitions prevent ambiguous interpretation during response reporting

Participants can produce and qualify flood extent maps from optical and SAR data.

• Flood mapping workflow distinguishes permanent water from event inundation
• SAR thresholding identifies open-water flooding beneath cloud cover
• Optical water indices supplement radar results during cloud-free periods
• Terrain, drainage and river networks checked against mapped flood patterns
• Flooded roads, settlements and cropland intersected with exposure layers
• Inundation uncertainty documented for vegetation, urban areas and shadows

Participants can assess wildfire extent, burn severity and recovery indicators from imagery.

• Normalized Burn Ratio calculated from near-infrared and shortwave infrared bands
• Differenced Normalized Burn Ratio classifies relative burn severity
• Active fire products compared with burned-area mapping outputs
• Thermal anomalies interpreted alongside weather and fuel conditions
• Burn perimeter maps intersect assets, habitats and populated places
• Post-fire erosion and debris-flow susceptibility indicators identified spatially

Participants can identify remotely observable damage proxies and prioritise areas for verification.

• Building damage proxies distinguished from confirmed structural damage
• Post-earthquake coherence loss highlights potential ground and building disturbance
• Landslide scarps, debris paths and blocked channels identified visually
• Cyclone wind damage inferred from roofs, vegetation and debris patterns
• Road obstruction and bridge disruption mapped for access planning
• Priority verification zones ranked using impact indicators and exposure

Participants can integrate field observations with remotely sensed findings for validated assessments.

• Field data collection forms capture location, observation and confidence
• KoboToolbox surveys structured for rapid damage and access verification
• Ground control observations sampled across mapped impact classes
• Crowdsourced reports screened for duplication, bias and positional accuracy
• Discrepant field and image findings investigated through evidence review
• Validation plans specify sample sizes, responsibilities and reporting thresholds

Participants can produce map products and briefings suitable for response coordination meetings.

• Map layouts prioritise operational questions, scale, legend and source attribution
• Situation maps show affected areas, access routes and critical facilities
• Analytical maps distinguish observed impacts from modelled estimates
• ISO 22320 principles inform incident information and reporting arrangements
• Map annotations communicate date, time, coverage and confidence clearly
• Decision briefings frame findings, limitations and recommended verification actions

Participants can apply quality controls and communicate uncertainty in emergency geospatial products.

• Quality assurance checklist covers geometry, attributes, symbology and metadata
• Positional, thematic and temporal accuracy reported using defined measures
• Uncertainty statements distinguish data limitations from analyst judgement
• Version control records updates to datasets, maps and assumptions
• Data protection requirements applied to sensitive population and facility information
• Peer review procedures identify errors before operational dissemination

Participants can design a repeatable imagery-analysis workflow aligned to response timelines.

• Trigger matrix links hazard alerts to imagery acquisition decisions
• Standard operating procedures assign roles for analysis, review and release
• Service-level timelines define first-look, assessment and update products
• Task prioritisation balances life safety, access and critical infrastructure
• Partner coordination identifies authoritative datasets and duplication risks
• Escalation procedures address contradictory evidence and high-consequence findings

Participants can assemble the technical and operational components of a response assessment package.

• Incident brief converted into questions, indicators and analytical outputs
• Area of interest and baseline datasets prepared for selected scenario
• Processing workflow documented from raw imagery through final classification
• Exposure analysis estimates affected people, assets and service locations
• Quality review records assumptions, evidence gaps and confidence levels
• Response product set prepared for operational handover and updates

Participants can build, review and present a complete remote sensing assessment package for an incident response.

• Incident scenario establishes hazard, affected area, constraints and decision priorities
• Data selection justifies sensor choice, dates and spatial coverage
• Analysis outputs include impact map, exposure summary and confidence statement
• Quality review tests processing choices, classifications and map readability
• Operational briefing recommends verification, prioritisation and information updates
• Peer feedback assesses technical defensibility and response usefulness