Remote Sensing in Humanitarian Operations Training Course

Participants can organise spatial reference information and humanitarian datasets for analysis.

• Coordinate reference systems selected for local mapping and distance calculations
• Vector features, raster grids, and attribute tables distinguished accurately
• Administrative boundaries, settlements, roads, and facilities structured as reference layers
• Scale, map extent, and positional accuracy assessed before interpretation
• Geocoding conventions applied to locations, incident reports, and assessment records
• QGIS project structure established for traceable humanitarian analysis

Participants can apply humanitarian data responsibility principles to remote sensing work.

• ICRC Professional Standards applied to sensitive spatial information products
• Data minimisation principles used when mapping vulnerable populations and sites
• Protection risks assessed before publishing displacement and shelter locations
• Informed consent limitations considered for drone and field validation data
• Licensing terms checked for commercial imagery, basemaps, and derived products
• Metadata records document provenance, restrictions, processing, and intended use

Participants can choose imagery sources that meet operational timing and analytical requirements.

• Sentinel-1 radar imagery selected for cloud-obscured flood monitoring
• Sentinel-2 optical imagery assessed for land cover and damage indicators
• Landsat archives used for longer-term environmental change analysis
• Commercial very-high-resolution imagery evaluated against tasking constraints and costs
• UAV imagery suitability assessed for site-level damage and infrastructure inspection
• Latency, revisit frequency, coverage, and cloud probability compared systematically

Participants can acquire, catalogue and prepare imagery for reproducible humanitarian analysis.

• Area-of-interest polygons created from operational boundaries and reported incidents
• Image acquisition criteria documented using date, sensor, cloud, and coverage
• Raster bands stacked, clipped, and reprojected within QGIS workflows
• Cloud masks and no-data values handled before optical image interpretation
• Radar backscatter products prepared with appropriate preprocessing documentation
• File naming conventions preserve acquisition dates, processing versions, and sources

Participants can interpret imagery features and classify basic land cover relevant to humanitarian operations.

• Tone, texture, pattern, shape, shadow, and association guide interpretation
• Training samples defined for water, built-up areas, vegetation, and bare ground
• Supervised classification principles applied to clearly specified land-cover classes
• Normalized Difference Vegetation Index interpreted for vegetation condition monitoring
• False-colour composites configured to distinguish water, vegetation, and settlements
• Classification errors identified through confusion matrices and reference observations

Participants can identify and explain meaningful spatial change between imagery dates.

• Pre-event and post-event imagery aligned for reliable temporal comparison
• Image differencing methods identify changed water, vegetation, and built-up surfaces
• Change thresholds tested against known locations and contextual information
• Time-series interpretation separates seasonal variation from crisis-related change
• Before-and-after map layouts communicate changes without overstating causation
• Analytical notes record assumptions, confounders, and confidence in findings

Participants can produce and validate a flood extent map using suitable imagery.

• Flood mapping questions framed around extent, depth proxies, and affected assets
• Radar backscatter changes interpreted for open-water and inundation detection
• Optical water indices applied where cloud conditions permit analysis
• Permanent water bodies masked using pre-event reference imagery
• Terrain, vegetation, and urban surfaces assessed as flood-detection limitations
• Flood extent validated against field reports, gauges, and authoritative situation data

Participants can identify damage indicators and produce qualified remote assessment findings.

• Damage assessment categories aligned with shelter, infrastructure, and service decisions
• Building footprints compared across imagery dates for visible structural change
• Road disruption indicators identified from washouts, debris, and surface changes
• Settlement damage proxies distinguished from confirmed household-level damage counts
• Very-high-resolution imagery interpreted using documented visual assessment criteria
• Confidence ratings assigned according to image quality and corroborating evidence

Participants can estimate exposed populations while documenting data limitations and assumptions.

• Hazard footprints intersected with population grids and administrative boundaries
• WorldPop and HRSL datasets compared for resolution and demographic assumptions
• Exposure estimates disaggregated by settlement, district, and service catchment
• Vulnerability indicators joined from assessment, census, and service datasets
• Double counting risks controlled across overlapping hazard and population layers
• Population estimates communicated as ranges with transparent methodological notes

Participants can assess settlement patterns and potential displacement indicators from spatial evidence.

• Settlement expansion patterns identified through multi-date imagery interpretation
• Shelter density proxies assessed using rooftops, plot patterns, and access routes
• Camp layout indicators reviewed for services, drainage, and firebreak planning
• Night-time lights interpreted cautiously for settlement activity and service disruption
• Protection-sensitive reporting avoids exposing routes, groups, and vulnerable locations
• Remote observations triangulated with registration, protection, and site-management data

Participants can use spatial analysis to support access planning and logistics decisions.

• Road networks cleaned for routing, accessibility, and bottleneck analysis
• Bridge, crossing, and landslide locations incorporated into route status maps
• Cost-distance analysis estimates travel constraints across damaged terrain
• Health facilities, warehouses, and distribution points mapped against affected populations
• Least-cost paths compared with reported access restrictions and security constraints
• Logistics maps distinguish verified route status from inferred accessibility

Participants can interpret environmental indicators for food security and anticipatory action decisions.

• Vegetation condition indices compared with seasonal baselines and rainfall data
• Standardized Precipitation Index interpreted alongside remote sensing drought indicators
• Cropland extent mapped using land-cover classes and agricultural calendars
• Surface water availability monitored using optical and radar observations
• Pasture condition findings linked cautiously to livelihood and market evidence
• Anticipatory action triggers documented with thresholds, lead times, and uncertainty

Participants can validate remote sensing outputs and document analytical quality for operational use.

• Ground truth sources assessed for timing, coverage, reliability, and bias
• Stratified sampling plans support efficient validation of classified map outputs
• Confusion matrices calculate overall accuracy, omission, and commission errors
• Independent review checks symbology, calculations, sources, and stated limitations
• Quality assurance logs record revisions, approvals, and unresolved analytical issues
• Uncertainty statements distinguish observed facts, estimates, and analyst interpretation

Participants can create clear maps and briefs that answer humanitarian operational questions.

• Map purpose, audience, and decision requested defined before product design
• Cartographic hierarchy uses titles, legends, labels, scale bars, and source notes
• Humanitarian Data Exchange datasets prepared using Humanitarian Exchange Language tags
• Situation maps combine hazard, exposure, access, and priority locations
• Analytical briefs present methods, findings, limitations, and recommended follow-up
• Dissemination plans specify formats, update cycles, access controls, and recipients

Participants can establish a coordinated workflow from request intake to product dissemination.

• Analysis requests screened against decision relevance, feasibility, and protection risks
• Terms of reference specify outputs, deadlines, sources, and acceptance criteria
• IMWG and cluster coordination requirements incorporated into product planning
• Version control procedures maintain traceable datasets, scripts, maps, and briefs
• Escalation pathways defined for conflicting evidence and urgent verification needs
• After-action reviews capture workflow lessons, delays, and data gaps

Participants can build, review and present a complete remote sensing assessment product for a humanitarian operational decision.

• Operational scenario translated into a defined analysis question and deliverables
• Imagery, reference layers, and secondary evidence selected using documented criteria
• Analysis workflow produces hazard, exposure, access, or damage findings
• Quality review tests accuracy, assumptions, protection risks, and map readability
• Decision brief communicates findings, limitations, priorities, and recommended actions
• Peer review and presentation defend methods against operational stakeholder questions