Climate Security Intelligence Using GIS Training Course

Participants can create a collection plan that links intelligence requirements to decisions and evidence sources.

• Intelligence requirements matrix linking decisions, users, locations, indicators and thresholds
• Key intelligence questions structured with who, what, where, when and why
• Decision calendars aligning seasonal monitoring windows with operational planning cycles
• Source reliability ratings using Admiralty Code provenance and credibility criteria
• Collection plans separating baseline layers, near-real-time feeds and field observations
• Information gaps logged with collection priority, owner, deadline and acceptance criteria

Participants can design a GIS data structure appropriate for climate-security analysis and intelligence production.

• Coordinate reference systems, datums and projections selected for analytical purpose
• Vector, raster and tabular data structures matched to security questions
• Geodatabases designed with controlled attributes, domains, identifiers and metadata
• Spatial joins, buffers and overlays answering location-based intelligence questions
• Map scale, resolution and positional accuracy interpreted before analysis
• OGC Web Map Service and Web Feature Service connections configured

Participants can apply protection, privacy and security controls to sensitive climate-security data.

• Do-no-harm assessment for sensitive locations, vulnerable groups and incident records
• Data protection controls for personal data, displacement records and field coordinates
• Threat modelling identifies adversaries, exposed assets, harms and mitigations
• Access classifications distinguish public, restricted, confidential and need-to-know datasets
• Aggregation and spatial masking reduce re-identification risks in published products
• Consent, provenance and community representation documented in data collection

Participants can select, prepare and interpret climate datasets for geographically specific risk assessment.

• CMIP6 projections interpreted through scenarios, ensembles, bias and uncertainty
• ERA5 reanalysis variables selected for temperature, precipitation, wind and soil moisture
• CHIRPS rainfall estimates compared with gauges using seasonal climatologies
• Climate normals, anomalies and percentiles calculated for local baselines
• Downscaling limits documented before using gridded climate projections locally
• NetCDF files inspected, subsetted and converted for GIS analysis

Participants can derive environmental indicators from optical and radar satellite imagery.

• Landsat and Sentinel-2 spectral bands matched to land and water indicators
• Normalized Difference Vegetation Index calculated for vegetation condition mapping
• Normalized Difference Water Index mapped for surface-water change detection
• Cloud masking, compositing and seasonal image selection reduce interpretation errors
• Synthetic aperture radar applications for flood extent and cloud-covered terrain
• Image classification accuracy assessed with reference samples and confusion matrices

Participants can create and validate spatial representations of climate-related hazards and their timing.

• Flood inundation footprints derived from radar imagery, terrain and rainfall
• Drought indicators combine SPI, vegetation anomalies and soil-moisture departures
• Heat exposure surfaces created from land surface temperature and population
• Wildfire susceptibility mapped using fuels, slope, weather and historical ignitions
• Multi-hazard calendars identify compound and cascading seasonal threats
• Event footprints validated against humanitarian situation reports and local observations

Participants can quantify people, assets and services exposed to climate-related hazards.

• Population exposure estimated with WorldPop grids and administrative boundaries
• Critical infrastructure inventories geocoded for hospitals, roads, water points and substations
• Travel-time surfaces identify settlements isolated from essential services
• Building footprints and land use quantify assets within hazard zones
• Network analysis tests road disruption effects on access and evacuation
• Exposure registers reconcile duplicate assets, geometry errors and changing boundaries

Participants can construct transparent vulnerability assessments using social, economic and service indicators.

• Vulnerability indicators selected through livelihoods, governance and social exclusion evidence
• Composite index construction documents weighting, normalization, directionality and sensitivity
• Small-area deprivation data joined to hazard and exposure layers
• Gender, age, disability and displacement disaggregation exposes unequal impacts
• Adaptive capacity mapped using services, finance, information and social networks
• Indicator limitations recorded to prevent false precision and harmful comparisons

Participants can combine evidence into a transparent, location-based climate-security risk model.

• Risk matrices combine hazard likelihood, exposure, vulnerability and consequence scores
• Weighted overlay models rank priority locations with transparent assumptions
• Scenario narratives translate climate signals into plausible security consequences
• Thresholds trigger monitoring escalation, contingency actions and decision briefings
• Uncertainty maps show confidence, missing data and model sensitivity
• First-week intelligence products peer-reviewed against stated decision requirements

Participants can analyse water-related climate pressures and associated security risks at basin and local scales.

• River-basin analysis links upstream rainfall, flow regimes, demand and institutions
• Water point functionality mapped alongside drought, population and livestock pressure
• Groundwater stress proxies combined with borehole records and land cover
• Transboundary water agreements assessed through riparian interests and seasonal scarcity
• Water conflict event data analysed for clustering, reporting bias and causality
• Allocation scenarios identify locations where shortages may intensify local tensions

Participants can map climate-related food-security pressures affecting agricultural and pastoral livelihoods.

• Crop condition monitoring combines NDVI, rainfall anomalies and planting calendars
• Market price series mapped with road access, conflict and harvest conditions
• Integrated Food Security Phase Classification evidence interpreted for spatial targeting
• Pastoral mobility corridors mapped against forage, water, borders and insecurity
• Seasonal livelihood zones connect climate shocks with household coping options
• Food-security alerts prioritize verification before operational resource allocation

Participants can assess climate-related displacement pressures while protecting sensitive population information.

• Displacement risk indicators combine hazards, tenure insecurity, conflict and services
• Origin-destination flows mapped using registration data, surveys and mobility traces
• Settlement growth detected through building footprints, night lights and imagery
• Site suitability screening applies safety, access, land and environmental criteria
• Protection risks assessed without publishing sensitive routes or household locations
• Population denominators reconciled across censuses, registrations and modelled estimates

Participants can interpret conflict-event data alongside climate pressures without making unsupported causal claims.

• ACLED-style event coding examined for actor, location, date and reporting bias
• Spatial point-pattern analysis identifies clustering beyond administrative reporting patterns
• Kernel density surfaces compare incident concentrations across consistent observation periods
• Temporal lag analysis tests associations without claiming unsupported causation
• Conflict forecasting indicators separated from explanatory variables and contextual narratives
• Red-team review challenges assumptions, alternative explanations and anticipated misuse

Participants can design an early-warning system linking indicators to accountable action protocols.

• Early warning architecture connects indicators, thresholds, analysts, authorities and responders
• Trigger protocols assign actions, decision rights, lead times and escalation rules
• Nowcasting combines satellite observations, gauges, forecasts and field reports
• Forecast-based financing principles link probability thresholds to pre-agreed actions
• Common Alerting Protocol messages adapted for location-specific threat communication
• Alert performance reviewed through timeliness, accuracy, actionability and false alarms

Participants can identify priority interventions using explicit criteria, trade-offs and protection safeguards.

• Prioritization models compare severity, population affected, feasibility and protection risks
• Location-allocation analysis positions response hubs under road and security constraints
• Multi-criteria decision analysis documents criteria weights, trade-offs and stakeholders
• Intervention theories of change connect outputs to climate-security outcomes
• Conflict-sensitive programming screens proposed actions for distributional harms
• Contingency plans specify triggers, resources, routes, responsibilities and fallback options

Participants can communicate geospatial findings through decision-ready maps, dashboards and intelligence briefs.

• Intelligence briefs distinguish observations, assessments, confidence levels and recommendations
• Situation maps use visual hierarchy, uncertainty notation, scale and source statements
• Operational dashboards display indicators, thresholds, trends and geographic priorities
• Story maps combine maps, charts, narratives and documented analytical caveats
• Map accessibility checked through colour choices, typography and print readability
• Version control preserves data lineage, revisions, approvals and publication dates

Participants can quality-assure climate-security workflows and document evidence for review and reuse.

• Data quality assessments examine completeness, timeliness, consistency, accuracy and lineage
• Metadata records follow ISO 19115 elements for datasets and services
• Reproducible workflows document inputs, parameters, scripts, outputs and decisions
• Peer review tests methods, assumptions, interpretation and decision relevance
• Model validation compares predictions with independent observations and held-out samples
• Audit trails retain source licences, transformations, approvals and dissemination records

Participants can plan the governance, roles and technical arrangements needed for sustained intelligence production.

• Analytic production cycles schedule collection, assessment, dissemination and feedback
• Roles matrix assigns data stewardship, analysis, approval and incident escalation
• Data-sharing agreements define purpose, access, retention, security and redress
• Minimum viable architecture selects desktop GIS, cloud processing and field collection
• Capacity plans identify training, maintenance, licensing, connectivity and continuity needs
• Implementation roadmaps sequence quick wins, dependencies, milestones and governance reviews

Participants can build, review and present a complete climate-security intelligence package for a defined decision problem.

• Decision question, area of interest and intelligence users formally scoped
• Documented data inventory combines climate, satellite, exposure and vulnerability sources
• Reproducible GIS workflow generates hazard, risk and priority intervention maps
• Confidence statement records uncertainties, limitations, ethics controls and validation evidence
• Executive intelligence brief presents findings, triggers, recommendations and implementation actions
• Peer review panel tests defensibility, usability and communication for decision-makers