EO Data
Table 1: Representative Optical EO Missions
Optical Constellation
Multi-spectral,
~3–5 m (moderate)
Near-daily coverage
Optical Missions (e.g. Sentinel-2)
Multi-spectral, 13 bands
10–20 m (RGB + NIR)
~5 days global coverage
Legacy Archives (Landsat series)
Multi-spectral, historical
15–30 m (panchromatic or multi-spectral)
16 days historically
Key Points:
NEO offers near-daily moderate-resolution coverage.
ESA missions like Sentinel-2 complement coverage with free, multi-spectral data.
Legacy data provide historical baselines for trend and climate adaptation analyses.
Table 2: Representative Radar EO Missions
Sentinel-1 (ESA)
C-band Synthetic Aperture Radar (SAR)
~10 m
~6–12 days (global)
Commercial Radar (e.g. X-band)
X-band SAR, all-weather
1–3 m (tasked)
On-demand or daily
Other Missions (L-, S-band)
L-band / S-band SAR
5–30 m
Variable, region-specific
Key Points:
Radar can penetrate clouds/night, crucial for flood detection or tropical zones.
Higher resolution commercial radar can be tasked on demand to detect fine infrastructure changes.
Complementing optical data with radar reduces data gaps from cloud or nighttime issues.
Table 3: Data Access & Integration Mechanisms
NEO Daily Imagery
Cloud-based tile API
Near-real-time (daily)
HPC aggregator ingestion, automated ETL
ESA Open Missions
Sentinel Hub, EO browser
5–12 days or on demand
HPC aggregator scripts (bulk/automated download)
Government / BFS aggregator
CSV, JSON, secure endpoints
Continuous or batch
HPC aggregator pipelines, role-based access
Key Points:
Automated ETL scripts unify NEO data with BFS aggregator logs.
HPC aggregator ensures minimal latency, robust parallel processing.
Varying revisit rates demand flexible ingestion schedules.
Table 4: Temporal & Spatial Resolution Considerations
NEO Optical Daily
Daily / sub-daily
~3–5 m (moderate)
Detect farmland expansions, deforestation pockets, building footprints
ESA Radar
~5–12 days globally (some on demand)
10–20 m typical
Flood extents, cloud-penetration for tropical zones
Legacy Archives
Historical (5–20 yrs)
15–30 m multi-spectral
Baselines, multi-year trend analyses, climate adaptation progress
Key Points:
Daily optical data yields high-frequency insights but moderate resolution.
Radar complements coverage for cloud-heavy or night situations.
Historical archives anchor longitudinal studies for climate or land use changes.
Table 5: Potential Layers for ESG & Climate Analytics
Land Cover/Use
Forest, farmland, urban footprints
NEO daily optical + HPC classification
ESG deforestation alerts, farmland expansions for SME analysis
Hazard / Disaster
Flood or drought extents, storms
Radar (flood detection), aggregator HPC merges weather data
Parametric insurance triggers, risk-based financial products
Infrastructure
Road expansions, industrial zones
Optical imagery daily, HPC aggregator logs for subnational expansions
Competitiveness & trade corridor improvements, climate-proofing
Key Points:
ESG-lens data includes land use, hazard overlays, and infrastructure footprints.
HPC aggregator merges BFS or local administrative data for social or governance aspects.
Table 6: Sustainability Metrics & Performance Indicators
Deforestation Rate (ha/day)
HPC aggregator classification of forest cover changes
Daily to weekly
Green bond verification, ESG compliance
Flood Impact on Agricultural Areas
Radar-based flood detection + aggregator BFS logs on farmland credit
Daily or event-based
Parametric insurance, climate adaptation financing
GHG Emissions Approx (ton/CO2 eq)
HPC aggregator merges land cover changes with known carbon data
Monthly or scenario-based
Low-carbon transitions, net-zero expansions
Key Points:
HPC aggregator logic can recast raw EO data into meaningful sustainability metrics.
FCI staff use these metrics to track compliance, pivot strategies.
Table 7: Parametric Triggers in Spatial Finance
Flood Threshold
Radar-based water extent, rainfall logs
If water coverage > set threshold in region, trigger payout
Microfinance parametric coverage, risk-based loan adjustments
Drought Severity
NDVI or soil moisture from multi-spectral images
HPC aggregator checks NDVI anomalies, dryness indices
Agriculture lending, climate-lens SME financing
Sea Level Storm Surge
Sea-level anomaly, satellite altimetry, local tide gauges
HPC aggregator param. triggers for coastal assets
Coastal resilience bonds, SME insurance
Key Points:
Parametric finance flows rely on real-time HPC aggregator checks.
Daily or sub-daily updates from NEO ensure minimal lag in trigger activation.
Table 8: HPC Aggregator Modules
Land Cover Classifier
Segment farmland, forest, or urban footprints
Deep learning (CNN)
NEO daily optical, aggregator BFS logs for cross-check
Flood Detection
Identify flood extents from radar data
SAR-based thresholding
ESA Sentinel-1, aggregator HPC scripts for param. triggers
ESG Performance Index
Merge E&S signals from multiple layers
Weighted scoring, anomaly detection
E.g., reforestation coverage, BFS aggregator data for community benefits
Key Points:
HPC aggregator modules each handle specialized tasks, integrated seamlessly.
AI/ML includes deep learning for classification, threshold triggers for parametric coverage, risk weighting for ESG.
Table 9: AI/ML Capabilities for Real-Time Scenario Planning
Commodity Price Collapse
HPC aggregator merges daily trade data, local industry expansions, multi-year EO of farmland
Visualizing region-level vulnerability, potential default risk
Swift policy pivot, reallocation of trade facilitation programs
Climate Warming Path (1.5°C)
HPC aggregator merges historical EO time-series, IPCC climate models
Identifies future hazard zones, farmland shifts, water stress
Long-term resilient investment design, parametric coverage expansions
Digital Finance Disruption
BFS aggregator logs on e-wallet usage, HPC aggregator sees agent expansions
SME usage patterns, e-lending hotspots, potential unscrupulous lending signals
Strengthening consumer protection, digital finance strategies
Key Points:
HPC aggregator runs scenario queries in near real time, generating data-driven insights.
FCI staff can refine policies or lending accordingly.
Table 10: Focus Areas for Pilots
Parametric Flood Microfinance
Monsoon region with repeated flooding
Daily radar + optical
Real-time flood extents, automatic parametric triggers, local SME risk updates
Green Corridor Bond
Deforestation-prone area
Weekly multi-spectral
NEO-based forest monitoring, BFS aggregator logs for community benefits or job creation
Trade Corridor Modernization
Cross-border corridor or major port
Daily or sub-daily optical + aggregator BFS trade flows
Real-time detection of congestion or shipping disruptions, enabling fast policy or financing responses
Key Points:
Each pilot covers a distinct dimension of FCI (financial stability, ESG compliance, trade facilitation).
HPC aggregator synergy ensures advanced scenario planning and daily anomaly detection.
Last updated
Was this helpful?