TECHNICAL SPECIFICATION · v2.1
The Signal Score Methodology
A reproducible, multi-source scoring system for detecting technology infrastructure gaps in underserved communities globally.
Core Formula
Signal Score = 0.30 × MDG + 0.25 × EES + 0.20 × IAS + 0.15 × SVS + 0.10 × TDS
All sub-scores are normalized 0-100. Satellite flags (SAR, GRACE-FO, NDVI, LST) can independently elevate a brief's priority regardless of composite score.
Sub-Score Definitions
Each sub-score is computed independently from publicly available data sources and normalized to a 0-100 scale before weighting.
Measures the gap between a community's environmental risk level and the density of physical monitoring infrastructure (gauges, sensors, stations) actively measuring it.
MDG = Risk_Composite × (1 − Monitoring_Composite / 100)
Risk is drawn from flood/fire/drought exposure. Monitoring is computed from USGS gauge density within 50km radius.
Data Sources
| Dataset | Update |
|---|---|
| USGS National Water Info System | Real-time |
| FEMA National Flood Hazard Layer | Quarterly |
| NASA FIRMS Fire Information | Daily |
| US Drought Monitor | Weekly |
0-30: Well-monitored for its risk level
30-60: Moderate monitoring gap
60-100: High-risk area with minimal sensor infrastructure
Quantifies cumulative environmental hazard burden across six dimensions: flood risk, wildfire exposure, drought severity, storm event history, air quality, and toxic contamination.
EES = weighted_average(Flood, Fire, Drought, Storm, Air, Toxic) × 100
Flood risk (FEMA) carries highest weight at 0.30; air quality (EPA AQI) and toxics (EPA EJScreen) contribute equally at 0.15 each.
Data Sources
| Dataset | Update |
|---|---|
| EPA EJScreen | Annual |
| NOAA Storm Events Database | Monthly |
| FEMA National Flood Hazard Layer | Quarterly |
| NASA FIRMS | Daily |
0-30: Low cumulative hazard burden
30-60: Moderate environmental exposure
60-100: High cumulative hazard - frequent multi-hazard overlap
Measures gaps in the physical and digital infrastructure that communities need to receive and operate technology solutions: broadband coverage, healthcare facility access, and grid reliability.
IAS = (1 − Broadband_penetration) × 0.40 + Healthcare_gap × 0.35 + Grid_unreliability × 0.25
Broadband from FCC Form 477; healthcare gap from CMS rural health data; grid reliability from EIA outage records.
Data Sources
| Dataset | Update |
|---|---|
| FCC Broadband Data Collection | Semi-annual |
| HUD Housing Needs Assessment | Annual |
| USDA Food Access Research Atlas | Annual |
| US Census TIGER Roads | Annual |
0-30: Good infrastructure access
30-60: Partial access gaps
60-100: Severe infrastructure deficit - deployment is hard
Captures the human vulnerability dimension: income poverty, health burden, housing cost, unemployment, and linguistic isolation - factors that compound when technology gaps exist.
SVS = CDC_SVI_composite × 0.50 + ACS_poverty_rate × 0.30 + CDC_PLACES_health × 0.20
CDC SVI is the primary composite; ACS income and PLACES chronic disease burden are secondary weights.
Data Sources
| Dataset | Update |
|---|---|
| CDC Social Vulnerability Index | Biennial |
| CDC PLACES | Annual |
| US Census ACS 5-Year | Annual |
0-30: Lower vulnerability - adoption support needs are modest
30-60: Moderate vulnerability
60-100: High vulnerability - solutions need local partner organizations
A measure of how historically underinvested this community has been in technology solutions - estimated from SBIR award history, broadband investment patterns, and IoT sensor density.
TDS = (1 − SBIR_award_density) × 0.60 + Low_sensor_density × 0.40
SBIR awards geocoded from SBIR.gov; sensor density estimated from USGS + EPA monitoring station locations.
Data Sources
| Dataset | Update |
|---|---|
| SBIR.gov | Monthly |
| NSF Award Search | Monthly |
0-30: History of tech investment
30-60: Some prior investment
60-100: Chronically underinvested - greenfield opportunity
Satellite Intelligence Layer
Four independent satellite data streams run in parallel to the ground-based scoring. A positive satellite flag can independently trigger a brief regardless of composite Signal Score.
SAR Coherence (Sentinel-1)
ESA Sentinel-1 C-band SAR · Every 6-12 days
Coherence drop >0.15 between consecutive passes indicates significant ground change - structural collapse, rapid construction, or severe vegetation loss.
Alert threshold
Coherence < 0.35 in built-up areas triggers SAR Alert flag
Groundwater Anomaly (GRACE-FO)
NASA/DLR GRACE-FO satellite pair · Monthly
Terrestrial water storage anomaly from gravity measurements. Persistent depletion below −5 cm/year over 3+ years indicates aquifer stress.
Alert threshold
Anomaly < −5cm AND trend declining > 3 years triggers Groundwater Alert
Vegetation Stress (MODIS NDVI)
NASA Terra MODIS · 16-day composite
Normalized difference vegetation index tracks agricultural health and vegetation stress. Sustained anomaly below 1.5σ from baseline indicates drought stress or land degradation.
Alert threshold
NDVI anomaly < −1.5σ from 5-year baseline over 60 days
Urban Heat Island (Landsat)
USGS/NASA Landsat 8/9 TIRS · Every 16 days
Land surface temperature offset between urban core and peri-urban buffer zone. Persistent delta >4°C indicates elevated heat risk for vulnerable populations.
Alert threshold
LST urban-buffer delta > 4°C in summer months
Brief Generation Triggers
A brief is generated when one or more trigger conditions are met. Each brief includes a trigger attribution so readers know exactly what caused it.
| Trigger | Source |
|---|---|
| Score Threshold | Scoring Engine |
| SAR Alert | Google Earth Engine |
| Groundwater Anomaly | NASA PO.DAAC |
| NDVI Stress | NASA MODIS |
| Heat Island | Landsat TIRS |
| Dark Zone | Sentinel-1 + Census |
| News Event | GDELT 2.0 |
| Community Report | Community Portal |
Accuracy and Validation
Multi-source corroboration is required before a brief is published. A single anomalous data point cannot trigger publication.
Multi-source corroboration
A minimum of 2 independent data sources must agree before a brief is published. Satellite alerts require ground-data corroboration.
Data freshness scoring
Every data point carries a freshness timestamp. Briefs display per-field data currency so readers can judge reliability.
Community validation
Residents and local organizations can flag, confirm, or correct briefs. Confirmed briefs carry a distinct badge and rank higher in search.
API Reference
The Signal Score API is publicly accessible. All endpoints return JSON.
Citing Delos
All Signal Scores and briefs are freely reproducible from publicly available data. If your research relies on Delos data, please cite appropriately and consider contributing community validations.