A general guide to interactive figures from a research workflow using nighttime satellite observations to study disaster disruption and electricity recovery.
Satellites can observe Earth at night. When electricity supply is disrupted after a major storm, lights may dim. As power is restored, lights may return. This makes nighttime lights a useful source of evidence for disaster impact and recovery monitoring.
However, satellite observations are not always clear. In tropical regions, clouds, storms, and atmospheric conditions often reduce how much of the ground the satellite can observe. This project therefore asks:
When can nighttime lights be trusted as evidence of disaster impact and recovery?
The main signal used here is DNB-BRDF nighttime radiance from NASA Black Marble. Lower radiance generally means less observed light. A sharp drop after a disaster can indicate power interruption, damage, evacuation, or reduced activity.
Some products include a Gap-Filled layer. This can make the time series look continuous, but it may carry forward information from previous clear observations. A smooth line is therefore not always a reliable line.
Spatial completeness is the percentage of valid observed pixels on a given day. High spatial completeness means the satellite had good usable coverage. Low spatial completeness means much of the region was obscured or unusable.
The analysis separates places by settlement type, from urban cores to rural and non-settlement areas. Urban areas usually provide stronger and more stable nighttime light signals, while rural or low-light areas can be harder to interpret.
This figure shows how the nighttime light signal changes when low-observability days are filtered out. It helps explain why reliability screening is necessary before interpreting daily satellite observations.
Look for: whether the signal changes when stricter spatial completeness thresholds are applied.
Open figureThis dashboard compares selected urban, municipal, and non-settlement locations around the Haiyan period.
Look for: which locations show clearer disruption and recovery signals, and which are noisier.
Open dashboardThis figure compares nighttime light dynamics across regions within the same settlement category.
Look for: whether urban cores behave more consistently than rural or mixed classes.
Open figureThis figure shows electricity load dynamics across Visayas subgrids using the 30-day moving average of 1 AM load.
Look for: major drops, recovery patterns, and differences between subgrids.
Open figureThis figure compares normalized nighttime lights with electricity load. Strong co-movement suggests that nighttime lights are capturing real electricity-system dynamics.
Look for: whether the colored nighttime light curves move with the black electricity-load curve.
Open figureThis summary compares which settlement masks and spatial completeness thresholds work best across different Visayas subgrids.
Look for: whether urban-focused masks are consistently selected across regions.
Open figureFor disaster agencies, infrastructure planners, energy analysts, and resilience researchers, the figures show both the promise and the caution of nighttime lights.
The promise is that satellite observations can provide an independent and spatially consistent view of disaster disruption and recovery. The caution is that satellite observations must first be screened for reliability, especially in cloudy tropical regions.
These figures should be used as a screening and interpretation layer, not as a standalone source of truth. The strongest use case is to combine nighttime lights with outage reports, electricity-load data, damage assessments, settlement maps, and local knowledge.
This page is part of the reproducible research repository for reliability-qualified nighttime lights analysis.