How Computers Automatically Spot Disaster Damage Using Different Types of Images
A method for comparing two different types of images—like satellite photos and drone footage—to automatically identify areas damaged by natural disasters.
Original patent title: “Method and apparatus for detecting changes between heterogeneous image data for identifying disaster damage”
A method for comparing two different types of images—like satellite photos and drone footage—to automatically identify areas damaged by natural disasters. Granted to Kakao Mobility Corp in 2025 with 9 claims.
Key facts
Coverage
What does this patent actually cover?
This technology compares 'before' and 'after' images of a disaster zone, even when those images come from different sources like optical cameras and multispectral sensors. It first identifies specific objects in both images—such as buildings or vegetation—based on their color or light reflectance. It then filters out 'exceptional objects' that aren't relevant to the disaster, like moving cars or shadows, to ensure they don't trigger false alarms. Finally, it uses mathematical techniques like Change Vector Analysis and PCA K-means to highlight exactly where the landscape has changed, pinpointing the damage.
The gap
What does this patent NOT cover?
- Does not cover analysis of homogeneous image data (e.g., comparing two identical camera feeds).
- Does not cover manual human-in-the-loop damage assessment without the automated filtering of exceptional objects.
- Does not cover real-time streaming video analysis for non-disaster events.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
What made this novel
The system doesn't just overlay images; it intelligently filters out 'exceptional objects' based on the disaster type before comparing them, preventing common false positives caused by temporary items like parked cars or changing light conditions.
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
Automated flood damage assessment using satellite imagery compared to drone photos.
Post-earthquake structural damage detection in urban environments.
Wildfire progression monitoring using multispectral sensor data.
Why it matters
The bigger picture
In disaster relief, time is critical. Manual inspection of satellite or drone footage is slow and prone to error. By automating the comparison of heterogeneous data—meaning data from different sensors or platforms—this system helps emergency responders identify hard-hit areas faster, allowing for more efficient deployment of resources.
Filed
November 17, 2022
Granted
November 18, 2025
Market context
Who's building on this
Companies in this space
Kakao Mobility Corp, the assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →, is actively integrating advanced mapping and spatial analysis into their logistics and transport platforms. This technology is also relevant to major geospatial analytics firms and government agencies focused on disaster response and climate resilience.
Market impact
This patent provides a technical framework for standardizing disaster assessment across diverse sensor platforms. It enables companies to build reliable, automated damage-detection services that can process data from varied sources, potentially reducing the reliance on manual image interpretation in the insurance and emergency management sectors.
Claim 1 — Plain English
What this patent covers
This technology compares 'before' and 'after' images of a disaster zone, even when those images come from different sources like optical cameras and multispectral sensors. It first identifies specific objects in both images—such as buildings or vegetation—based on their color or light reflectance. It then filters out 'exceptional objects' that aren't relevant to the disaster, like moving cars or shadows, to ensure they don't trigger false alarms. Finally, it uses mathematical techniques like Change Vector Analysis and PCA K-means to highlight exactly where the landscape has changed, pinpointing the damage.
The clever bit
The system doesn't just overlay images; it intelligently filters out 'exceptional objects' based on the disaster type before comparing them, preventing common false positives caused by temporary items like parked cars or changing light conditions.
What it does not cover
- Does not cover analysis of homogeneous image data (e.g., comparing two identical camera feeds).
- Does not cover manual human-in-the-loop damage assessment without the automated filtering of exceptional objects.
- Does not cover real-time streaming video analysis for non-disaster events.
Patent timeline
Application submitted to the patent office
Application published, typically 18 months after filing
Patent officially issued
PatentBrief Score
Impact Score
Early stage
Citation count
0/40
No citations yet
Claim breadth
6/20
Moderate scope
Recency
20/20
Granted within 5 years
Assignee scale
0/20
Independent or smaller assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$24K – $77K
Midpoint $48K · 16.4 yr remaining · industry ×1.6
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
The original legal language
Original claims
9 claims as filed with the patent office.
Concepts involved
Citations
Patent lineage
Cite this patent
HONG, S. H., CHOI, Y. J., & Farkoushi, M. G. (2025). How Computers Automatically Spot Disaster Damage Using Different Types of Images (U.S. Patent No. 12,475,678). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/12475678/spacex-engine-philosophy
Auto-generated from the patent record. Double-check author order and the issue date against the official USPTO document before submitting.
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Common Questions
Frequently Asked Questions
What does How Computers Automatically Spot Disaster Damage Using Different Types of Images cover?
A method for comparing two different types of images—like satellite photos and drone footage—to automatically identify areas damaged by natural disasters.
Who owns patent US 12475678?
Kakao Mobility Corp owns this patent, granted in 2025.
When does this patent expire?
This patent is expected to expire on November 18, 2045, when the invention enters the public domain.
What problem does this patent solve?
In disaster relief, time is critical. Manual inspection of satellite or drone footage is slow and prone to error. By automating the comparison of heterogeneous data—meaning data from different sensors or platforms—this system helps emergency responders identify hard-hit areas faster, allowing for more efficient deployment of resources.
What does this patent NOT cover?
Does not cover analysis of homogeneous image data (e.g., comparing two identical camera feeds).
Patent monitoring