Optical Flood Sensing With Grid Weighting for Rapid Impact Mapping
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Solution Overview
Problem
Existing flood detection and risk mitigation systems are inadequate for large-scale, rapid, and accurate assessment of flood impacts, particularly in complex urban environments, leading to misinterpretation and inability to provide reliable risk-transfer and insurance coverage due to limited sensor range and inaccurate information transmission.
Innovation Solution
An automated system using airborne and spaceborne optical sensors divides geographic areas into equidistant grid cells, assigns weightage values based on object density, and measures flood impacts to provide dynamic parametric coverage through adaptive risk-transfer structures, enabling precise flood mapping and timely payouts based on measurable parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If in-situ sensors and manual image processing techniques are used for flood detection, then detection accuracy can be improved through machine learning, but the range for inspecting disaster occurrence is limited and information transmission accuracy remains low
Solution Approach 1:
The patent divides the geographic area into multiple grid cells (e.g., 1002) to enable systematic coverage of large areas. Each grid cell can be independently processed and analyzed, allowing the system to maintain high detection accuracy across extensive regions by segmenting the monitoring task into manageable units.
Solution Approach 2:
The patent transitions from traditional 2D satellite imagery analysis to a 3D grid-based spatial representation. By creating a three-dimensional grid structure (1002) overlaid on the geographic area, the system adds a dimensional framework that enables more comprehensive coverage and precise location tracking of flood impacts across large territories.
2Productivity
If manual image processing and traditional sensor systems are used, then system complexity is reduced, but productivity and response speed are insufficient for rapid disaster assessment
Solution Approach 1:
The patent pre-divides the geographic area into grid cells (1002) and establishes the measurement framework before flood events occur. This preliminary structuring allows rapid automated analysis during actual flood events, as the system only needs to measure flood presence and extent within the pre-established grid framework rather than performing complex real-time processing.
Solution Approach 2:
The system enables automated self-assessment of flood impacts through computer-based analysis of satellite imagery. The automated measurement of flood extent within grid cells eliminates the need for manual intervention in the assessment process, significantly improving response speed while the modular grid structure keeps system complexity manageable.
3Area of stationary object
If satellite imagery-based systems process massive amounts of data, then coverage area is increased, but the ability to detect disaster occurrence in short periods of time is reduced
Solution Approach 1:
By segmenting the large coverage area into smaller grid cells (1002), the system can process and analyze each cell rapidly using automated algorithms. This segmentation allows the system to maintain wide coverage while reducing the time required for analysis, as each grid cell can be independently and quickly evaluated for flood presence.
Solution Approach 2:
The patent replaces manual image processing techniques with automated computer-based analysis systems. This substitution of mechanical manual processing with automated digital processing enables rapid detection of flood occurrences across large areas, significantly reducing detection time while maintaining comprehensive coverage.
4Measurement precision
If traditional flood detection systems are used, then information transmission can be simplified, but the accuracy of flood impact measurement and risk-transfer capability is insufficient
Solution Approach 1:
The patent implements automated measurement and verification processes that provide feedback on flood impact accuracy. By systematically measuring flood extent within each grid cell and comparing results against expected outcomes, the system ensures high accuracy in impact measurement and can correct any information transmission errors through iterative verification.
Solution Approach 2:
The system replaces manual information transmission methods with automated digital communication of flood impact data. This substitution ensures accurate and reliable transmission of measurement results, as digital data can be transmitted without the errors and ambiguities that occur in verbal or manual reporting, thereby improving both measurement precision and information transmission accuracy.
Data Source
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AI summary
The invention relates to automated airborne and/or spaceborne optical flood sensory and flood impact sensory method and system for measuring and/or forecasting a weightage-specific, quantitative flooding measure value and/or a weightage-specific, quantified flooding impact extent measure value, the weightage being based on an object density of a selected topographic and/or geographic area impacted by an occurrence of a flood event.