Remote Sensing Data Fusion for Natural Event Quantification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for assessing natural disasters, such as flooding, are limited by inaccurate maps and insufficient data, especially when in-situ sensors are unavailable or inaccessible, making it difficult to quantify the extent and recurrence of events.
Innovation Solution
A method that combines remote sensing data with computer simulation results to generate weighted probability data sets, allowing for the computation of the extent and recurrence of natural events in a geographical area, even without ground-based sensors, by using computing means to combine remote sensing data with simulation data to create a map indicating the extent and recurrence of events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If in-situ ground-based sensors are deployed to obtain accurate measurements of natural events, then measurement precision is improved, but device complexity and loss of time increase due to deployment requirements
Solution Approach 1:
The patent uses remote sensing data (satellite images, aerial photos) as copies or representations of the actual physical state of the geographical area. Instead of deploying physical sensors to directly measure flooding events, the system captures and processes remote sensing images that copy the spatial information of affected areas, thereby achieving measurement without physical sensor deployment
Solution Approach 2:
The patent replaces the mechanical system of ground-based sensor deployment with a remote sensing and computer vision system. By using image processing algorithms to analyze remote sensing data, the system substitutes physical measurement devices with computational methods that process optical/electromagnetic data from satellites or aerial platforms
2Measurement precision
If in-situ sensors are used to obtain accurate event measurements, then measurement precision is improved, but loss of time increases due to sensor deployment and data collection requirements
Solution Approach 1:
The system performs preliminary actions by continuously monitoring geographical areas with remote sensing and maintaining updated probability data sets before natural events occur. When a flooding event happens, the system can quickly compare pre-existing data with new observations to rapidly assess the event extent without needing to deploy sensors or collect data from scratch
Solution Approach 2:
By using remote sensing images as copies of the physical state, the system enables rapid data collection without the time-consuming process of sensor deployment. Multiple remote sensing platforms can simultaneously capture images of large areas, providing timely data for immediate analysis and decision-making
3Ease of operation
If remote sensing data is used to assess natural events, then ease of operation is improved, but measurement precision deteriorates due to lack of ground-based sensor data
Solution Approach 1:
The patent merges multiple data sources including remote sensing data, topographical data, infrastructure data, and probability data sets into an integrated analysis system. By combining these diverse data types and using image processing to correlate them with simulation results, the system compensates for the limitations of individual data sources and achieves more accurate measurements
Solution Approach 2:
The system introduces probability data sets and image processing algorithms as intermediaries between remote sensing observations and final event quantification. These intermediaries process and interpret the remote sensing data, comparing observed events with simulated scenarios to derive accurate measurements of event extent and recurrence probability
4Ease of manufacture
If traditional mapping methods are used to illustrate danger levels, then ease of manufacture is improved, but measurement precision deteriorates due to limited accuracy in return period and frequency computations
Solution Approach 1:
The patent merges traditional mapping approaches with computer simulation technology and probability analysis. By integrating observed event data from remote sensing with simulated flooding scenarios and recurrence frequency models, the system produces maps that contain both qualitative danger level illustrations and quantitative return period computations
Solution Approach 2:
The mapping system uses composite data structures that combine multiple types of information: observed event probabilities, simulated recurrence frequencies, topographical features, and infrastructure data. This composite approach creates enriched hazard maps that provide both visual danger level representation and precise numerical return period calculations
Data Source
AI summary
A method for quantifying the extent and recurrence of a predetermined natural event, such as a flooding event, in a geographical area, in particular in spite of the absence of reliable data from sensors on the ground where the natural event develops. The method relies on remote sensing data, such as satellite imagery, and data processing, and reaps the benefits of computational models based on accurate remote sensing of the area under consideration.