Satellite Imagery Analysis for Site Selection
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Solution Overview
Problem
Traditional site selection methods are time-consuming, expensive, and inefficient, lacking the ability to provide real-time monitoring and comprehensive analysis of spatial data for informed decision-making across various industries.
Innovation Solution
A comprehensive method and system utilizing geospatial analysis, satellite imagery, and a digital earth representation to identify and monitor candidate locations, incorporating machine learning algorithms and digital twin technology for continuous data updates and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional site selection methods are used, then the process is simple and low-cost, but it is time-consuming and inefficient
Solution Approach 1:
The patent replaces traditional mechanical field survey methods with automated satellite imagery processing and machine learning algorithms. The system automatically analyzes satellite images to identify candidate locations, extract spatial features, and evaluate site suitability, eliminating the need for manual field surveys and significantly reducing the time required for site selection while improving efficiency
Solution Approach 2:
The patent creates a digital copy of the physical environment through satellite imagery and generates a digital twin model of candidate locations. This digital representation allows for virtual analysis and evaluation of sites without requiring physical presence, enabling rapid assessment of multiple locations simultaneously and reducing the time needed for site selection
2Measurement precision
If comprehensive geospatial analysis is performed, then the accuracy of site selection is improved, but the system complexity increases
Solution Approach 1:
The patent divides the complex site selection process into distinct sequential stages: data acquisition, pre-processing, candidate identification, feature extraction, and suitability evaluation. Each stage is handled by specialized algorithms and processing modules, making the overall complex system manageable and maintainable while achieving high measurement precision through systematic analysis
Solution Approach 2:
The patent introduces a digital twin model as an intermediary between raw satellite data and final site selection decisions. This digital representation serves as a mediator that integrates and processes complex geospatial data, transforming raw information into actionable insights while simplifying the analysis process and reducing the complexity burden on the user
3Speed
If real-time monitoring is implemented, then the responsiveness to changes is improved, but the data processing requirements and costs increase
Solution Approach 1:
The patent implements periodic satellite imagery acquisition and analysis cycles rather than continuous monitoring. The system performs automated analysis at scheduled intervals to detect changes in candidate locations, balancing the need for timely information with energy conservation. This periodic approach enables responsive monitoring while reducing the computational energy consumption associated with continuous data processing
Data Source
AI summary
This disclosure presents a novel method and system for remotely identifying physical locations that meet specific criteria. The method involves obtaining source input data and satellite imagery, which are pre-processed and normalized to form a digital representation of the Earth. Three-dimensional and mosaic data are then produced, corresponding to the digital earth, and geospatial analysis is performed based on the defined criteria. The analysis includes object recognition and the application of machine learning algorithms to identify features of interest. The method further involves identifying candidate locations that meet the criteria and optionally monitoring them through satellite tasking. A computer system and non-transitory storage medium are also described, incorporating artificial intelligence algorithms and spatial statistics visualization to facilitate the identification and monitoring processes. This innovative approach offers a comprehensive and efficient means of remotely identifying and assessing potential locations for various applications such as site selection, monitoring, and decision-making.