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projectThis solution utilizes AI technology with diverse, high-precision multi-sensor data to swiftly and accurately detect land change information and efficiently manage the national territory.
The system detects and manages the ever-changing landscape of our nation annually, but improvements were needed in work duration, accuracy, and cost due to the reliance on manual processes. Therefore, the project is currently advancing a project by supporting an AI expert consortium to develop and apply an AI solution. This solution utilizes AI technology with diverse, high-precision multi-sensor data to swiftly and accurately detect land change information and efficiently manage the national territory.
To develop an AI solution, satellite, aerial, and drone imagery data along with high-precision location-aligned data are refined and processed to build training data. This data is then used to train an AI-based national land change detection solution that identifies the presence of changes, the nature of changes, and location alignment using a GIS (Geographic Information System) platform. This solution is developed and validated.
This AI solution provides functionality to detect the presence and nature of changes by matching locations between imagery for land change detection. It also automatically generates high- precision, realistic orthoimages, enabling efficient production and utilization of national base maps.
Development and demonstration of an AI solution for detecting national land changes based on automated modules for generating high-precision GCP-registered imagery, utilizing refined and processed aerial/satellite/drone imagery data and high-precision GCP (Ground Control Point) training data. This includes tools for organizing time-series imagery data and managing AI change detection training data based on GIS (Geographic Information System) tools.
The adoption of AI solutions is expected to enhance the accuracy of detecting land changes, thereby supporting the creation of more precise national base maps. It is also anticipated to reduce the administrative time required for regular national base map updates and lower associated costs. Furthermore, beyond land change management administration, it will contribute to various fields including urban planning, disaster response, and environmental protection.
Launch year: 2024
Case study courtesy of the National Information Society Agency, Republic of Korea, Apolitical's Content Partner. Sourced from Use Cases of Public AI Service, Vol.1, https://eng.nia.or.kr/site/nia_eng/ex/bbs/View.do?cbIdx=31975&bcIdx=28997&parentSeq=29047
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