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Remote sensing data plays a crucial role in environmental monitoring, disaster assessment, and urban planning. However, efficiently acquiring, analyzing, and visualizing such data from multiple sources remains a challenge. This paper introduces GeoHUB, an AI-powered platform designed to streamline remote sensing data analysis by integrating conventional and artificial intelligence-based processing techniques. GeoHUB supports data acquisition from diverse satellite sources, including SPOT, Sentinel, Landsat, Pleiades, KOMPSAT, COSMO-SkyMed, and UAV imagery, ensuring comprehensive data accessibility. The platform provides advanced analytical tools for image classification, change detection, and feature extraction, leveraging deep learning and machine learning models to enhance interpretation accuracy. Furthermore, GeoHUB seamlessly integrates with Geographic Information Systems (GIS) to facilitate spatial analysis, querying, and result visualization. A case study is presented to demonstrate GeoHUB’s capabilities in assessing the damage caused by Typhoon Yagi (2024) in Hai Phong, Vietnam, highlighting its effectiveness in rapid disaster impact evaluation. The results underscore the potential of GeoHUB as a powerful decision-support system based on remote sensing applications across various domains.

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A Novel AI-Based Framework for Remote Sensing Data Analysis

  • 会议论文

  • 发表日期：

    2026年

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  • Nguyen Ngoc Quang,
  • Do Anh Huy,
  • Nguyen Hoang Long,
  • Nguyen Quang Minh

摘要

Remote sensing data plays a crucial role in environmental monitoring, disaster assessment, and urban planning. However, efficiently acquiring, analyzing, and visualizing such data from multiple sources remains a challenge. This paper introduces GeoHUB, an AI-powered platform designed to streamline remote sensing data analysis by integrating conventional and artificial intelligence-based processing techniques. GeoHUB supports data acquisition from diverse satellite sources, including SPOT, Sentinel, Landsat, Pleiades, KOMPSAT, COSMO-SkyMed, and UAV imagery, ensuring comprehensive data accessibility. The platform provides advanced analytical tools for image classification, change detection, and feature extraction, leveraging deep learning and machine learning models to enhance interpretation accuracy. Furthermore, GeoHUB seamlessly integrates with Geographic Information Systems (GIS) to facilitate spatial analysis, querying, and result visualization. A case study is presented to demonstrate GeoHUB’s capabilities in assessing the damage caused by Typhoon Yagi (2024) in Hai Phong, Vietnam, highlighting its effectiveness in rapid disaster impact evaluation. The results underscore the potential of GeoHUB as a powerful decision-support system based on remote sensing applications across various domains.