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Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS

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Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS
Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS by Chang-Wook Lee
English | PDF | 2021 | 167 Pages | ISBN : 3036516042 | 142.7 MB
Recently, remote sensing and GIS techniques have gained increasing importance for rapid urbanization, the expansion of urban growth, and the enlargement of populations, due to the application of artificial intelligence, machine learning, and deep learning algorithms. This Special Issue aims to present the state-of-the-art research on optics, SAR, hyperspectral images, and GIS techniques for monitoring urban area environments corresponding to changes in times using publicly available and commercial datasets such as satellite and UAV data.


Recently, remote sensing and GIS techniques have gained increasing importance for rapid urbanization, the expansion of urban growth, and the enlargement of populations, due to the application of artificial intelligence, machine learning, and deep learning algorithms. This Special Issue aims to present the state-of-the-art research on optics, SAR, hyperspectral images, and GIS techniques for monitoring urban area environments corresponding to changes in times using publicly available and commercial datasets such as satellite and UAV data.
Given the information above, the aim of this Special Issue is to present the observed urban area and monitor the surrounding urban area in "Artificial Intelligence Methods Applied to Urban Remote Sensing and GIS". This research paper of Remote Sensing will cover a wide range of fields, including GISs, remote sensing, earth science, computer science, and environmental science, to analyze the urbanization phenomenon along with theoretical research and practical developments.
Some of the prospective/encouraged topics for this Special Issue include:
- Remote sensing applications in urban disaster monitoring using AI;
- Groundwater monitoring in urban areas;
- Fusion of multispectral and SAR image applications;
- Hyperspectral image applications in urban area classification;
- Natural/artificial disaster monitoring;
- Deep/machine learning method algorithms;
- Change detection monitoring in urban areas;
- UAV/drone image processing and analysis;
- Water, river, and lake monitoring in and surrounding urban areas;
- Land subsidence, sink hole, and landslide monitoring;
- Urban river and stream ice monitoring;
- Survey research for citizens'perceptions of urban disaster.



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