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Isaac Oluoch
Over the past two decades, there has been increasing research on the use of artificial intelligence (AI) and geographic information technologies for monitoring and mapping varying phenomena on the Earth?s surface. At the same time, there has been growing...
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Marina Georgati, Henning Sten Hansen and Carsten Keßler
Population growth in urban centres and the intensification of segregation phenomena associated with international mobility require improved urban planning and decision-making. More effective planning in turn requires better analysis and geospatial modell...
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Mateo Cano-Solis, John R. Ballesteros and German Sanchez-Torres
Vegetation encroachment in power line corridors remains a major challenge for modern energy-dependent societies, as it can cause power outages and lead to significant financial losses. Unmanned Aerial Vehicles (UAVs) have emerged as a promising solution ...
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Hao Sun, Shu Wang, Yunqiang Zhu, Wen Yuan and Zhiqiang Zou
In the era of GeoAI, Geospatial Intelligent Question Answering (GeoIQA) represents the ultimate pursuit for everyone. Even generative AI systems like ChatGPT-4 struggle to handle complex GeoIQA. GeoIQA is domain complex IQA, which aims at understanding a...
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Wenwen Li and Chia-Yu Hsu
GeoAI, or geospatial artificial intelligence, has become a trending topic and the frontier for spatial analytics in Geography. Although much progress has been made in exploring the integration of AI and Geography, there is yet no clear definition of GeoA...
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John R. Ballesteros, German Sanchez-Torres and John W. Branch-Bedoya
Drone imagery is becoming the main source of overhead information to support decisions in many different fields, especially with deep learning integration. Datasets to train object detection and semantic segmentation models to solve geospatial data analy...
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Marianna Farmakis-Serebryakova, Magnus Heitzler and Lorenz Hurni
Since landforms composing land surface vary in their properties and appearance, their shaded reliefs also present different visual impression of the terrain. In this work, we adapt a U-Net so that it can recognize a selection of landforms and can segment...
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Serdar Kizilkaya, Ugur Alganci and Elif Sertel
The classification of maritime boats and ship targets using optical satellite imagery is a challenging subject. This research introduces a unique and rich ship dataset named Very High-Resolution Ships (VHRShips) from Google Earth images, which includes d...
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Konstantinos Demertzis and Lazaros Iliadis
Deep learning architectures are the most effective methods for analyzing and classifying Ultra-Spectral Images (USI). However, effective training of a Deep Learning (DL) gradient classifier aiming to achieve high classification accuracy, is extremely cos...
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Yun Li, Yongyao Jiang, Justin C. Goldstein, Lewis J. Mcgibbney and Chaowei Yang
One longstanding complication with Earth data discovery involves understanding a user?s search intent from the input query. Most of the geospatial data portals use keyword-based match to search data. Little attention has focused on the spatial and tempor...
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