GeoAI

Unveiling the Power of Geospatial Artificial Intelligence (GeoAI) and its Applications

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By Shahabuddin Amerudin Introduction The term Geospatial Artificial Intelligence (GeoAI) lacks a universally agreed-upon definition. Initially, GeoAI referred to the utilisation of machine learning tools within Geographic Information Systems (GISs) to predict future scenarios by classifying data. This included disaster occurrence, human health epidemiology, and ecosystem evolution, aimed at bolstering community resilience through traditional geographic information in digital cartography (Esri, 2018). A broader interpretation considers GeoAI as processing Geospatial Big Data (GBD) encompassing various sources, […]

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Simplifying Automated Building Footprint Extraction with Deep Learning in GIS

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By Shahabuddin Amerudin Abstract This paper delves into the realm of geospatial data processing, highlighting the amalgamation of Python scripting and advanced deep learning techniques for object detection. The resulting synergy offers an avenue to streamline complex tasks within this domain. The focus of this work is on the automation of building footprint extraction from aerial imagery using these integrated methodologies. Automated Building Footprint Extraction via Deep Learning Techniques Consider a scenario where the conventional

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GeoAI: Merging Geospatial Data and AI for Enhanced Decision-Making

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By Shahabuddin Amerudin Geospatial Artificial Intelligence (GeoAI) is a specialized field that combines geospatial data, which includes geographic information such as location, coordinates, and spatial relationships, with artificial intelligence (AI) techniques to extract valuable insights, patterns, and predictions from spatially referenced data. In essence, GeoAI involves the application of AI algorithms and methodologies to geospatial data to solve complex problems and enhance decision-making in various domains. Key Components of GeoAI Applications of GeoAI Tools and

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GeoAI: Unveiling Patterns and Shaping Futures at the Nexus of Geography and Artificial Intelligence

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By Shahabuddin Amerudin Introduction In the contemporary era of technological advancements, the amalgamation of artificial intelligence (AI) with geography has ushered in a revolutionary field known as GeoAI. This interdisciplinary domain leverages the prowess of AI to decode intricate patterns concealed within geospatial data, enabling us to predict, analyze, and respond to a spectrum of events and phenomena. From predicting ecological shifts to deciphering human mobility trends, GeoAI stands as a beacon of innovation that

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