- By:
- Anantharaj, Valentine G; Tsaris, Aristeidis ; Zimmer, Christopher J; Potnis, Abhishek V; Lunga, Wadzanai D
- Page Number:
- 429-447
- Book Title:
- GeoAI for Earth Observation Imagery: Fundamentals and Practical Applications
- Publication Date:
- June 2, 2026
- Publisher Location:
- Elsevier, London, United Kingdom
- View DOI Listing:
- https://doi.org/10.1016/B978-0-44-343796-0.00027-9
Abstract
This chapter explores the role of high-performance computing (HPC) in advancing geospatial artificial intelligence (GeoAI) through the processing and analysis of a vast array of geospatial datasets, particularly remote sensing imagery. HPC plays a vital role in the synthesis of geospatial intelligence and reasoning enabled by deep learning. Modern HPC ecosystems are defined by advanced hardware architectures, parallel computing algorithms and high throughput input and output (I/O) capabilities. This chapter provides an overview of the essential elements of HPC, including parallelization strategies that facilitate the development of GeoAI applications, illustrated by a practical application involving rapid building damage assessment at scale using HPC resources. We also outline emerging technologies that promise near real-time GeoAI applications for decision support.
