GeoAI for spatial image processing
The development of digital image processing, as a subset of digital signal processing, depended upon the maturity of photography and image science, introduction of computers, discovery and advancement of digital recording devices, and the capture of digital images. In addition, government and industry applications in the Earth and medical sciences were paramount to the growth of the technology. From the early days when photography was first introduced to science to today, artificial intelligence and deep learning technologies have been intensively used to analyze imagery. Spatial image processing has experienced breakthroughs and evolutions. This chapter presents an overview of the history of image processing, GeoAI-based image processing applications, and the role of GeoAI in advancing image processing methods and research. We also discussed the remaining challenges to using GeoAI for image processing regarding training data annotation, the issues of scale, resolution, and change in space over time.
Citation Information
Publication Year | 2023 |
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Title | GeoAI for spatial image processing |
DOI | 10.1201/9781003308423-5 |
Authors | Samantha Arundel, Kevin G McKeehan, Wenwen Li, Zhining Gu |
Publication Type | Book Chapter |
Publication Subtype | Book Chapter |
Index ID | 70250934 |
Record Source | USGS Publications Warehouse |
USGS Organization | Center for Geospatial Information Science (CEGIS) |