An Overview of Technological Revolution in Satellite Image Analysis
Open accessAbstract
The satellite image based applications are highly utilized nowadays from simple purposes like vehicle navigation to complex surveillance and virtual environment modeling projects.On increased population rate, the depletion of natural resources is highly unavoidable and it leads to increased threats on natural hazards.In order to protect and overcome the physical losses on devastation of properties, the risk mapping models such as weather forecasts, drought modeling and other hazard assessment models are in need.Though many intelligent risk mapping models do exist, the high level of intelligence needed to predict the real time events is still unresolved.And it leads to increased research efforts on designing intelligent assessment models using more advanced machine learning (ML) schemes for better satellite image interpretation.This paper focuses on bringing a clear understanding on satellite image interpretation methods right from the traditional statistical models to the more recent ML methods through stating the gradual revolution in satellite image analysis.
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Using more advanced intelligence schemes like DNN in satellite image analysis could improve the level of reasoning with a reduction in training complexities.
“However, using more advanced intelligence schemes like DNN in satellite image analysis could improve the level of reasoning with a reduction in training complexities [159].”
From Applications and Challenges of Artificial Intelligence in Space Missions (2024) · cites this paper as [159]
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- Authors
- Department of Computer Science & Engineering, K. A. U., Jenice, A. R., Raimond, K., & Department of Computer Science & Engineering, K. A. U.
- Affiliations
- Karunya University (IN)
- ORCID
- Raimond, Kumudha
- Venue
- Journal of Engineering Science and Technology Review
- Publisher
- International Hellenic University
- Published
- 2016-08
- Volume
- 9
- Issue
- 4
- Pages
- 1-5
- ISSN
- 1791-2377 (ISSN-L)
- 1791-9320
- OpenAlex
- W2964026632
- Cited by
- 11
- References
- 49
- Citations by year
- 2025: 1 · 2024: 3 · 2023: 2 · 2022: 1 · 2021: 2 · 2019: 1 · 2017: 1
- FWCI
- 0.72
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- public-domain
- Locations
- Journal of Engineering Science and Technology Review (publishedVersion, public-domain)
- Topics
- Physical Sciences › Engineering › Media Technology › Remote-Sensing Image Classification
- Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Remote Sensing and Land Use
- Physical Sciences › Engineering › Ocean Engineering › Satellite Image Processing and Photogrammetry
- Keywords
- satellite image analysis, satellite image interpretation, machine learning, natural hazard assessment, drought modeling, weather forecasting, statistical image analysis
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