Next-Generation Artificial Intelligence Techniques for Satellite Data Processing

  • Neha SisodiyaEmail author
  • Nitant Dube
  • Priyank Thakkar
Part of the Remote Sensing and Digital Image Processing book series (RDIP, volume 24)


In this chapter, we have tried to cover majority of the artificial intelligence (AI) techniques that has contributed to the remote sensing community in the form of satellite data processing, right from the basics to advanced level. A wide variety of applications and enormous amount of satellite data growing exponentially has critical demands in speedup, cost cutting, and automation in its processing while maintaining the accuracy. We have started with the need of AI techniques and evolution made for revolutionary changes in remote sensing and other areas. Subsequently, the traditional ML techniques and its limitations, advancements, and need of introducing DL in various applications are reviewed with what is the present requisites and expectation from AI community to overcome the issues and meet the upraised demands by emerging applications. We concluded that ML and DL technology should integrate with big data technologies and cloud computing to meet the future needs.


Satellite images AI Machine learning Deep learning Hyperspectral Multispectral 


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Institute of Technology, Department of Computer Science EngineeringNirma UniversityAhmedabadIndia
  2. 2.Space Application Center–Indian Space Research OrganizationAhmedabadIndia

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