• Surekha Borra
  • Rohit Thanki
  • Nilanjan Dey
Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)


With the recent developments in sensors, communication and satellite technology, data storage, processing, and networking capabilities, satellite image acquisition and mining are on the rise. Satellite images play a vital role in providing geographical information. Satellite image classification identifies the land cover/land use and labels each class entity by applying decision rules on numerical values of pixels, which represents the average spectral reflectance. The design of highly accurate decision support systems, assists and eases the data analysts. Integrating the Machine Learning (ML) technology with the human visual psychometric helps meet the demands of the geologists to improve the efficiency and quality of classification in real time, reduces human errors, and allows fast and rigorous analysis of land use and land cover information. This chapter presents an overview of satellite imaging system, imaging sensors, resolutions, distortions, image interpreters, automatic classifiers, and their performance assessment methods.


Active Infrared Passive Microwave Sensor Satellite 


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Copyright information

© The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Surekha Borra
    • 1
  • Rohit Thanki
    • 2
  • Nilanjan Dey
    • 3
  1. 1.Department of Electronics and Communication EngineeringK.S. Institute of TechnologyBengaluruIndia
  2. 2.Faculty of Technology and Engineering, Department of ECEC. U. Shah UniversityWadhwan cityIndia
  3. 3.Department of Information TechnologyTechno India College of TechnologyKolkataIndia

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