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Book cover Satellite Image Analysis: Clustering and Classification

Part of the book series: SpringerBriefs in Applied Sciences and Technology ((BRIEFSINTELL))

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Abstract

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.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, K.S. Institute of Technology, Bengaluru, Karnataka, India

    Surekha Borra

  2. Faculty of Technology and Engineering, Department of ECE, C. U. Shah University, Wadhwan city, Gujarat, India

    Rohit Thanki

  3. Department of Information Technology, Techno India College of Technology, Kolkata, West Bengal, India

    Nilanjan Dey

Authors
  1. Surekha Borra
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  2. Rohit Thanki
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  3. Nilanjan Dey
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Borra, S., Thanki, R., Dey, N. (2019). Introduction. In: Satellite Image Analysis: Clustering and Classification. SpringerBriefs in Applied Sciences and Technology(). Springer, Singapore. https://doi.org/10.1007/978-981-13-6424-2_1

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  • DOI: https://doi.org/10.1007/978-981-13-6424-2_1

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6423-5

  • Online ISBN: 978-981-13-6424-2

  • eBook Packages: EngineeringEngineering (R0)

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