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Leveraging Potential of Deep Learning for Remote Sensing Data: A Review

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Intelligent Systems and Human Machine Collaboration

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 985))

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Abstract

Remote sensing has witnessed impressive progress of computer vision and state of art deep learning methods on satellite imagery analysis. Image classification, semantic segmentation and object detection are the major computer vision tasks for remote sensing satellite image analysis. Most of work in literature is concentrated on utilization of optical satellite data for the aforementioned tasks. There remains a lot of potential in usage of Synthetic Aperture Radar (SAR) data and its fusion with optical data which is still at its nascent stage. This paper reviews, state of the art deep learning methods, recent research progress in Deep learning applied to remote sensing satellite image analysis, related comparative analysis, benchmark datasets and evaluation criteria. This paper provides in depth review of satellite image analysis with the cutting edge technologies and promising research directions to the budding researchers in the field of remote sensing and deep learning.

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Authors and Affiliations

  1. Datta Meghe College of Engineering, Airoli, Navi Mumbai, India

    Kavita Devanand Bathe & Nita Sanjay Patil

  2. K J Somaiya Institute of Technology, Mumbai, India

    Kavita Devanand Bathe

Authors
  1. Kavita Devanand Bathe
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  2. Nita Sanjay Patil
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Correspondence to Kavita Devanand Bathe .

Editor information

Editors and Affiliations

  1. Algebra University College, Zagreb, Croatia

    Siddhartha Bhattacharyya

  2. Kyushu Institute of Technology, Kitakyushu, Fukuoka, Japan

    Mario Koeppen

  3. Maulana Abul Kalam Azad University of Technology, Kolkata, West Bengal, India

    Debashis De

  4. University of Milan, Milan, Italy

    Vincenzo Piuri

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Devanand Bathe, K., Patil, N.S. (2023). Leveraging Potential of Deep Learning for Remote Sensing Data: A Review. In: Bhattacharyya, S., Koeppen, M., De, D., Piuri, V. (eds) Intelligent Systems and Human Machine Collaboration. Lecture Notes in Electrical Engineering, vol 985. Springer, Singapore. https://doi.org/10.1007/978-981-19-8477-8_11

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  • DOI: https://doi.org/10.1007/978-981-19-8477-8_11

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