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Review of Machine Learning in Geosciences and Remote Sensing

  • Noel DavidEmail author
  • Rejo Mathew
Conference paper
  • 45 Downloads
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 49)

Abstract

It is known that the machine learning algorithms are able to process data without the need of human intervention. A lot of the research and analysis involved in Geosciences and Remote Sensing is labor intensive and demanded high amount of resources. The problems in Geosciences are usually different to what is encountered in other applications, requiring unique techniques and formulations. A more time and cost effective method is needed to help classify, identify, and collect the required data. Machine learning is used to solve various problems in geosciences and remote sensing effectively. Machine learning is a collection of various algorithms such as support vector machines, gradient boosting machines, trees, etc. which provide us with different options of mapping our results, including classification, identification and prediction. The main objective is to use Machine learning as a tool to learn from the given data and effectively solve problems in remote sensing and geosciences.

Keywords

Geosciences Genetic Programming Machine learning Remote sensing RSI images Regression Support Vector Machine 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Mukesh Patel School of Technology Management and EngineeringNMIMS University (Deemed-to-be)MumbaiIndia

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