Special Issue Review: Artificial Intelligence and Machine Learning Applications in Remote Sensing

Ying Nong Chen, Kuo Chin Fan, Yang Lang Chang, Toshifumi Moriyama

Research output: Contribution to journalEditorial

7 Scopus citations

Abstract

Remote sensing is used in an increasingly wide range of applications. Models and methodologies based on artificial intelligence (AI) are commonly used to increase the performance of remote sensing technologies. Deep learning (DL) models are the most widely researched AI-based models because of their effectiveness and high performance. Therefore, we organized a Special Issue on remote sensing titled “Artificial Intelligence and Machine Learning Applications in Remote Sensing.” In this paper, we review nine articles included in this Special Issue, most of which report studies based on satellite data and DL, reflecting the most prevalent trends in remote sensing research, as well as how DL architecture and the functioning of DL models can be analyzed and explained is a hot topic in AI research. DL methods can outperform conventional machine learning methods in remote sensing; however, DL remains a black box and understanding the details of the mechanisms through which DL models make decisions is difficult. Therefore, researchers must continue to investigate how explainable DL methods for use in the field of remote sensing can be developed.

Original languageEnglish
Article number569
JournalRemote Sensing
Volume15
Issue number3
DOIs
StatePublished - Feb 2023

Keywords

  • artificial intelligence
  • deep learning
  • machine learning
  • remote sensing

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