Citation

Lim, Sin Liang and Sreevalsan‐Nair, Jaya and Daya Sagar, B. S. (2024) Multispectral data mining: A focus on remote sensing satellite images. WIREs Data Mining and Knowledge Discovery, 14 (2). ISSN 1942-4787

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Abstract

This article gives a brief overview of various aspects of data mining of multispectral image data. We focus on specifically the remote sensing satellite images acquired using multispectral imaging (MSI), given the technology used across multiple knowledge domains, such as chemistry, medical imaging, remote sensing, and so on with a sufficient amount of variation. In this article, the different data mining processes are reviewed along with state-of-the-art methods and applications. To study data mining, it is important to know how the data are acquired and preprocessed. Hence, those topics are briefly covered in the article. The article concludes with applications demonstrating the knowledge discovery from data mining, modern challenges, and promising future directions for MSI data mining research. This article is categorized under: Application Areas > Science and Technology Fundamental Concepts of Data and Knowledge > Knowledge Representation Fundamental Concepts of Data and Knowledge > Big Data Mining Graphical Abstract (Left) The multispectral image of Kerala, India, that is captured by Sentinel-2, shows the aftermath of its devastating floods in August 2018. Data mining of such an image would lead to knowledge discovery, which is critical for the estimation of damages, risk assessment, and so on. The data mining in this scenario involves processes, such as segmentation and change detection from multi-source and/or time-series images. These processes lead to the knowledge of flood extent. (Right) Our article reviews all such processes in the context of the entire data science workflow for multispectral images from satellite sensors. (Image generated by authors. (Left) Satellite images and data story courtesy: https://earthobservatory.nasa.gov/images/92669/before-and-after-the-kerala-floods)

Item Type:	Article
Uncontrolled Keywords:	Data mining
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	07 Dec 2023 01:50
Last Modified:	01 Apr 2024 05:28
URII:	http://shdl.mmu.edu.my/id/eprint/11921

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