rasterMiner: An Open-Source Python Library to Discover Knowledge From Raster Imagery Data

This paper introduces "rasterMiner," a comprehensive open-source Python software for extracting insights from satellite imagery data. This software offers 30 knowledge discovery algorithms spanning supervised and unsupervised techniques like classification, clustering, pattern mining, imag...

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Bibliographic Details
Published in2024 IEEE Space, Aerospace and Defence Conference (SPACE) pp. 1160 - 1163
Main Authors Veena, Pamalla, Kiran, Rage Uday, Yoshiko, Ogawa, Makiko, Ohtake
Format Conference Proceeding
LanguageEnglish
Published IEEE 22.07.2024
Subjects
artificial intelligence
Big data
Classification algorithms
Clustering algorithms
Knowledge discovery
Libraries
machine learning
open-source
pattern mining
raster data
Satellite images
Software
Software algorithms
space
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DOI10.1109/SPACE63117.2024.10667674

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Summary:This paper introduces "rasterMiner," a comprehensive open-source Python software for extracting insights from satellite imagery data. This software offers 30 knowledge discovery algorithms spanning supervised and unsupervised techniques like classification, clustering, pattern mining, image fusion, and imputation. Notable attributes encompass an intuitive GUI for seamless algorithm selection, the adaptability of being accessed as a Python library, and the ability to export findings to standard CSV files for visualization in GIS software. Our software is bolstered by extensive support resources, including user and developer guides and a robust bug-reporting system.
DOI:10.1109/SPACE63117.2024.10667674