Steps toward a classifier for the Virtual Observatory. I. Classifying the SDSS photometric archive

2007/06/29 by R. D’Abrusco, R. D'Abrusco, A. Staiano +9 · 1 citation
Environmental Science · Physics and Astronomy · #Astrophysics (astro-ph) #FOS: Physical sciences #Remote Sensing in Agriculture #astro-ph

paper · pdf · doi:10.48550/arxiv.0706.4424

To appear in the Proceedings of the "1st Workshop of Astronomy and Astrophysics for Students" - Naples, 19-20 April 2006

arxiv created 2007/06/29 · openalex publication_date 2007/06/29 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Modern photometric multiband digital surveys produce large amounts of data that, in order to be effectively exploited, need automatic tools capable to extract from photometric data an objective classification. We present here a new method for classifying objects in large multi-parametric photometric data bases, consisting of a combination of a clustering algorithm and a cluster agglomeration tool. The generalization capabilities and the potentialities of this approach are tested against the complexity of the Sloan Digital Sky Survey archive, for which an example of application is reported.

Cited by

• FAST REDSHIFT CLUSTERING WITH THE BAIRE (ULTRA) METRIC

Related

• Image-Based Multi-Survey Classification of Light Curves with a Pre-Trained Vision Transformer
• Astronomical databases, Space photometry and time series analysis: Open questions
• Cross-matching Engine for Incremental Photometric Sky Survey
• Challenges for Cluster Analysis in a Virtual Observatory
• Automated stellar classification for large surveys: a review of methods\n and results