Paper Info
Title
A Flexible Architecture For The Pre-Processing Of Solar Satellite Image Time Series Data - The Setl Architecture
Abstract
Satellite image time series (SITS) is a challenging domain for knowledge discovery database due to their characteristics: each image has several sunspots and each sunspot is associated with sensor data composed of the radiation level and the sunspot classifications. Each image has time parameters and sunspots' coordinates, spatiotemporal data. Several challenges of SITS domain are faced during the extract, transform, and load (ETL) process. In this paper, we proposed an architecture called SITS's extract, transform, and load (SETL) that extracts the visual characteristics of each sunspot and associates it with sunspot's sensor data considering the spatiotemporal relations. SETL brings flexibility and extensibility to working with challenging domains such as SITS because it integrates textual, visual and spatiotemporal characteristics at sunspot-record level. Furthermore, we obtained acceptable performance results according to a domain expert and increased the possibility of using different data mining algorithms comparing to the art state.
Year
DOI
Venue
2019
10.1504/IJDMMM.2019.098970
INTERNATIONAL JOURNAL OF DATA MINING MODELLING AND MANAGEMENT
Keywords
Field
DocType
satellite image time series, SITS, spatiotemporal ETL process, solar STIS process
SETL,Data mining,Architecture,Computer architecture,Satellite Image Time Series,Computer science
Journal
Volume
Issue
ISSN
11
2
1759-1163
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Carlos Roberto Silveira Junior131.85
Marilde Terezinha Prado Santos2136.85
M. X. Ribeiro36812.72