Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/25976
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: A novel decision support system for the interpretation of remote sensing big data (Forthcoming/Available Online)
Authors: Boulila, Wadii
Farah, Imed Riadh
Hussain, Amir
Contact Email: ahu@cs.stir.ac.uk
Keywords: Decision support system
Remote sensing data
Image interpretation
ETL process
Data warehouse
Predictive analytic
Descriptive analytics
Prescriptive analytics
Issue Date: 5-Aug-2017
Citation: Boulila W, Farah IR & Hussain A (2017) A novel decision support system for the interpretation of remote sensing big data (Forthcoming/Available Online), Earth Science Informatics.
Abstract: Applications of remote sensing (RS) data cover several fields such as: cartography, surveillance, land-use planning, archaeology, environmental studies, resources management, etc. However, the amount of RS data has grown considerably due to the increase of aerial and satellite sensors. With this continuous increase, the necessity of having automated tools for the interpretation and analysis of RS big data is clearly obvious. The manual interpretation becomes a time consuming and expensive task. In this paper, a novel tool for interpreting and analyzing RS big data is described. The proposed system allows knowledge gathering for decision support in RS fields. It helps users easily make decisions in many fields related to RS by providing descriptive, predictive and prescriptive analytics. The paper outlines the design and development of a framework based on three steps: RS data acquisition, modeling, and analysis & interpretation. The performance of the proposed system has been demonstrated through three models: clustering, decision tree and association rules. Results show that the proposed tool can provide efficient decision support (descriptive and predictive) which can be adapted to several RS users’ requests. Additionally, assessing these results show good performances of the developed tool.
DOI Link: http://dx.doi.org/10.1007/s12145-017-0313-7
Rights: This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.

Files in This Item:
File Description SizeFormat 
ESIJournalVF.pdf586.2 kBAdobe PDFUnder Embargo until 6/8/2018     Request a copy

Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.



This item is protected by original copyright



Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

If you believe that any material held in STORRE infringes copyright, please contact library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.