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Using data mining for predicting cultivable uncultivated regions in the Middle East
Joint Authors
Abd Allah, Ahsan
Basuhail, Abd Allah
Aslam, Ahtisham
Bakhashwain, Ahmad Abd Allah
Source
The International Arab Journal of Information Technology
Issue
Vol. 15, Issue 6 (30 Nov. 2018)12 p.
Publisher
Publication Date
2018-11-30
Country of Publication
Jordan
No. of Pages
12
Main Subjects
Information Technology and Computer Science
Abstract EN
-Middle-East region is mostly characterized by a hot and dry climate, vast deserts and long coastlines.
Deserts cover large areas, while agricultural lands are described as small areas of arable land under perennial grass pastures or crops.
In view of the harsh climate and falling ground-water level, it is critical to identify which agriculture produce to grow, and where to grow it? The traditional methods used for this purpose are expensive, complex, prone to subjectivity, risky and are time-consuming; this points to the need of exploring novel IT techniques using GIS (Geographic Information Systems).
In this paper, we present a data-driven stand-alone flexible analysis environment i.e.
Spatial Prediction and Overlay Tool (SPOT).
SPOT is predictive spatial data mining GIS tool designed to facilitate decision support by processing and analysing agro-meteorological and socio-economic thematic maps and generating crop cultivation geo-referenced prediction maps by predicative data mining.
In this paper, we present a case study of Saudi Arabia by using decade old wheat cultivation data, and compare the historically uncultivated regions predicted by SPOT with their current cultivation status.
The prediction results were found to be promising after verification in time and space using latest satellite imagery followed by on-site physical ground verification using GPS.
American Psychological Association (APA)
Abd Allah, Ahsan& Bakhashwain, Ahmad Abd Allah& Basuhail, Abd Allah& Aslam, Ahtisham. 2018. Using data mining for predicting cultivable uncultivated regions in the Middle East. The International Arab Journal of Information Technology،Vol. 15, no. 6.
https://search.emarefa.net/detail/BIM-874031
Modern Language Association (MLA)
Abd Allah, Ahsan…[et al.]. Using data mining for predicting cultivable uncultivated regions in the Middle East. The International Arab Journal of Information Technology Vol. 15, no. 6 (Nov. 2018).
https://search.emarefa.net/detail/BIM-874031
American Medical Association (AMA)
Abd Allah, Ahsan& Bakhashwain, Ahmad Abd Allah& Basuhail, Abd Allah& Aslam, Ahtisham. Using data mining for predicting cultivable uncultivated regions in the Middle East. The International Arab Journal of Information Technology. 2018. Vol. 15, no. 6.
https://search.emarefa.net/detail/BIM-874031
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-874031