Document Details

Document Type : Article In Journal 
Document Title :
Comparison of Four Classification Methods to Extract Land Use and Land Cover from Raw Satellite Images for Some Remote Arid Areas, Kingdom of Saudi Arabia
مقارنة أربعة طرق تصنيف لاستخلاص الغطاء الأرضي واستخدامات الأراضي من صور الأقمار الصناعية الخام لبعض المناطق الجافة النائية بالمملكة العربية السعودية
 
Subject : Earth Sciences 
Document Language : English 
Abstract : Remote sensing (RS) technologies was utilized to extract some of the important spatially variable parameters, such as land cover and land use (LCLU), from satellite images for remote arid areas in Saudi Arabia. Four different classification techniques unsupervised (ISODATA), and supervised (Maximum likelihood, Mahalanobis Distance, and Minimum Distance) are applied in three sub-catchments in Saudi Arabia for the classification of the raw TM5 images. The developed maps are then visually compared with each other and accuracy assessments utilizing ground-truths are undertaken. It was found that the Maximum likelihood method gave the best results and both Minimum distance and Mahalanobis distance methods overestimated agriculture land and suburban areas. In spite of missing few insignificant features due to the low resolution of the satellite images (90m), good agreement between parameters extracted automatically from the developed maps and field observations was found. 
ISSN : 1012-8832 
Journal Name : Earth Sciences Journal 
Volume : 20 
Issue Number : 1 
Publishing Year : 1430 AH
2009 AD 
Number Of Pages : 24 
Article Type : Article 
Added Date : Sunday, October 11, 2009 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
فهد سالم الأحمدي F. S. Al-AhmadiResearcher  
أحمد شفيق الحمصA. S. Al-HamesResearcher  

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