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Land Use Land Cover of an Urban Area using Remote Sensing (Texture Analysis Applications) and GIS - A Case Study of Central Region of Almadinah Almunawarah, Saudi Arabia


 
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1. Title Title of document Land Use Land Cover of an Urban Area using Remote Sensing (Texture Analysis Applications) and GIS - A Case Study of Central Region of Almadinah Almunawarah, Saudi Arabia
 
2. Creator Author's name, affiliation, country Saleh Daqamseh; Department of Human Sciences & Technology, Geography, Taibah University, Medina, Kingdom of Saudi Arabia
 
2. Creator Author's name, affiliation, country (doi: 10.23953/cloud.ijarsg.256)
 
3. Subject Discipline(s)
 
3. Subject Keyword(s) classification; commercial area; IKONOS; image processing; geography; geospatial information; remote sensing; land cover
 
4. Description Abstract In this study IKONOS images with high spatial resolution have been used for urban planning classification. This research explores approaches to improve urban planning and build up the data base for types of patterns area within the urban scheme in central of Almadinah Almunawarah using remote sensing based on Texture Analysis Applications and Geospatial Information System (GIS softwares). It has been compared with Traditional method (Field Survey) of urban planning classification in Almadinah Almunawarah. The activities of central Almadinah was divided into commercial area, investment area, industrial area, health services building, religious building, garden, infrastructure, government services building, and agricultural area. The results of this study showed the commercial and investments area was the largest area 6.5 km, and it is followed by religious services 3.2 km, while the third ring area the largest area was the agricultural housing area 16 km and then followed by commercial and investments area 5.3 km of the total area. This study recommends to use remote sensing data to classify the urban planning due to significantly improve land cover classification performance compare to traditional survey.
 
5. Publisher Organizing agency, location
 
6. Contributor Sponsor(s)
 
7. Date (YYYY-MM-DD) 2017-04-29
 
8. Type Status & genre Peer-reviewed Article
 
8. Type Type
 
9. Format File format PDF
 
10. Identifier Uniform Resource Identifier http://technical.cloud-journals.com/index.php/IJARSG/article/view/733
11. Source Journal/conference title; vol., no. (year) International Journal of Advanced Remote Sensing and GIS; Volume 6 (Year 2017)
 
12. Language English=en en
 
14. Coverage Geo-spatial location, chronological period, research sample (gender, age, etc.)
 
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