Detection of Residential Buildings to Estimate Population in Lebanon using GeoEye Images
| Dublin Core | PKP Metadata Items | Metadata for this Document | |
| 1. | Title | Title of document | Detection of Residential Buildings to Estimate Population in Lebanon using GeoEye Images |
| 2. | Creator | Author's name, affiliation, country | Kamel Allaw; CREEMO, Geography Department, Saint Joseph University, Beirut, Lebanon |
| 2. | Creator | Author's name, affiliation, country | Jocelyne Adjizian Gerard; CREEMO, Geography Department, Saint Joseph University, Beirut, Lebanon |
| 2. | Creator | Author's name, affiliation, country | Makram Chehayeb; Surveying Department, Islamic University of Lebanon, Lebanon |
| 2. | Creator | Author's name, affiliation, country | Nada Badaro Saliba; CREEMO, Geography Department, Saint Joseph University, Beirut, Lebanon |
| 2. | Creator | Author's name, affiliation, country | (doi: 10.23953/cloud.ijarsg.419) |
| 3. | Subject | Discipline(s) | |
| 3. | Subject | Keyword(s) | Building detection; Convex hull; High resolution satellite image; HIS; Population; Supervised classification |
| 4. | Description | Abstract | Scholars in urban planning and Geography are increasingly interested in grasping demographic information using Remote Sensing data. The accurate detection of residential buildings from satellite images seems to be essential in this domain. This paper has a dual purpose: It aims firstly at developing an automatized method for residential buildings extraction, then, evaluating the relationship between residential building characteristics (number, area, and volume) and demographic data. To do so, a dual phasic methodology is proposed. During the first phase, the extraction of residential buildings has been done using a transformation into HSI representation where the buildings corresponds to the higher values of band I. After that, the image has been transformed into vector and the forms of the buildings have been adjusted using convex hull tool in ArcGIS. The identification of residential buildings has been done using statistical data. The volumes of buildings has been calculated using MATLAB script. During the second phase, a multivariate regression has been established and a strong relationship (R2 =0.87) has been found between the volume of buildings and the population data. |
| 5. | Publisher | Organizing agency, location | |
| 6. | Contributor | Sponsor(s) | |
| 7. | Date | (YYYY-MM-DD) | 2019-08-27 |
| 8. | Type | Status & genre | Peer-reviewed Article |
| 8. | Type | Type | |
| 9. | Format | File format | |
| 10. | Identifier | Uniform Resource Identifier | http://technical.cloud-journals.com/index.php/IJARSG/article/view/961 |
| 11. | Source | Journal/conference title; vol., no. (year) | International Journal of Advanced Remote Sensing and GIS; Volume 8 (Year 2019) |
| 12. | Language | English=en | en |
| 14. | Coverage | Geo-spatial location, chronological period, research sample (gender, age, etc.) | |
| 15. | Rights | Copyright and permissions |
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