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Land Use Classification and Change Detection Using Multi-temporal Landsat Imagery in Sulaimaniyah Governorate, Iraq: Land Use Classification and Change Detection Using Multi-temporal Landsat Imagery in Sulaimaniyah Governorate, Iraq
2019 (English)In: Advances in Remote Sensing and Geo Informatics Applications: Advances in Remote Sensing and Geo Informatics Applications / [ed] Hesham M. El-AskarySaro LeeEssam HeggyBiswajeet Pradhan, Switzerland: Springer, 2019, p. 117-120Conference paper, Published paper (Refereed) [Artistic work]
Abstract [en]

Rapid growth in urbanized areas is a worldwide phenomenon.The rate of urban growth is very fast in developing countries like Iraq. This study illustrated urbanized area development in Sulaimaniyah Governorate from 2001 to 2017 using different Landsat imagery, Landsat Thematic Mapper (TM) and Landsat Operational Land Imager (OLI). The Environment for visualizing images ENVI 5.3 and GIS software was utilized for image pre-processing, calibration and classification. The Maximum likelihood method was used in the accurately

extracted solution information from geospatial Landsat satellite imagery of different periods. The Landsat images from the study area were categorized into six different classes. These are: forest, vegetation, rock, soil, built up and water body. Land cover variation and land use change detection in the area were calculated for over a 17 year period. The Change detection Analysis shows an explosive demographic shift in the urban area with a record of +8.99% which is equivalent to 51.80 km   over a 17 years period and the vegetation area increased with 214 km 2. On the other hand, soil area was reduced by 257.87 km 2. This work will help urban planners in the future development of the city.

Place, publisher, year, edition, pages
Switzerland: Springer, 2019. p. 117-120
Series
Advances in Science, Technology & Innovation
Keywords [en]
Land use land cover (LULC), Maximum likelihood classification (MLC), Change detection
National Category
Engineering and Technology
Research subject
Environmental Management
Identifiers
URN: urn:nbn:se:ltu:diva-72657OAI: oai:DiVA.org:ltu-72657DiVA, id: diva2:1281708
Conference
Proceedings of the 1st Springer Conference of the Arabian Journal of Geosciences (CAJG-1), Tunisia 2018
Available from: 2019-01-23 Created: 2019-01-23 Last updated: 2019-09-06

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CiteExportLink to record
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