A Comparative Study of the Different Remote Sensing Techniques for Evaluating Land Use/ Cover in Basra City, Iraq. | ||||
| MEJ- Mansoura Engineering Journal | ||||
| Article 17, Volume 45, Issue 4, December 2020, Page 21-32 PDF (1.71 MB) | ||||
| Document Type: Research Studies | ||||
| DOI: 10.21608/bfemu.2021.139429 | ||||
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| Authors | ||||
Mahmoud Elmwafi Shteiwi1; F. Zarzoura2; Zaid Jumaah  3
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| 1Professor of surveying and geodesy in Public Works Department, Faculty of Engineering, Mansoura University, Egypt. | ||||
| 2Lecturer in Public Works Department, Faculty of Engineering, Mansoura University, Egypt | ||||
| 3Department of Public Works, Faculty of Engineering, Mansoura University, Egypt. | ||||
| Abstract | ||||
| Basra governorate represents one of the most important governorates in Iraq, where it is the only seaport for exporting oil and agriculture products. However, this governorate is facing serious land degradation problems results in major changes in land use/ cover (LULC) within the area. Accordingly, the main objective of this study was to evaluate LULC in Basra city using different techniques on remotely sensed data. For that purpose, Landsat 8, Sentinel 2A images were used in 2018 to study extent of urban areas, agricultural lands, water bodies and bare lands areas in Basra city center. The studied techniques include: the supervised classification in three methods (minimum distance, maximum likelihood, and Mahalanobis distance), spectral indices, manual digitizing of features and land surface temperature (LST). These methods were applied on both Sentinel 2A and Landsat data at three spatial resolutions 10, 15 and 30 m, respectively. The obtained results indicated that the minimum distance technique has the highest accuracy in identifying LULC when compared with the other classification methods. It was found that the higher the spatial resolution the higher the accuracy of the results. The spectral indices were more accurate than the classification methods in identifying agricultural areas and water bodies. There was a higher inclusion between urban areas and bare lands due to the similarity in their spectral reflectance. Accordingly, it is recommended to manually digitize urban areas than classifying it. The LST can be used as an indirect and fairly accurate method for evaluating LULC in Al-Basra city. In conclusion, remote sensing data and techniques could help in providing more accurate information about LULC in Basra City to be used in its future planning and sustainable development | ||||
| Keywords | ||||
| Land use/ cover; Land degradation; Remote sensing; image classification; Land surface temperature Basra city | ||||
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