Home Articles List Article Information
JES. Journal of Engineering Sciences
Journal Archive
Volume Volume 52 (2024)
Volume Volume 51 (2023)
Volume Volume 50 (2022)
Volume Volume 49 (2021)
Volume Volume 48 (2020)
Volume Volume 47 (2019)
Volume Volume 46 (2018)
Volume Volume 45 (2017)
Volume Volume 44 (2016)
Volume Volume 43 (2015)
Volume Volume 42 (2014)
Volume Volume 41 (2013)
Volume Volume 40 (2012)
Volume Volume 39 (2011)
Volume Volume 38 (2010)
Volume Volume 37 (2009)
Volume Volume 36 (2008)
Volume Volume 35 (2007)
Volume Volume 34 (2006)
A. Farrag, F., G. Mostafa, Y., A. Mohamed, N. (2020). DETECTING LAND COVER CHANGES USING VHR SATELLITE IMAGES: A COMPARATIVE STUDY. JES. Journal of Engineering Sciences, 48(No 2), 200-211. doi: 10.21608/jesaun.2019.264927
Farrag A. Farrag; Yasser G. Mostafa; Nasser A. Mohamed. "DETECTING LAND COVER CHANGES USING VHR SATELLITE IMAGES: A COMPARATIVE STUDY". JES. Journal of Engineering Sciences, 48, No 2, 2020, 200-211. doi: 10.21608/jesaun.2019.264927
A. Farrag, F., G. Mostafa, Y., A. Mohamed, N. (2020). 'DETECTING LAND COVER CHANGES USING VHR SATELLITE IMAGES: A COMPARATIVE STUDY', JES. Journal of Engineering Sciences, 48(No 2), pp. 200-211. doi: 10.21608/jesaun.2019.264927
A. Farrag, F., G. Mostafa, Y., A. Mohamed, N. DETECTING LAND COVER CHANGES USING VHR SATELLITE IMAGES: A COMPARATIVE STUDY. JES. Journal of Engineering Sciences, 2020; 48(No 2): 200-211. doi: 10.21608/jesaun.2019.264927

DETECTING LAND COVER CHANGES USING VHR SATELLITE IMAGES: A COMPARATIVE STUDY

Article 2, Volume 48, No 2, March and April 2020, Page 200-211  XML PDF (942.64 K)
Document Type: Research Paper
DOI: 10.21608/jesaun.2019.264927
View on SCiNiTO View on SCiNiTO
Authors
Farrag A. Farrag1; Yasser G. Mostafa2; Nasser A. Mohamed3
1Civil Eng. Dpt. Faculty of Engineering, Assiut University.
2Civil Eng. Dpt. Faculty of Engineering, Sohag University.
3Civil Eng. Dpt. Faculty of Engineering, Sohag University
Abstract
The new satellites sensors such as GeoEye , WorldView and Ikonos , provide new data for better delineation, detection, and visualization of Land cover changes. Several techniques have been proposed and developed for change detection automatically. The main aim of this research is to assess the use of very high-resolution satellites images in monitoring land cover changes in Egypt. Five change detection techniques have been tested using Ikonos and WorldView images. The techniques considered are image difference, image ratio, principal component analysis, postclassification comparison, and multi-date direct classification. The accuracy of each technique is evaluated via the overall accuracy and kappa coefficient. The results showed that the principal component analysis technique produced more accurate change detection map compared to other methods. Also, it was found that changes from vegetation to urban in the study area are greater than changes from bare soil to vegetation.
Keywords
change detection; very high-resolution; object-based
Main Subjects
Civil Engineering: structural, Geotechnical, reinforced concrete and steel structures, Surveying, Road and traffic engineering, water resources, Irrigation structures, Environmental and sanitary engineering, Hydraulic, Railway, construction Management.
Statistics
Article View: 117
PDF Download: 255