Scholarly record
SPATIO-TEMPORAL ANALYSIS OF URBAN EXPANSION USING REMOTE SENSING DATA
Abstract
The rapid increase of the population, misuse of natural resources, contradictions about potential land use are the most important problems on the agenda of many developed and developing countries around the world. In the last century, the migrations from urban areas to rural areas due to labor force employment and living conditions led to the growth and urban expansion in the cities. This situation reveals the necessary changes in land use in order to provide people with the fundamental needs such as food, accommodation, and transportation. Therefore, monitoring and modeling the urban expansion in the cities is the key parameter to take the necessary precautions. Today, one of the efficient ways to monitor the urban expansion is to use Remote Sensing (RS) and Geographic Information Systems (GIS) technologies. The urban development of the highly populated areas of Istanbul including the Bosporus is selected as the study area. The land changes are modeled considering the current trends, ecological conditions, and digital elevation models. The main purpose of the study is to determine the land use, land cover, and land management decisions in order to evaluate the growth policies and their potential effects in Istanbul. LandSAT satellite images for the years of 2003 and 2016 are used in this study. The land use and land cover types are derived and classified from the satellite images using ENVI software. The images contain seven classes as follows; Arable Land, Construction Side, Forest, Road, Urban Fabric, Water, and Yellow Soil. The classified images are evaluated with TerrSET software to determine the changes quantitatively between the corresponding years. Finally, the study results and generated information are visualized in ArcGIS as commonly used GIS software. Based on the analysis of the classified images, the study reveals that the most of the area loses are observed in the classes of Forest, Arable Land, and Water while the most of area increases are observed in the classes of Road, Construction Side, and Urban Fabric. It can be stated that the increases in the Road and Construction Side classes are caused by the mega projects of Istanbul. These projects are Istanbul Canal, the third bridge over the Bosporus, and the third international airport. The decreases and increases trends reveal that the study area has been deforesting and a rapid increase in the urban and built-up areas should be expected in the near future.
Publication Impact Profile
Publication details
References9
United Nations, World Urbanization Prospects, The 2014 Revision, 2014.
Fenta, A. A., Yasuda, H., Haregeweyn, N., Belay, A. S., Hadush, Z., Gebremedhin, M. A., Mekonnen, G., The dynamics of urban expansion and land use/land cover changes using remote sensing and spatial metrics: the case of Mekelle City of northern Ethiopia, International Journal of Remote Sensing, 38(14), 4107-4129, 2017.
Berberoğlu, S., Akın, A., Clarke, K. C., Cellular automata modeling approaches to forecast urban growth for Adana, Turkey: A comparative approach, Landscape and Urban Planning, 153, 11-27, 2016.
Akintunde, J. A., Adzandeh, E. A., Fabiyi, O. O., Spatio-temporal pattern of urban growth in Jos Metropolis, Nigeria, Remote Sensing Applications: Society and Environment, 4, 44-54, 2016.
Wilson, A. G., Urban and regional models in geography and planning. John Wiley & Sons Inc., 1974.
Fazal, S., Amin, A., Impact of urban land transformation on water bodies in Srinagar City, India, Journal of environmental protection, 2(02), 142, 2011.
Pauchard, A., Aguayo, M., Peña, E., Urrutia, R., Multiple effects of urbanization on the biodiversity of developing countries: the case of a fast-growing metropolitan area (Concepción, Chile), Biological conservation, 127(3), 272-281, 2006.
Yeh, A. G. O., Li, X., A constrained CA model for the simulation and planning of sustainable urban forms by using GIS, Environment and Planning B: Planning and Design, 28(5), 733-753, 2001.
Jensen, J. R., Introductory digital image processing: a remote sensing perspective (No. Ed. 2). Prentice-Hall Inc., 1996.
Citing literature
Number of times cited according to Crossref: 1
View or Download full articleAccess options
SWS access login
Login as SWS Scientific CommitteeLogin as SWS Scientific PartnerLogin as SWS AuthorAuthors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.
For librarian assistance: [email protected]
Purchase Instant Access
- Article can be downloaded after successful payment.
- Article may be used according to SWS library access terms.
- Article cannot be redistributed.
