Utilizing Nighttime Photos to Locate Attraction Zones at the Metropolitan Scale: An Analysis of Istanbul

Abstract

Up-to-date information about different forms of land-use (residential areas, industrial areas, central business districts, recreational areas, etc.) is essential for city planning processes to obtain better urban and regional planning decisions. Traditional methods (e.g., field surveying or WEB/GPS based data collection) used to gather up-to-date information can often contain some errors and can also be time-consuming and expensive, especially for large metropolitan urban areas. With the integration of Remote Sensing (RS) and Geographic Information Systems (GIS) related technologies, the difficulty of providing up-to-date information about different types of land-use can be greatly reduced. On the other hand, in terms of urban and regional planning, the level of utilization of these technologies is still considered to be insufficient. In this respect, authors wanted to draw attention to another possible usage of night-time data in urban and regional planning discipline for the purpose of determination of the location, size, and hierarchy of the attraction zones in urban scale which are mostly composed of central business districts (CBD), commercial zones, touristic corridors and/or concentration areas etc., as these regions are more illuminated areas compared to other zones of a city. Thus, a methodology based on GIS and RS integration and spatial and statistical analysis capabilities of GIS is presented in this study to determine the boundary and size of the attraction zones and their hierarchical levels by using the night-time imageries. To show how effective the suggested model is, the proposed methodology has been used in the city of Istanbul. The assessment of the location, size, and hierarchy of the attraction zones could give an essential decision support for the decision makers, especially those working in the urban planning discipline, as the attraction zones of cities need to be developed in a more specific and detailed manner. Thus, the model's outputs' reliability and potential applications in the field of urban planning are also examined.