The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIV-4/W3-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-4/W3-2020, 383–389, 2020
https://doi.org/10.5194/isprs-archives-XLIV-4-W3-2020-383-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIV-4/W3-2020, 383–389, 2020
https://doi.org/10.5194/isprs-archives-XLIV-4-W3-2020-383-2020

  23 Nov 2020

23 Nov 2020

USING GIS-BASED MULTI-CRITERIA DECISION ANALYSIS TECHNIQUES IN THE SMART CITIES

S. Sisman and A. C. Aydinoglu S. Sisman and A. C. Aydinoglu
  • Dept. of Geomatics Engineering, Gebze Technical University, 41400 Gebze, Kocaeli, Turkey

Keywords: Geography Information Systems (GIS), Multi Criteria Decision Analysis (MCDA), Smart Cities

Abstract. The population of cities is increasing rapidly nowadays, and therefore, rational use of urban resources is required. With developing technology, the amount of data obtained from different sources also increases. This situation sometimes causes complex geographic decision problems in cities where many factors must be evaluated simultaneously. Difficulties in this decision-making process can be overcome by using Multi-Criteria Decision Analysis (MCDA) techniques. In this study, how the different MCDA techniques can be used in geographic-based problems and the most commonly used methods were examined in this context. The case applications on the adaptation of GIS-based MCDA techniques in smart cities were examined and explained. All of the examined case applications were carried out in the Pendik district of Istanbul. The subjects of the investigated case applications are, respectively, the evaluation of land suitability for determining urban development areas, producing a land value map for the management of the urban real estate, parking areas selection for sustainable urban transportation planning, and prioritizing suitable/alternative car parking areas. This study provides an effective implementation methodology for the hybrid use of GIS-based MCDA techniques within the scope of sustainable urban land management practices in smart cities.