Design and Validation of a Computational Program for Analysing Mental Maps: Aram Mental Map Analyzer

Farshid Aram, Ebrahim Solgi, Ester Higueras García, Danial Mohammadzadeh S., Amir Mosavi and Shahaboddin Shamshirband
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Farshid Aram: Escuela Técnica Superior de Arquitectura, Universidad Politécnica de Madrid-UPM, 28040 Madrid, Spain
Ebrahim Solgi: School of Engineering and Built Environment, Griffith University, Gold Coast 4215, Australia
Ester Higueras García: Escuela Técnica Superior de Arquitectura, Universidad Politécnica de Madrid-UPM, 28040 Madrid, Spain
Danial Mohammadzadeh S.: Department of Civil Engineering, Ferdowsi University of Mashhad, Mashhad 9177948974, Iran
Amir Mosavi: Faculty of Health, Queensland University of Technology, Brisbane QLD 4059, Australia
Shahaboddin Shamshirband: Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh, Vietnam
Authors registered in the RePEc Author Service: Danial Mohammadzadeh S., Sr. ()

Sustainability, 2019, vol. 11, issue 14, 1-20

Abstract: Considering citizens’ perceptions of their living environment is very helpful in making the right decisions for city planners who intend to build a sustainable society. Mental map analyses are widely used in understanding the level of perception of individuals regarding the surrounding environment. The present study introduces Aram Mental Map Analyzer (AMMA), an open-source program, which allows researchers to use special features and new analytical methods to receive outputs in numerical data and analytical maps with greater accuracy and speed. AMMA performance is contingent upon two principles of accuracy and complexity, the accuracy of the program is measured by Accuracy Placed Landmarks (APL) and General Orientation (GO), which respectively analyses the landmark placement accuracy and the main route mapping accuracy. Also, the complexity section is examined through two analyses Cell Percentage (CP) and General Structure (GS), which calculates the complexity of citizens’ perception of space based on the criteria derived from previous studies. AMMA examines all the dimensions and features of the graphic maps and its outputs have a wide range of valid and differentiated information, which is tailored to the research and information subject matter that is required.

Keywords: Smart urban planning; sustainable urban development; mental maps; smart cities; quantitative analysis; environmental psychology; landmark; sustainable society (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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