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A Model for Locating Tall Buildings through a Visual Analysis Approach.

Authors :
Karimimoshaver, Mehrdad
Hajivaliei, Hatameh
Shokri, Manouchehr
Khalesro, Shakila
Aram, Farshid
Shamshirband, Shahab
Source :
Applied Sciences (2076-3417); Sep2020, Vol. 10 Issue 17, p6072, 25p
Publication Year :
2020

Abstract

Tall buildings have become an integral part of cities despite all their pros and cons. Some current tall buildings have several problems because of their unsuitable location; the problems include increasing density, imposing traffic on urban thoroughfares, blocking view corridors, etc. Some of these buildings have destroyed desirable views of the city. In this research, different criteria have been chosen, such as environment, access, social-economic, land-use, and physical context. These criteria and sub-criteria are prioritized and weighted by the analytic network process (ANP) based on experts' opinions, using Super Decisions V2.8 software. On the other hand, layers corresponding to sub-criteria were made in ArcGIS 10.3 simultaneously, then via a weighted overlay (map algebra), a locating plan was created. In the next step seven hypothetical tall buildings (20 stories), in the best part of the locating plan, were considered to evaluate how much of theses hypothetical buildings would be visible (fuzzy visibility) from the street and open spaces throughout the city. These processes have been modeled by MATLAB software, and the final fuzzy visibility plan was created by ArcGIS. Fuzzy visibility results can help city managers and planners to choose which location is suitable for a tall building and how much visibility may be appropriate. The proposed model can locate tall buildings based on technical and visual criteria in the future development of the city and it can be widely used in any city as long as the criteria and weights are localized. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
10
Issue :
17
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
145988918
Full Text :
https://doi.org/10.3390/app10176072