Serdar Bilgi
Biographic Data
| ID | 9965753 |
|---|---|
| NAME | Serdar Bilgi |
| GIVEN NAMES | Serdar |
| FAMILY NAME | Bilgi |
| SIGNATURE | BILGI S |
| AFFILIATIONS | Istanbul Technical University |
| ORCID | 0000-0002-8396-3202 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2020 |
| H-INDEX | 0 |
Evaluation of the Space Syntax Measures Affecting Pedestrian Density through Ordinal Logistic Regression Analysis
This paper examines the relationship between pedestrian density and space syntax measures in a university campus using ordinal logistic regression analysis. The pedestrian density assumed as the dependent variable of regression analysis was categorised in low, medium, and high classes by using Jenks natural break classification. The data elements of groups were derived from pedestrian counts performed in 22 gates 132 times. The counting period gr…
Citizens’ Spatial Footprint on Twitter—Anomaly, Trend and Bias Investigation in Istanbul
Social media (SM) can be an invaluable resource in terms of understanding and managing the effects of catastrophic disasters. In order to use SM platforms for public participatory (PP) mapping of emergency management activities, a bias investigation should be undertaken with regard to the data related to the study area (urban, regional or national, etc.) to determine the spatial data dynamics. Thus, such determinations can be made on how SM can b…
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Evaluation of the Space Syntax Measures Affecting Pedestrian Density through Ordinal Logistic Regression Analysis
This paper examines the relationship between pedestrian density and space syntax measures in a university campus using ordinal logistic regression analysis. The pedestrian density assumed as the dependent variable of regression analysis was categorised in low, medium, and high classes by using Jenks natural break classification. The data elements of groups were derived from pedestrian counts performed in 22 gates 132 times. The counting period gr…
Citizens’ Spatial Footprint on Twitter—Anomaly, Trend and Bias Investigation in Istanbul
Social media (SM) can be an invaluable resource in terms of understanding and managing the effects of catastrophic disasters. In order to use SM platforms for public participatory (PP) mapping of emergency management activities, a bias investigation should be undertaken with regard to the data related to the study area (urban, regional or national, etc.) to determine the spatial data dynamics. Thus, such determinations can be made on how SM can b…
Computer Science (2 works) · Geography (2 works) · Mathematics (2 works) · Anomaly detection (1 work) · Artificial Intelligence (1 work) · Data mining (1 work) · Data science (1 work) · Data-Driven Disease Surveillance (1 work) · Econometrics (1 work) · Engineering (1 work)