Analysis of the role of micro-scale environmental factors in predicting the occurrence of construction violations(Case study: Khorramabad city)

Enayat Mirzaei ¹ ( Assistant Professor of Urban Planning Department, Engineering Faculty, Lorestan University, Iran. )
Gholam Reza Mirzaei ² ( Assistant Professor of Urban Planning, Art and Architecture Faculty, Salman Farsi University of Kazerun, Iran. )
Elahe Balvasi ³ ( Bachelor student in urban planning, Lorestan University, Iran. )

Submited date : 2024-04-23 Accepted date : 2024-08-01

Keywords: Khorramabad, Construction violations, Environmental variables, Generalized logistic regression,

Abstract :

Over the past few decades, the increasing growth of construction violations has greatly affected the physical-spatial structure and urban landscape and has become a serious challenge for city officials and planners. During the past 5 years, about 9457 cases related to construction violations have been referred to the preliminary commission of Article 100 of Khorramabad Municipality, which indicates the prevalence of this phenomenon. Although numerous studies have been conducted in this field in the past years, there are still some research gaps. In line with previous studies, the purpose of the current research is to analyze the impact of environmental and social factors in micro-scale on predicting the probability of construction violations; a subject that has received less attention in previous studies. In terms of method, this research is a quantitative study; and uses descriptive and inferential statistical methods for data analysis. Thirty variables were defined to measure built environment and social dimensions. The data were gathered from 4191 urban blocks located in Khorramabad with the help of ArcGIS Pro software. Then, these variables were reduced into eight underlying factors using the factor analysis method (principal component analysis). The construction violations committed in the last five years have been assigned to the relevant blocks as a dependent variable, after being extracted from the municipal database. The generalized logistic regression model has been used to analyze the relationships between the variables. The results of the data analysis showed that the factors of price, the volume of issued permits, and high density in the urban block have a direct effect, and the factors of density, non-residential-non-commercial area, and the average area of residential plots have an inverse effect on the probability of construction violations. Furthermore, the variations in the influence coefficient of two factors including price and density on the probability of construction violations among urban blocks are significant.