A Novel Approach to Measure the Pattern of Urban Agglomeration Based on the Road Network

Kalpana, Lindamullage Don Charls Hasintha Nawod; Abenayake, Chethika; Jayasinghe, Amila; Mahanama, Pelpola K.S.; Sanjaya, Niroshan

doi:10.18280/ijsdp.160205

Cited by 4 publications

(3 citation statements)

References 32 publications

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“…To perform percolation analysis, this study uses the DBSCAN algorithm. Density-based spatial clustering of applications with noise (DBSCAN) is a machine-learning algorithm that generates density clusters based on the Euclidian distance to each identical network node (Kalpana et al, 2021). This DBSCAN calculation uses the software QGIS 3.22 with the DBSCAN Clustering algorithm.…”

Section: Percolation (Dbscan)mentioning

confidence: 99%

Fractal Dimensions Analysis of Urban Agglomeration at Road Intersections in Metropolitan Malang Raya

Afrianto

2023

IOP Conf. Ser.: Earth Environ. Sci.

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The agglomeration review is mostly carried out by identifying the physical and economic dispersal processes of the two growth poles. Many researchers conclude on the result of agglomeration rather than the process nor the forecasts. This study tries to examine the process of urban agglomeration in the metropolitan city of Malang. This is done by combining city fractal theory and urban percolation. The DBSCAN clustering approach at the intersection is used to identify the agglomeration process between the growth poles. While Minkowski’s Dimensional theory is used to identify the fractals that occur. The calculation results show that the maximum Minkowski dimension distribution figure is 200m. It indicates the fractals that occur in the road network data. The DBSCAN clustering modeling at 200m has a strong correlation with the number of light intensity values in the 2021 nighttime light satellite imagery. On the other hand, modeling at 250m to 350m provides an overview of the future agglomeration. This research can be the basis for urban planners to analyze the agglomeration process and predict the future.

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Section: Percolation (Dbscan)mentioning

confidence: 99%

Fractal Dimensions Analysis of Urban Agglomeration at Road Intersections in Metropolitan Malang Raya

Afrianto

2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…In such a context, this study utilized the iCN Model to derive the urban boundaries of cities. The iCN Model is a multi-functional urban simulation tool developed by (Kalpana et al 2021), which is capable of modeling the urban agglomeration and urban development pattern of cities. Thus, in this study, the same analytical framework was used to determine urban boundaries of cities.…”

Section: Existing Applications Limitations and Failuresmentioning

confidence: 99%

“…The iCN Model is a multi-functional urban simulation tool developed by (Kalpana et al 2021), which is capable of modeling the urban agglomeration and urban development patterns of cities. It has been developed under three fundamental concepts of the network science, identified as Road Network Configuration, Percolation Theory and Fractal Geometry.…”

Section: Application Of the Icn Model To Identify Urban Boundariesmentioning

confidence: 99%

Urban Boundary Demarcation—An iCN Model Approach

et al. 2021

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During the last two decades, determining the urban boundaries of cities has become one of the major concerns in the urban and regional planning subject domains. Many scholars have tried to model the change of urban boundaries as it helps with sustainable development, population projections and social policy making, but such efforts have been futile, owing to the complex nature of urbanization and the theoretical and technical limitations of the proposed applications. Hence, many countries continue to rely on the administrative boundary demarcation, which rarely represent the actual urbanizing pattern. In such context, this study utilized the “Intersection-Based Clustered Network Model—(iCN Model)” to determine the urban boundaries of cities and selected Sri Lanka as the study area and considered few cities to test the model empirically, with satellite imagery classified urban boundaries. The findings of the study depict that the iCN Model is capable of capturing the complex and dynamic socioeconomic interdependencies of cities via the transportation network configurations. Therefore, the proposed approach is an excellent proxy to derive the urban boundaries of cities, which correspond with the same, derived by the satellite imageries. The proposed model is entirely based on open-source GIS applications and is free to implement and modify using the methods described in this paper.

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Percolation Model to Capture Urban Coalescence («Natural Cities»). The Case of Italy

Lombardini

2024

Lecture Notes in Civil Engineering

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A Novel Approach to Measure the Pattern of Urban Agglomeration Based on the Road Network

Cited by 4 publications

References 32 publications

Fractal Dimensions Analysis of Urban Agglomeration at Road Intersections in Metropolitan Malang Raya

Fractal Dimensions Analysis of Urban Agglomeration at Road Intersections in Metropolitan Malang Raya

Urban Boundary Demarcation—An iCN Model Approach

Percolation Model to Capture Urban Coalescence («Natural Cities»). The Case of Italy

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