Evaluating Road Network Complexity of Hyderabads Regional Ring Road Using Fractal Dimension

Abstract

Urban growth in Hyderabad has accelerated the demand for efficient transport corridors, leading to the development of the Regional Ring Road (RRR). This study evaluates the northern section of the RRR (160 km) using Fractal Dimension (FD) analysis to understand its effect on road network complexity and connectivity. The box-counting method was applied in ArcGIS at multiple grid scales to compute FD in two scenarios: with and without the RRR’s Northern corridor. Results at the metropolitan scale show a measurable rise in FD after integrating the RRR, reflecting enhanced spatial coverage and improved connectivity.At the micro level, six representative zones (J1–J6) were analysed using combined FD and road density metrics to classify network typologies as Saturated, Fragmented, Emerging, and Inefficient. Zones such as Sangareddy (J1) and Bhongir (J5) showed high road density but low FD, classified as Inefficient, indicating unstructured layouts, while othersexhibited low density and poor integration. The findings highlight FD’s value as a diagnostic tool to guide infrastructure planning, ensuring balanced growth and better accessibility in rapidly expanding metropolitan regions.

Introduction

Hyderabad's rapid urban expansion has strained its transport infrastructure. The proposed 330 km Regional Ring Road (RRR) aims to:

• Relieve congestion

• Improve interconnectivity

• Support balanced urban growth

This study applies Fractal Dimension (FD) — a metric from fractal geometry — to assess how the northern corridor of the RRR affects Hyderabad’s road network, both city-wide (macro level) and locally (micro level).

2. Why Fractal Dimension (FD)?

• FD quantifies spatial complexity and connectivity, going beyond basic metrics like road length or density.

• A higher FD suggests a more interconnected, space-filling network.

• Used here with Box-Counting Method integrated into ArcGIS workflows for both macro and micro analysis.

3. Objectives

• Calculate FD of Hyderabad’s road network with/without RRR (north).

• Compare FD values to assess impact on urban connectivity.

• Classify six local zones (J1–J6) along the northern RRR corridor using FD and road density, identifying patterns like fragmented or inefficient growth.

4. Methodology

A. Study Area & Data

• Hyderabad Metropolitan Region (~6,789 km²)

• Road data sourced from OpenStreetMap via BBBike Extract.

• Roads cleaned and standardized in ArcGIS Pro.

• Network evaluated at multiple scales using fishnet grids (30×30 to 200×200).

B. FD Calculation

• Modified Box-Counting Method: Log–log plot of intersecting grids vs total grid count.

• Regression slope = FD value.

• FD close to 2 = highly connected, <1.6 = sparse or fragmented.

C. Road Density

• Road length per km² calculated in each zone.

• Used alongside FD for typology classification.

5. Macro Analysis (Entire Network)

Impact of RRR on Spatial Complexity:

• FD increases slightly with RRR (especially in finer grids).

• Suggests better circumferential connectivity in the north, easing pressure on city center roads.

• Small FD rise signals structural improvement even without major additions to total road length.

6. Micro Analysis (Zones J1–J6)

Typology Definitions:

7. Key Findings

• Fragmented Zones (J2, J3, J4, J6):

  • Sparse, disconnected road networks.

  • Need urgent new road connections to integrate with broader city.

• Inefficient Zones (J1, J5):

  • High density but poor structure and flow.

  • Require planning controls and restructuring, not just more roads.

• No zones are “saturated”—none have optimal structure and density yet.

8. Planning Implications

• The RRR improves regional connectivity and adds structural order, particularly in developing corridors.

• FD + Density analysis provides a diagnostic tool for identifying where interventions should focus:

  • Build new roads in fragmented zones.

  • Optimize and restructure in inefficient areas.

• Offers a data-driven planning framework aligned with sustainable urban development.

Conclusion

This study assessed the spatial impact of the Regional Ring Road (RRR) on Hyderabad’s Road network using Fractal Dimension (FD) and road density analysis. The methodology applied a box-counting approach at macro and micro scales to quantify structural connectivity, followed by typology classificationto guide planning decisions.

References

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Copyright

Copyright © 2025 Shaik Afroz Sharook, P. Sravana, Tejavath Naresh. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.