Python Library for Road Network Analysis in the Case of Debre Berhan City

Python Library for Road Network Analysis in the Case of Debre Berhan City

Copyright: © 2024 |Pages: 18
DOI: 10.4018/979-8-3693-1754-9.ch009
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Abstract

This study employs the Python library for road network analysis in the Debre Berhan Metropolitan City, focusing on determining the best route, shortest path, road types, length in km, and speed limit in km/h. Geopandas is utilized to visualize the road network data, enabling the calculation of the shortest path and extraction of road type and speed limit information. Network analysis libraries like,folium, NetworkX convert the data into a graph representation, using algorithms like Dijkstra's or A* to find the shortest path based on distance or travel time. Geopandas then overlays road segments on a map, highlighting the shortest path and indicating road type, length, and speed limit, offering a robust framework for assessing and optimizing the road network in urban areas and contributing to the effective management and enhancement of transportation infrastructure.
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Road Network Analysis

The topology of spatial networks represents the spatial relationships, including the shape and structural configuration of the network (Dumedah & Garsonu, 2021). According to Dumedah & Garsonu, topological measures assess the network's configuration, connectedness, and robustness – and how these characteristics are distributed. The main objective of network analysis is to Find optimal school locations using spatial data (Wondwossen Mindahun & Bedasa Asefa, 2019).

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