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Related Concept Videos

Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
Manipulation and Analysis01:21

Manipulation and Analysis

GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
Thematic Layering in GIS01:30

Thematic Layering in GIS

In the past, planning projects such as schools or public facilities required extensive manual effort to gather and compile data. Information such as property boundaries, soil characteristics, road networks, zoning regulations, and flood zones had to be sourced individually from courthouses, utility providers, and registry offices. Assembling these datasets into a coherent format often took several months, delaying project timelines.The introduction of Geographic Information Systems (GIS)...
Levels of Use of a GIS01:29

Levels of Use of a GIS

Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
Applications of GIS: Disaster Management and Emergency Response01:29

Applications of GIS: Disaster Management and Emergency Response

Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...

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Related Experiment Video

Updated: Jun 28, 2026

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
14:55

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

A multiscale interpretability framework for identifying actionable road network features to mitigate congestion in

Nishant Kumar1, Yatao Zhang2, Nina Wiedemann3

  • 1National University of Singapore (NUS), Singapore, Singapore.

Scientific Reports
|June 26, 2026
PubMed
Summary
This summary is machine-generated.

Transferring traffic congestion strategies between cities is hard. This study identifies actionable road network features for demand-side planning, revealing commonalities across cities for better traffic management.

Related Experiment Videos

Last Updated: Jun 28, 2026

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
14:55

Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

Published on: January 20, 2023

Area of Science:

  • Urban Planning
  • Transportation Engineering
  • Data Science

Background:

  • Transferring traffic congestion mitigation strategies across cities is hindered by city-specific road network features and varying spatial scale influences.
  • Effective urban planning requires understanding how road network characteristics impact traffic congestion at different resolutions.

Purpose of the Study:

  • To develop a multiscale framework for identifying actionable road network features that consistently correlate with traffic congestion across spatial scales.
  • To investigate city-specific and common features influencing traffic congestion for improved urban planning and policy development.

Main Methods:

  • A multiscale framework was applied to analyze road network features and traffic congestion in seven major global cities.
  • Feature importance and directional associations were systematically investigated using Random Forest-based TreeSHAP (RF-based TreeSHAP).

Main Results:

  • Significant city-specific variations in road network feature importance for supply-side planning were observed.
  • Consistent exacerbating features for demand-side considerations were identified across multiple cities, suggesting transferable insights.
  • Directional associations were found to reflect data patterns, not necessarily causal effects, requiring further validation.

Conclusions:

  • Urban congestion mitigation strategies, particularly demand-side measures, can benefit from transferable insights derived from consistently identified road network features.
  • Future urban planning should consider micro-scale spatial analysis and test road network features beyond current ranges to design more resilient cities.
  • The findings support tailoring supply-side planning individually while leveraging commonalities for demand-side interventions and policy robustness.