Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

199
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
199
Levels of Use of a GIS01:29

Levels of Use of a GIS

251
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...
251
Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

246
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...
246
Manipulation and Analysis01:21

Manipulation and Analysis

224
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...
224
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

184
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
184
Thematic Layering in GIS01:30

Thematic Layering in GIS

232
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)...
232

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

What's at the back door? Characterising thrift textile donations and their circular potential in the Canadian context.

Waste management (New York, N.Y.)·2026
Same author

Sustainability, profitability, and resiliency of the fast fashion industries during a pandemic.

Energy & environment (Brentwood, England)·2026
Same author

A framework to assess plastic recycling efficiency of the primary and final processors.

Journal of environmental management·2026
Same author

An analytical framework to decode socioeconomic interplays in pesticides and fertilizer container collection patterns using land dynamics metrics.

Waste management (New York, N.Y.)·2025
Same author

Sub-zero soil CO<sub>2</sub> respiration in biostimulated hydrocarbon-contaminated cold-climate soil can be linked to the soil-freezing characteristic curve.

Environmental science and pollution research international·2025
Same author

Management Assessment of used Oil, Filters, and containers in the Canadian automotive sector using resource recovery metrics.

Waste management (New York, N.Y.)·2024

Related Experiment Video

Updated: Dec 18, 2025

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

4.0K

Parameter interrelationships in a dual phase GIS-based municipal solid waste collection model.

Hoang Lan Vu1, Kelvin Tsun Wai Ng1, Damien Bolingbroke1

  • 1Environmental Systems Engineering, University of Regina, Saskatchewan, Canada.

Waste Management (New York, N.Y.)
|June 21, 2020
PubMed
Summary

This study introduces a GIS-based model for dual-phase solid waste collection, optimizing handcart and truck routes. The model identified optimal temporary collection points, reducing truck travel distances by 13.76%.

Keywords:
Geographic information systemLocation-allocationMulti-phase collection systemMunicipal solid waste collectionSpatial distribution of temporary collection pointVehicle routing problem

More Related Videos

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
11:41

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Published on: February 1, 2020

20.8K
Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon
09:44

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon

Published on: October 16, 2018

10.6K

Related Experiment Videos

Last Updated: Dec 18, 2025

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

4.0K
Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
11:41

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

Published on: February 1, 2020

20.8K
Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon
09:44

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon

Published on: October 16, 2018

10.6K

Area of Science:

  • Environmental Science
  • Operations Research
  • Geographic Information Systems

Background:

  • Geographic Information Systems (GIS) are underutilized in dual-phase solid waste collection systems.
  • Understanding interrelationships in waste collection is complex.

Purpose of the Study:

  • To propose a GIS-based dual-phase model for solid waste collection.
  • To estimate total system costs and optimize routes for handcart and truck phases.
  • To investigate interrelationships between model parameters and cost-effectiveness.

Main Methods:

  • Developed a GIS-based dual-phase model integrating handcart pre-collection and truck collection phases.
  • Utilized maximize coverage and minimize facility location-allocation tools to identify temporary collection points.
  • Modeled two vehicle routing problems separately for handcart and truck routes.
  • Evaluated 30 scenarios to analyze parameter interrelationships and costs.

Main Results:

  • The optimal scenario involved 11 temporary collection points and a 500m maximum handcart collection distance.
  • A single temporary collection point can serve approximately 2,590 people within 0.11 km².
  • The proposed model achieved a 13.76% reduction in truck travel distances compared to the status quo.
  • The number and distribution of temporary collection points significantly impacted cost-effectiveness.

Conclusions:

  • The GIS-based dual-phase model effectively optimizes solid waste collection.
  • Strategic placement of temporary collection points is crucial for cost-effective waste management.
  • The model provides valuable insights for improving waste collection efficiency in similar urban settings.