GIS is NOT a Load of Garbage

By Hany A. Hassaballa

Introduction

A geographic information system (GIS) is one of the most sophisticated contemporary technologies to capture, analyze and display spatial data (Chalkias and Lasaridi, 2011). Due to the nature of solid waste management operations, GIS provides an effective means to import, manage and examine solid waste data. Planning and operating a successful solid waste management strategy requires collecting a large amount of solid waste data and assets with static or dynamic locations. This article highlights the use of GIS technology in modern solid waste management operations.

Data Collection

Basemap Information

Like most other GIS applications, developing a basemap to be used as a reference and a backdrop for solid waste operation is an essential first step. Data collection methodologies should primarily focus on layers related to environmental activities, such as soil type, hydrology and land use. The following is an example of datasets that contribute to an effective basemap used in the field of solid waste management:

Spatial Data

Type

Geometry

Road Network

Vector

Line

Administrative Boundaries

Vector

Polygon

Soils

Vector

Polygon

Hydrology

Vector

Point/Line/Polygon

Demographics (Census Data)

Vector

Polygon

Building Footprints

Vector

Polygon

Pedestrian Routes

Vector

Line

Mass Transit Data (Train Lines /Stations)

Vector

Line/Point

Land use

Vector

Polygon

Aerial Photo/Satellite imagery

Raster

Polygon

Spot Elevation/Contour/Digital Elevation Model

Vector/Raster

Polygon

Solid Waste Asset Data

Solid waste asset data relate to waste facilities and utilities used for collecting, transferring and storing solid waste. Data are usually obtained from municipalities or solid waste contractors. Besides collecting the spatial location of these assets, gathering and documenting volumes, capacities and compacting abilities of the storage facilities also are essential. A complete inventory of solid waste assets and facilities facilitates planning and estimating for waste generation studies. The following is an example of typical, domain-specific solid waste datasets:

Spatial Data

Type

Geometry

Landfill Location

Vector

Polygon/Point

Transfer Station

Vector

Point

Underground Compactors

Vector

Point/Polygon

Ground Compactors

Vector

Point/Polygon

Waste Containers (Bins)

Vector

Point

Material Recovery Facility

Vector

Point/Polygon

Waste Generation and Characteristics

According to the California Department of Resources Recycling and Recover (CalRecycle), solid waste generation rates estimate the amount of waste created by residences, businesses and large events (e.g. severe weather or seismic occurrences) over a certain amount of time (e.g, a day or year). Waste generation includes all discarded materials, whether or not these materials are later recycled or disposed in a landfill. Waste generation rates for residential and commercial activities can be used to estimate the impact of new development on the local waste stream, as well as determine the required capacity for storage and/or permanent disposal sites.

The amount of waste generation depends on the size of a resident population and workforce, the number of visitors or tourists (especially relevant in the case of large crowds during a major sporting event), and socio-economic factors. According to the World Bank Waste Generation Report (2012), the waste generation rate per person ranges between 1.2 to 1.4 kilograms/day. Each municipality or event organizer normally conducts a waste generation study to arrive at a rate that helps estimate the total volume and weight of solid waste.

Another important dataset to collect as part of solid waste management involves waste characterization, where a waste analysis determines the composition of anticipated solid waste. Solid waste streams could include portions of plastic, paper and cardboard, organics, metal or glass. Each component requires different handling requirements, processing needs and opportunities for recycling. Waste characterization is fundamental to selecting, designing and implementing a successful waste management solution for each of the waste components.

Coding Assets Data and Using RFID for Geo-Referencing

Assets are the core of solid waste management operations. As part of creating a solid waste spatial asset inventory, each asset is given a unique identifier to help link its spatial location and tabular attributions such as capacity, compacting ability and tonnage capacity.

Figure 1. Example of coding the location of solid waste (SW) assets

After coding the solid waste assets, a radio-frequency identification (RFID) tag can be mounted on each asset. The RFID tag allows sensors to detect the movement of a specific mobile asset in close proximity to a sensor, or allows the transmission of asset characteristics to a retrieval device or system monitoring the state of that asset. In the first case, the RFID tag may be attached to a waste container that, when full, is transported to a disposal location. In the second instance, the RFID tag may be attached to a compactor and relays a signal to the management system when the compactor becomes full. In both occurrences, the RFID tag is relaying position information along with other attributes of the asset on which it is mounted.

Integrated Approach

Integration of multiple solution components is critical in order to best manage solid waste operations. Each component listed below plays a specific role to achieve solid waste management solutions.

Spatial Database

A spatial database is the core of a spatial solid waste management solution. As discussed, data collected for solid waste management (such as the basemap and assets) are stored in a solid waste spatial database. The database also can be updated using a live feed from field operations and solid waste incidents (e.g., waste accumulation metrics from a particular site) can be reported immediately using database triggers and advance communication protocols  embedded within the spatial database.

Figure 2. A comprehensive GIS solution for SW management (Click for larger image)

Field Operations

Additionally, field operations including solid waste collection can be monitored and managed through the use of spatial technology to realize operational efficiencies. There have been several success stories using RFID tags mounted on assets and read by transfer trucks operating in the field. When equipped with a global positioning system (GPS) device and wireless Internet connectivity these vehicles collect and transfer data to a central operation station. Three pieces of information can be collected by the transferring truck for each served facility and transmitted wirelessly to the central operation station, including:

  • Solid waste collection location (latitude and longitude)
  • Collection time
  • Weight and volume of waste

The integration of communication technology (Internet connectivity) with RFID and GPS for location identification can serve as the base for solid waste monitoring systems and connect to the bigger picture of solid waste management. Data collected at transfer stations and landfills for solid waste tonnage measures and characteristics should be collected manually or through wireless, electronic transmission of metrics to the enterprise management solution.

Dashboard View

Using dashboards to produce a common operational picture for solid waste operations enables operation managers to be spatially aware of the on-the- ground status of solid waste assets and metrics at a strategic level. For example, a spatially enabled dashboard can monitor the performance of solid waste compactors located near a solid waste supervisor. Using the dashboard, the manager is able to see filled compactors, predict the next compaction cycle time, plan the collection schedule and secure required operational resources.

Sold Waste and Spatial Analysis

Adding the spatial component to solid waste operations helps to optimize mounting, collecting and processing operations. Such analysis can assist in identifying waste characteristics (such as food, paper, plastic or metal) for each zone of data collection and ensure appropriate asset assignment for each zone in addition the best processing plans. In turn, this allows planners and managers to identify and address inefficiencies in operations.

Advanced routing using spatial analysis techniques optimizes collection routes. GPS-enabled devices mounted in the cab of collection vehicles allow drivers to follow the optimized routes displayed on their electronic maps. Advanced spatial analysis also can be used to determine asset positions based on optimal distribution. For example, operational analysis is used for site selection of solid waste compactors, transfer stations and landfills based on spatial criteria such as area soil type and accessibility.

Conclusion

GIS serves as a powerful tool for managing solid waste management operations by playing an essential role in solid waste data collection and by providing field operations support with spatially enabled dashboards and in-vehicle capabilities. GIS analytical capabilities greatly enhance solid waste operation planning by defining the best collection routes and approach to solid waste asset maintenance and operation. Although often overlooked in the GIS context, proper and efficient management of solid waste is imperative to maintain healthy, environmentally responsible communities.

References

  • Christos Chalkias and Katia Lasaridi (2011). “Benefits from GIS Based Modeling for Municipal Solid Waste Management, Integrated Waste Management.”
  • Nikolaos V. Karadimas, Vassili G. Loumos (2008). “GIS-based modelling for the estimation of municipal solid waste generation and collection.”
  • Maher Arebey, M. A. Hannan, Hassan Basri, R. A. Begum and Huda Abdullah (2010). “RFID and Integrated Technologies for Solid Waste Bin Monitoring System.”
  • The World Bank (2012). “WHAT A WASTE, A Global Review of Solid Waste Management.”
  • California's Department of Resources Recycling and Recovery (CalRecycle - http://www.calrecycle.ca.gov/)

Published Monday, October 13th, 2014

Written by Hany A. Hassaballa



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