MPC
Project Details

Title:	Grain Highway Network Analysis: Use of Satellite Imagery and USDA Data to Forecast Heavy Truck Trips Generated from Rural Land Use Zones
Principal Investigators:	Denver Tolliver
University:	North Dakota State University
Status:	Completed
Year:	1999
Project #:	MPC-190

Abstract

The location of new facilities such as agricultural processing plants is significantly altering truck traffic patterns in rural areas. Large processing plants create substantial inbound truck flows that typically are concentrated on several collector or arterial highways. After a facility begins operation, the annual equivalent single axle loads (ESALs) on key access highways may be significantly higher than the design values. This project will build on an existing study (MPC-168). A prototype network model is being developed of a large corn processing plant in southeastern ND. The model will simulate flows of corn based on forecasted supply, demand, and farmer delivery criteria. It will function within a GIS environment (Arcview) and will utilize three main GIS database layers: (1) corn production; (2) elevator capacities and demands, and (3) plant demand and capacity. The model will forecast grain flows from production zones to elevators, satellites, and processing plants; assign the predicted flows to truck types and highways; and estimate the ESALs on key arterial and major collector highways. At the start of MPC168, corn production data were available only at the county level. Now, much better data can be derived. Using satellite images and field data provided by USDA, corn production forecasts will be developed for 1,500 sub-county strata.

In addition to better data, the project will add value to MPC-168 by illustrating how USDA data and NASA satellite images can be used to estimate zonal grain production and forecast the annual truck trips generated from rural land use zones.