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We are excited to share that the South Dakota Agricultural Freight Data Improvement Study is now available! Please click on the report cover to download the final version. For your convenience, below please find the Executive Summary. 

Historical trends of traffic and truck counts have been the primary means used by the South Dakota Department of Transportation (SDDOT) to forecast traffic volumes necessary for planning roadway improvements and maintenance. However, historical trends do not reflect the rapid changes in agricultural production and the resulting transportation activity in the State. To better explain agricultural freight demand, predict impacts on transportation systems, and improve policy and transportation investment decisions, this research developed a methodology to integrate new sources of data beyond conventional, historical traffic counts to make more reliable decisions and to improve transportation system performance. 

The key findings of this study include:  


    Among SDDOT, local agencies and private entities, nine different agricultural freight related purposes and applications of improved data were identified that can be utilized for planning purposes over a horizon ranging from days to months, seasons, and years. 


    South Dakota agencies make limited use of available USDA data along with forecasts and data compiled by agricultural associations to support transportation system decision‐making, mostly on the state‐ owned rail system. Innovative data collection methods such as Unmanned Aerial Vehicles (UAVs) and smartphones offer significant promise for to cost‐effective means to filling large gaps in data on local roadway traffic counts and surface condition. At present, privacy and cost of other data sources such as producer production records and remotely sensed data inhibit their widespread use by SDDOT. 


    The demonstration developed a compendium of conventional and “unconventional” agricultural freight data related to major crops and livestock facilities. The demonstration included trip generation estimates for four major crop types and two types of livestock facilities, and testing of various planning scenarios, including facility siting and public roadway closures. 

The research recommended that SDDOT should: (1) actively monitor agricultural and transportation industry trends; (2) incorporate available agricultural resources including knowledge of agricultural production and agricultural and transportation industry trends into short‐ and long‐term transportation decision‐making; and, (3) lead new data development efforts in partnership with regional and local transportation agencies.