Transport cost to port though Brazilian federal roads network: Dataset for years 2000, 2005, 2010 and 2017
Daniel de Castro Victoria,
Ramon Felipe Bicudo da Silva,
James D.A. Millington,
Valeri Katerinchuk,
Mateus Batistella
Affiliations
Daniel de Castro Victoria
Embrapa Agricultural Informatics. Brazilian Agricultural Research Corporation (EMBRAPA). Avenida Andre Tosello 209 Campus da Unicamp Barão Geraldo. PO Box 6041 - 13083-886 Campinas, São Paulo, Brazil; Corresponding author.
Ramon Felipe Bicudo da Silva
Center for Systems Integration and Sustainability, Department of Fisheries and Wildlife, Michigan State University. 115 Manly Miles Building 1405 S. Harrison Rd. East Lansing, MI 48823, United States; Center for Environmental Studies and Research, State University of Campinas (NEPAM/UNICAMP), Rua dos Flamboyants, 155 - Cidade Universitária Campinas/SP - CEP: 13.083-867 Campinas, Brazil
James D.A. Millington
Department of Geography, King's College London, Strand, London WC2B 4BG, United Kingdom
Valeri Katerinchuk
Department of Geography, King's College London, Strand, London WC2B 4BG, United Kingdom
Mateus Batistella
Embrapa Agricultural Informatics. Brazilian Agricultural Research Corporation (EMBRAPA). Avenida Andre Tosello 209 Campus da Unicamp Barão Geraldo. PO Box 6041 - 13083-886 Campinas, São Paulo, Brazil; Center for Environmental Studies and Research, State University of Campinas (NEPAM/UNICAMP), Rua dos Flamboyants, 155 - Cidade Universitária Campinas/SP - CEP: 13.083-867 Campinas, Brazil
Transport costs can play a significant role in agricultural exports and businesses profitability. It can also influence farmers’ decisions regarding cropland expansion, intensification or land abandonment. Thus, transport is useful to take into account when modeling and evaluating land use and cover change related to agriculture production. The dataset described in this article represents the Infrastructure Capital in the work presented by Millington et al. (2021) [1], in which the CRAFTY-Brazil model is used to evaluate the impacts of changing global demand for agricultural products on land use and cover change. This modeling required a transport cost dataset that spanned the model calibration period, was consistent through time and covered the entire study area. The most recent federal road network (for year 2017) obtained in vector format (shapefile) was joined to road section surface status tables for past years (2000, 2005 and 2010) in order to reconstruct the historic road network. Export ports handling agricultural commodities, and their years of operation, were identified. Both datasets were used to derive the relative transport cost to the nearest port for Brazil, for years 2000, 2005, 2010 and 2017.
