Assessment of Motorway Impact on Agricultural Land with a Simplified Method and GIS Data as a Tool for Selecting the Optimal Route

Stanisław Bacior (), Krzysztof Chmielowski and Barbara Prus
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Stanisław Bacior: Department of Geodesy, Cadastre and Photogrammetry, Faculty of Environmental Engineering and Geodesy, University of Agriculture in Krakow, Balicka Str. 253A, 30-198 Kraków, Poland
Krzysztof Chmielowski: Department of Sanitary Engineering and Water Management, Faculty of Environmental Engineering and Geodesy, University of Agriculture in Krakow, Mickiewicza Ave. 24/28, 30-059 Kraków, Poland
Barbara Prus: Department of Land Management and Landscape Architecture, Faculty of Environmental Engineering and Geodesy, University of Agriculture in Krakow, Balicka Str. 253C, 30-198 Kraków, Poland

Sustainability, 2022, vol. 14, issue 24, 1-13

Abstract: The highway network has to grow because of the increasing vehicle use, the effort to improve road safety, and the needs generated by economic development and efficient international transport. The negative impact of the motorway on agricultural holdings in its vicinity can be determined with general agricultural land valuation methods. However, this approach necessitates an in-depth analysis of land cultivated by each farm, which is rather labour-intensive. Impact on agricultural land should be assessed after the detailed plans for constructing a motorway are ready or even after construction. Nevertheless, simplified methods can be applied as early as the preliminary design stage or when evaluating potential alternative routes. Less labour-intensive, these methods can determine the harmful impact of a motorway on agricultural land with sufficient accuracy. The simplified and automated method presented for assessing the impact of a motorway on agricultural land uses GML files to automatically acquire data for the calculations, using the linear nature of the motorway. The prepared input data is then processed to optimally place the motorway in space. The final step is the visualisation of the road investment. The process has been automated to facilitate rapid analysis and employment of the data in linear project modelling and assessments of available options.

Keywords: rural areas; road network optimisation; sustainable transport; data automation; calculation process (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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