Academia de Studii Economice Bucuresti

Amfiteatru Economic
AN ECONOMIC AND BUSINESS RESEARCH PERIODICAL
Facultatea de Business si Turism

Urban Agriculture Digital Planning for the European Union’s Green Deal

Author:Ana M. Bartolome, Deiyalí A. Carpio și Beatriz Urbano

JEL:R11, R14, R52

DOI:10.24818/EA/2022/59/159

Keywords:Potential urban agriculture, land use, binary logistic regression, citizens’ well-being, city climate change adaptation, societal demand.

Abstract:
Urban agriculture is a nature-based solution recommended for the regeneration and adaptation of urban areas to climate change, in consonance with the European Green Deal. Nevertheless, for the development of urban agriculture, the availability, access and usability of cultivable land in urban areas is of particular concern. This study aimed to use the digital agricultural data geographic information system AGRO-GIS to calculate and predict potential urban agriculture from abandoned horticultural lands and greenhouses in urban areas. In doing so, the variation of agrarian land in urban areas was calculated. A binary logistic regression modelled abandoned horticultural land and greenhouses in urban areas to obtain the determinant factors for potential urban agriculture. Then, an analysis of variance (ANOVA) was used to obtain significant differences in the variation of the agrarian land among urban areas. Results show that an average of 97.85 ha of abandoned horticultural land and greenhouses can provide potential urban cultivable land in cities. The variation of non-irrigated lands and grasslands-shrublands are determinant for potential urban agriculture. A hectare decrease in non-irrigated lands is associated with an 87.98% increase in the odds of potential urban agriculture. An increase of a hectare of grasslands-shrublands increases the likelihood of potential urban agriculture by 67.59%. Furthermore, it is concluded that differentiated planning and management of urban agriculture by urban areas is needed. This study can help urban planners to manage, plan and predict cultivable land for urban agriculture.
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