Smart agriculture in urban regions.
A transdisciplinary and multilevel approach for implementing and combining quantitative and qualitative methods
Rosalia FILIPPINI *±1,2 – Stefano CORSI 2 – Sylvie LARDON,1,3
1 AgroParisTech, UMR Métafort, Aubière, France
2 DISAA – University of Milano, Italy
3 INRA, UMR Métafort, Aubière, France
± Corresponding author: firstname.lastname@example.org
The concept of Smart Agriculture (SA) has been included in the EU growth strategy Horizon 2020, related to the goals of smart, sustainable and inclusive growth. The strategy highlights these concepts as key objectives and mutually reinforcing priorities to reach the stated policy targets (European Commission, 2010). Despite the attention given, at the moment there is not a unique definition for SA. In literature, as well as in political discourses SA appears as a new term indicating a holistic vision of agricultural potentialities, for raising collective behaviour. This is probably due to the fact that agricultural activity and agricultural science have very wide definitions, since they impact different aspects of the human society. As results, in academic research several different disciplines deal with SA. In the framework of ERA-NET projects “Toward a Smart Rural Europe” , in order to develop a theoretical framework around SA, able to include the different aspects of the concept, a first bibliographic analysis has identified seven main features: Technological issues and agricultural engineering (Opara 2004); Climate change mitigation (Bogdanski, 2012); Landscape and land use (Beuchelt and Badstue, 2013); Social inclusion (Sullivan and al., 2012); Supply and demand (Renting et al., 2003); Multifunctional Agriculture (Wilson, 2008); Public policies (Lo Schiavo et al., 2013). SA is the results of combined effects of seven smart dimensions.
SA shares views with other concepts, such as sustainable agriculture for the common environmental, economic and social goals; agriculture oriented to food security and against climate change; innovative agriculture able to improve its development effects, through issues provided by precision farming, ecological networks, alternative food networks.
The analysis of SA needs a transdisciplinary and multilevel approach in order to:
- involve different actors both institutional and private,
- catch at the same time macro and micro phenomena,
- provide effective policy framework and governance,
- promote the participation of civil society by means of education and gaming.
The present work faces two hypotheses. First, qualitative and quantitative methods are at disposition at the different territorial scales, and so it is possible to operate a joint of the different territorial scales, through processes of up-scaling and downscaling. Second, multi-level analysis is requested by several conceptual models, but there’s a lack of some integrating element able to combine together the different territorial scales and the different approaches.
The aim of this analysis is to design a transdisciplinary and multilevel approach for implementing and combining quantitative and qualitative methods in order to build a common framework for local and global stakeholder. The study will be applied on the case studies of Milan and Pisa in order to formalize the results expected from the full implementation of the multi-level model.
Materials and Methods
The present work aims at combining and implementing different analytical models for measuring SA in two Italian case studies. The first method is the Smart Agriculture Index (SAI), a composite index including the seven dimensions of SA, which can be implemented at different scales. In the present work the analysis of the case studies is developed at municipal level, and data come from national agricultural census. Based on a quantitative analysis, SAI provides a very interesting, and flexible description of territory showing the smartest areas and the comparison between different SA dimensions. The second method is the collection of the several different local projects concerning SA dimensions. Projects have been selected and analyzed since their aim was the inclusion of agriculture in the urban and territorial dynamic. The qualitative approach was mainly based on direct interviews to the actors involved carried out on a sample. The bridge between the two methods is the use of the same Smart Agriculture Grid, which includes the seven dimensions of SA. In this way the method provides a guideline for a combined approach of quantitative and qualitative analysis and different territorial scales.
Results and Discussion
The expected results are:
- An experimental protocol to test the methodology on full concrete cases as Milan and Pisa
- A critical analysis of the used methods, their combination, the identification of the methodological locks and the analysis on the ability of the transdisciplinary approach to identify and describe actual complex territorial phenomena
- The acquisition of transdisciplinary knowledge on results, both methodological (i.e. tools for socio-spatial configuration, statistical treatment of municipal data, etc…), and thematic (i.e. territorial dynamics, modes of action, public policy evaluation)
- The definition of innovative participation models.
The combination of economic, geographic and agronomic approaches, benefits to a renovation on the way we analyze the territorial dynamics, also providing new knowledge on the case studies. It also provides a theoretical and methodological framework to evaluate the public policies and design recommendation for regional policy makers. Finally, the action perspective provides a final purpose to the analysis: this is possible through intermediate objects that have meaning for actors and integrates the different dimensions of the complex system studied.
Beuchelt, T. (2013). Gender, nutrition and climate-smart food production: Opportunities and trade-offs. Food Security 5 (5): 709-721.
Bogdanski, A. (2012). Integrated food-energy systems for climate-smart agriculture. Agriculture and Food Security 1-9.
European Commission (2010). Europe 2020 – A strategy for smart, sustainable and inclusive growth. Communication from the commission. Brussels, European Commission
Lo Schiavo, L., Delfanti, M., Fumagalli, E., Olivieri, V. (2013). Changing the regulation for regulating the change: Innovation-driven regulatory developments for smart grids, smart metering and e-mobility in Italy. Energy Policy 57: 506-517.
Opara, L.U. (2004). Emerging technological innovation triad for smart agriculture in the 21st century.Part I. Prospects and impacts of nanotechnology in agriculture. International Commission of Agricultural Engineering.
Renting, H., Marsden, T. and J. Banks (2003). Understanding Alternative Food Networks: Exploring the Role of Short Food Supply Chains in Rural Development. Environment and Planning A 35: 393-411.
Sullivan, A. (2012). Climate Smart Agriculture: More Than Technologies Are Needed to Move Smallholder Farmers Toward Resilient and Sustainable Livelihoods. FANRPAN Policy Brief 2, XIII. Pretoria, South Africa: FANRPAN.