Geospatial analysis for decision support, suitability assessment for value chain infrastructure interventions

This study consists of desk research under the scope of the FAO Hand-in-Hand Initiative (HiHI), an evidence-based, country-led, and country-owned initiative of the Food and Agriculture Organization of the United Nations (FAO) targeting to accelerate agricultural transformation and sustainable rural development with the goal of eradicating poverty, ending hunger and malnutrition, and reducing inequalities. The research follows the Initiative objective to use integrated geospatial analysis and market-oriented agri-food systems lens to differentiate territories and focus action, to identify opportunities to raise the incomes, reduce the inequities and vulnerabilities of rural populations. The analysis deliver suitability assessments aimed at value chain infrastructure interventions for around 60 participating countries, designed for, crops, livestock (dairy/meat), and fish farming. Research methodology include literature review on region, country, and value chain/sector, for background and context, with the suitability modelling adopting geographic Information system (GIS) Multi-criteria Evaluation (MCE) approach using weighted factors, converting, and combining geospatial data and decision criteria. Spatial decision problems involve a set of alternatives and multiple (sometimes opposing) assessment criteria, frequently evaluated by many intervenient. In GIS-MCE, GIS capabilities are enhanced by multi-criteria decision analysis procedures, techniques, and algorithms for structuring decision problems, to design, evaluate and prioritize alternatives. Based on specific theory, geospatial modelling is developed for each farming system within a value chain, playing with criteria combination and weighting, and combining different set of constraints. The business rules define sub-models, the criteria, and spatial constraints, that characterize the socioeconomic (supply, demand, and infrastructure /accessibility) and biophysical factors, that are considered to define a locations suitability. Transportation network infrastructures are modelled as raster-based travel time/cost analysis, and the accessibility to market (demand) is processed for large urban areas, utilizing population size and purchase power as weighting factors. Final recommendation, mapping outputs, on site location, utilizes exclusive criteria or constraints, e.g. distance to major roads, access to information and communication technologies, access to finance. GIS-MCE provides a replicable and auditable model, improving communication between project participants and decision-makers, offering different perspectives on problem solution, and helping to redefine initial specification or criteria. It usually follows a three-stage hierarchy of: intelligence, design, and choice. In the intelligence phase, data are acquired, processed, and exploratory data analysis is performed. The design phase entails the formal modelling and development of a solution set of spatial decision alternatives. The choice phase involves selecting location alternatives using specific decision rules, used to evaluate and rank alternatives. From a critical standpoint it can be stated that, while quantitative data analysis and evidence gathering through GIS modelling can contribute to attaining evidence for decision-making processes, a set of complex socio-economic, political, cultural, ethno-anthropological aspects, and power relations, shape decision-making processes. Modelling is also as good as the input data, quality and reliability support the extent to which conclusions can be trusted, and specification and objectives define modelling assumptions and approximations and can always produce distinct answers.