French wine: Combination of multiple open data sources to mapping the expected harvest value
Martial Ph\'elipp\'e-Guinvarc'h (GAINS, UM)

TL;DR
This paper develops a detailed, spatially explicit map of expected wine harvest values by integrating multiple open data sources and optimization techniques to address data heterogeneity and support risk assessment in the wine industry.
Contribution
It introduces a novel method combining open data sources and optimization to estimate detailed harvest values at a fine spatial scale.
Findings
Created a detailed spatial map of harvest values
Demonstrated the effectiveness of data integration and optimization methods
Facilitated risk assessment and decision-making for wine producers
Abstract
The purpose of this paper is to estimate a representative and detailed map of the harvest value in wine using structured and unstructured open data sources. With climate change and new environmental and ecological policies, wine producers are facing new challenges. The ability to model the evolution of these risks is strategic for wine producers and research in order to adapt. Many research projects require the values exposed to risk. For example, to assess the economic impact of risks or the premium of crop insurance, or to choose between different agroecological solutions in a cost-benefit approach. The high spatial heterogeneity and complexity of wine characteristics add to the challenge of these production values and the need to improve our spatial assessment of these harvest-expected values.Structured, exhaustive and detailed historical data are collected by the customs services,…
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Taxonomy
TopicsHorticultural and Viticultural Research · Wine Industry and Tourism · Fermentation and Sensory Analysis
