Une méthode d’étude synthétique du paysage

The use of multivariate statistics to correlate chemical data to spectral information seems as a valid alternative for the quantification of red wine phenolics. The advantages of these techniques include simplicity and cost effectiveness together with the limited time of analysis required. Although many
publications on this subject are nowadays available in the literature most of them only reported feasibility
studies. In this study 400 samples from thirteen fermentations including five different cultivars plus 150
wine samples from a varying number of vintages were submitted to spectrophotometric and chromatographic phenolic analysis.

The zoning of grapevine in a hilly area should consider the variability of the environmental characteristics due to topography. Since soil and climate data are usually available as point data

The way to manage the vineyard soils has certainly changed in Spain during the last years. Traditionally, the vineyards were tilled, but this growing technique has been replaced in some vineyards by the bare soil with herbicide

Infection of the grapes with Botrytis cinerea has a tremendous impact on the resulting crop yield and quality. Well-known problems that are associated with B. cinerea are specific off-flavors, poor filterability, and brownish color in white wines. The development of a B. cinerea infection strongly depends on weather conditions and is highly variable through different vintages. Typical control measures include defoliation and the use of fungicides, which involves high personnel and material costs. They also involve a great risk, especially since the effectiveness and time point of these treatments are difficult to predict.

In viticulture, the challenges of local climate modelling are multiple: taking into account the local environment, fine temporal and spatial scales, reliable time series of climate data, ease of implementation and reproducibility of the method. At the local scale, recent studies have demonstrated the contribution of spatialization methods for ground-based climate observation data considering topographic factors such as altitude, slope, aspect, and geographic coordinates (Le Roux et al, 2017; De Rességuier et al, 2020). However, these studies have shown questions in terms of the reproducibility and sustainability of this type of climate study. In this context, we evaluated the potential of MODIS thermal satellite images validated with ground-based climate data (Morin et al, 2020). Previous studies have been encouraging, but questions remain to be explored at the regional scale, particularly in the dynamics of the massive use of bioclimatic indices to classify the climate of wine regions. The results at the local scale were encouraging, but this approach was tested in the current study at the regional scale. Several objectives were set: 1) to evaluate the downscaling method for land surface temperature time series, 2) to identify regional thermal structure variations. We used weekly minimum and maximum surface temperature time series acquired by MODIS satellites at a spatial resolution of 1000 m and downscaled at 500 m using topographical variables. Two types of analyses were performed: