Using two GEOBIA (Geographical Object Based Image Analysis) algorithms on a set of segmented images compared to grid partitioning at different scales, we show that statistical metrics related to both objects and sets of pixels are (more or less) subject to the Modifiable Areal Unit Problem. Subsequently, even in a same spatial partition, there may be a bias in statistics describing the objects due to some size effect of the pixel samples. For instance, pixels homogeneity based on Grey Level Cooccurrence Matrices (GLCM), Landscape Shape Index, entropy, object compacity, perimeter/area ratio are studied according to scale. The approach consists in studying the behavior of a given statistical metrics through scales and to compare the results on several image segmentations, according to different partitioning processes, from GEOBIA (Baatz & Schäpe algorithm and Self Organizing Maps) or using reference grids. We finally discuss about the relationship between GEOBIA metrics and scale. By analysing object shape and pixels composition from different metrics points of views, we show that GEOBIA does not always mitigate the Modifiable Areal Unit Problem.

La question de l'élargissement de l’Union Européenne (UE) à l'Est et plus précisément l'intégration commerciale des Pays d'Europe Centrale et Orientale (PECO) se pose actuellement avec acuité. En effet, les transformations de l'environnement économique et géopolitique conduisent l'UE à redéfinir ses relations tant avec les Pays Tiers Méditerranéens (PTM) qu'avec les « exclus » des Pays d'Europe Centrale et Orientale (PECO). Plus particulièrement les pays du Maghreb et la Turquie, qui ont les économies les plus dépendantes de l'Europe et pour lesquels leurs avantages comparatifs sont les plus proches des PECO, courent un risque d'éviction.

Foodshed approaches allow for the assessment of the theoretical food self-sufficiency capacity of a specific region based on biophysical conditions. Recent analyses show that the focus needs to be shifted from foodshed size portrayed as an isotropic circle to a commodity–group-specific spatial configuration of the foodshed that takes into account the socio-economic and biophysical conditions essential to the development of local food supply chains. We focused on a specific animal product (beef) and used an innovative modeling approach based on spatial analysis to detect the areas of the foodshed dedicated to beef feeding (forage, pasture, and grassland), considering the foodshed as a complex of complementary areas called an archipelago. We used available statistical data including a census to address the city-region of Avignon, France covering a 100 km radius. Our results showed that the factors driving the use of short supply chains for beef feeding areas are the foodshed archipelago’s number of patches, the connectivity between them, and the rugosity of the boundaries. In addition, our beef self-sufficiency assessment results differ depending on geographical context. For instance, being located within the perimeters of a nature park seems to help orient beef production toward short supply chains. We discuss possible leverage for public action to reconnect beef production areas to consumption areas (the city) via short supply chains (e.g., green, home-grown school food programs) to increase local food security through increased local food self-sufficiency.