Abstract
AbstractInk disease of sweet chestnut (Castanea sativa) caused by the oomycetes Phytophthora cinnamomi and P. x cambivora is the limiting factor for chestnut cultivation in several European regions. The objective of this study was to explore how the spatial landscape heterogeneity affects the distribution pattern of ink disease over a large chestnut area in Central Italy using an approach that combined remote sensing, ground truthing activities and GIS. A multivariate model was developed that explained a large proportion of the variance of the impact of the disease using the density of roads and drainage networks as predictor variables. The association of these landscape elements, specifically with ink disease foci, also provides practical tool to improve the accuracy of monitoring of this disease and the preparation of risk maps.
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