La commune de San Juan de la Costa (province d’Osorno – 10^ème Région de Los Lagos) connaît depuis la fin des années 1980 une expansion remarquable des plantations de pins et d’eucalyptus. Ces boisements sont à l’origine de nombreuses perturbations environnementales mais aussi sociales dans une région considérée comme un hotspot de biodiversité. Si les processus de changement d’occupation et d’utilisation du sol (lucc) sont dans l’ensemble bien connus, les zones de forêts natives susceptibles d’être converties en plantations industrielles sont quant à elles inconnues. Cet article se focalise sur la validation spatiale de deux modèles de simulation afin de proposer des interprétations prospectives en se basant sur une approche supervisée (chaînes de Markov couplées à une évaluation multicritère) et une approche automatique (réseau neuronal multicouches). Les deux modèles intègrent la connaissance des dynamiques passées grâce à l’analyse diachronique de trois images satellites landsat (1986-1999-2008).

Usually risk assessment falls within the competence of “hard sciences” through environmental and epidemiological measurements, evaluations, and modeling. Even if these approaches bring accurate assessment and evaluation of environmental processes, the perception of local inhabitants is often excluded or at least relegated to second place. Evaluation of human vulnerabilities and capacities to face such hazards requires us to understand the perceptions of the population exposed. Three case studies (Lao, Tunisia, and Ecuador) are presented where we applied a perception-based regional mapping, a mapping tool based on local perceptions, for assessing the connection between land uses and health issues. A selection of the results collected on these three study areas show that the perception of local inhabitants provides a good spatial representation of the different contaminations observed locally, with a good consistency with external data. It also indicates for a certain number of cases that the contamination extends far beyond the simulated radius and impacts peripheral areas. Beyond the analysis of such a method (methodological bias, spatial representation bias, etc.), the objective is to combine our results with epidemiological measurement.

The Ituri-Epulu-Aru landscape (IEAL) is experiencing deforestation and forest degradation. This deforestation is at the root of many environmental disturbances in a region characterized by endemism in biodiversity. The importance of this article is to provide useful information for those who wish to discuss a model that can be replicated for other territories affected by deforestation and changes in natural and anthropogenic forest structure. This article focuses on the triangulation of spatialized prospective scenarios in order to identify future trajectories based on the knowledge of historical dynamics through the diachronic analysis of three satellite images (2003–2010–2014–2016). The scenarios were designed in a supervised model implemented in the DINAMICA EGO platform. The three scenarios: business as-usual (BAU), rapid economic growth (REG) and sustainable management of the environment (SME), extrapolating current trends, show that by 2061 this landscape will always be dominated forests (+84%). Old-growth forests occupy 74.2% of the landscape area in the BAU scenario, 81.4% in the SEM scenario and 61.2% in the REG scenario. The SEM scenario gives hope that restoration and preservation of biodiversity priority habitats is still possible if policy makers become aware of it.