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Forest is a resource that is increasingly utilized for multiple purposes. The balance between energy demands and the long-term capacity of ecosystems to support biodiversity and other ecosystem services is crucial. The aim of this project was to increase the knowledge on and to develop methods and tools for trade-offs and synergies analysis among forest ecosystem services based on different forest management policies. Paper I provides an overview of existing models for integrated energy-environment assessment. A literature review was conducted on assessment models and their ability to integrate energy with environmental aspects. Missing environmental aspects concern land use, landscapes and biodiversity. In Paper II a modelling framework was set up to link a landscape simulator with a habitat network model for integrated assessment of bioenergy feedstock and biodiversity related impacts in Kronoberg County. In Paper III we continued with the same management scenarios, while the analysis was expanded to five ecosystem services by developing the Landscape simulation and Ecological Assessment (LEcA) tool: industrial wood, bioenergy, forest carbon stock, recreation areas and habitat networks. In Paper IV we present two heuristic methods for spatial optimization – simulated annealing (SA) and genetic algorithm (GA) – to find optimal solutions for allocating harvest activities, in order to minimize the impacts on habitat networks. In Paper V, as response to the findings in Paper I, we linked the energy model MESSAGE with our LEcA tool for forest bioenergy demand assessment while applying environmental and transport restrictions, in a study of Lithuania. We found trade-offs between industrial wood production and bioenergy on one side, and recreation values, biodiversity, and to some extent carbon storage on the other side. The LEcA tool integrated forest simulation and management with assessment of ecosystem services, which is promising for integrated sustainability assessment of forest management policies. / <p>QC 20171023</p>

De nos jours, les informations liées au déplacement et à la mobilité dans un réseau de transport représentent sans aucun doute un potentiel important.Ces travaux visent à mettre en œuvre un Système d’Information de Service d’Aide à la Mobilité Urbaine (SISAMU).Le SISAMU doit pouvoir procéder par des processus de décomposition des requêtes simultanées en un ensemble de tâches indépendantes. Chaque tâche correspond à un service qui peut être proposé par plusieurs fournisseurs d’information en concurrence, avec différents coûts, temps de réponse et formats. Le SISAMU est lié à un Réseau informatique Etendu et distribué de Transport Multimodal (RETM) qui comporte plusieurs sources d’information hétérogènes des différents services proposés aux utilisateurs de transport. L’aspect dynamique, distribué et ouvert du problème, nous a conduits à adopter une modélisation multi-agent pour assurer au système une évolution continue et une flexibilité pragmatique. Pour ce faire, nous avons proposé d’automatiser la modélisation des services en utilisant la notion d’ontologie. Notre SISAMU prend en considération les éventuelles perturbations sur le RETM.Ansi, nous avons créé un protocole de négociation entre les agents. Le protocole de négociation proposé qui utilise l’ontologie de la cartographie se base sur un système de gestion des connaissances pour soutenir l'hétérogénéité sémantique. Nous avons détaillé l’Algorithme de Reconstruction Dynamique des Chemins des Agents (ARDyCA) qui est basé sur l’approche de l’ontologie cartographique. Finalement, les résultats présentés dans cette thèse justifient l’utilisation de l’ontologie flexible et son rôle dans le processus de négociation / Nowadays, information related on displacement and mobility in a transport network represents certainly a significant potential. So, this work aims to modeling, to optimize and to implement an Information System of Services to Aid the Urban Mobility (ISSAUM).The ISSAUM has firstly to decompose each set of simultaneous requests into a set of sub-requests called tasks. Each task corresponds to a service which can be proposed different by several information providers with different. An information provider which aims to propose some services through our ISSAUM has to register its ontology. Indeed, ISSAUM is related to an Extended and distributed Transport Multimodal Network (ETMN) which contains several heterogeneous data sources. The dynamic and distributed aspects of the problem incite us to adopt a multi-agent approach to ensure a continual evolution and a pragmatic flexibility of the system. So, we proposed to automate the modeling of services by using ontology idea. Our ISSAUM takes into account possible disturbance through the ETMN. In order to satisfy user requests, we developed a negotiation protocol between our system agents. The proposed ontology mapping negotiation model based on the knowledge management system for supporting the semantic heterogeneity and it organized as follow: Negotiation Layer (NL), the Semantic Layer (SEL), and the Knowledge Management Systems Layer(KMSL).We detailed also the reassignment process by using Dynamic Reassigned Tasks (DRT) algorithm supporting by ontology mapping approach. Finally, the experimental results presented in this thesis, justify the using of the ontology solution in our system and its role in the negotiation process

Spaceborne Remote Sensing, the observation of the features on ground from orbiting satellites is one of the expanding business areas of international space business, attracting the analysis of the markets and the growth patterns in the international arena. Whatever be the product/service, it is important for the market players to know the market characteristics to draw up marketing strategy and defining marketing mix, which becomes important for Remote Sensing services as well without an exception. The market for Remote Sensing data and services is influenced by a multitude of factors, which may seem unrelated at the outset. These may be Socio-Economic and Natural Resources related variables in addition to the expected product/market related variables. Hence the research work to model the market dynamics is taken up with the objectives of: 1)To identify factors influencing the market potential for Remote Sensing Data services 2)To model the relationship between these factors and the market potential 3)To validate and verify the model developed The analysis was carried out with 82 valid responses from respondents spread across 17 countries where Remote Sensing market is prevailing. A broad spectrum of economic, political, social, natural, and geographic variables believed to be influencing the Remote Sensing requirements were enumerated and validated through pilot study. Raw values for the variables were obtained from secondary sources and relative importance of these variables was determined through primary survey. The variables were synthesised into factors and captured into a regression model to arrive at the market potential index. This is statistically validated and also verified with market potential of a known country market, India. The analysis and results revealed that, market dynamics influencing market potential for Spaceborne Remote Sensing Data can be synthesised as the following three factors, explaining 80% of the variance in the market potential. (i)Politico Developmental factor-variables border related (Number of border countries, Border length, level of Border Disputes, Energy Production & Consumption, Economy and Information & Communication Infrastructure) (ii)Geo-Natural factor: represented by extent of Natural Resources, Energy Reserves etc. (iii)Market/Product related factor variables like product features, level of competition, availability of substitutes, current market position, and growth rate etc. The emergence of variables representing the developmental aspects on one side and political aspects on the other, as important factor is the outcome formally brought to recognition by the study. This is manifesting the growing importance of developmental activities and theatres of war as important additional market drivers in high and very-high resolution data services across the globe, in addition to the traditional applications like natural resources monitoring and management.