The development of spatio–temporal geoscience information systems (TGSIS) as the next generation of geographic information systems (GIS) and geoscience information systems (GSIS) was investigated with respect to the following four aspects: concepts, data models, software, and applications. These systems are capable of capturing, storing, managing, and querying data of geo–objects subject to dynamic processes, thereby causing the evolution of their geometry, topology and geoscience properties. In this study, five data models were proposed. The first data model represents static geo–objects whose geometries are in the 3–dimensional space. The second and third data models represent geological surfaces evolving in a discrete and continuous manner, respectively. The fourth data model is a general model that represents geo–objects whose geometries are n–dimensional embedding in the m–dimensional space R^m, m >= 3. The topology and the properties of these geo–objects are also represented in the data model. In this model, time is represented as one dimension (valid time). Moreover, the valid time is an independent variable, whereas geometry, topology, and the properties are dependent (on time) variables. The fifth data model represents multiple indexed geoscience data in which time and other non–spatial dimensions are interpreted as larger spatial dimensions. To capture data in space and time, morphological interpolation methods were reviewed, and a new morphological interpolation method was proposed to model geological surfaces evolving continuously in a time interval. This algorithm is based on parameterisation techniques to locate the cross–reference and then compute the trajectories complying with geometrical constraints. In addition, the long transaction feature was studied, and the data schema, functions, triggers, and views were proposed to implement the long transaction feature and the database versioning in PostgreSQL. To implement database versioning tailored to geoscience applications, an algorithm comparing two triangulated meshes was also proposed. Therefore, TGSIS enable geologists to manage different versions of geoscience data for different geological paradigms, data, and authors. Finally, a prototype software system was built. This system uses the client/server architecture in which the server side uses the PostgreSQL database management system and the client side uses the gOcad geomodeling system. The system was also applied to certain sample applications.

Paysages emblématiques des campagnes de l’Ouest, les bocages ont connu une série de transformations rapides et importantes ces quarante dernières années : érosion du linéaire de haies, changements des usages du sol, rationalisation et agrandissement du parcellaire, banalisation et massification des bâtiments agricoles, enfrichement des secteurs les plus difficiles à exploiter. L’ampleur des ajustements observés souligne le décalage entre ces formes paysagères héritées d’une longue histoire agraire, et l’évolution des systèmes agricoles qui contribuent à les produire.Si la transformation des paysages de bocage est généralement attribuée au tournant « productiviste » du modèle agricole français, les processus socio-techniques à l’origine de ces évolutions sont plus rarement explicités. L’objet de ce travail est d’évaluer plus spécifiquement la contribution de l’agrandissement des exploitations agricoles à la dynamique d’évolution des paysages bocagers de l’Ouest de la France.Ce travail de géographie s’appuie dans un premier temps sur une analyse statistique à l’échelle du grand Ouest de la France, visant à étudier l’effet des transformations foncières sur les structures spatiales agricoles (assolements, parcellaire, linéaires boisés…). Dans un second temps, les dynamiques paysagères et foncières de quatre espaces d’étude (Bessin, Bocage Virois, Sud Manche, Pays d’Auge), situés en domaine laitier et bocager mais présentant des configurations agricoles variées, ont été étudiées entre 2003 et 2016. Ce travail s’appuie notamment sur un dispositif méthodologique original, articulant au sein d’un système d’information géographique à échelle parcellaire (1) la construction d’un suivi à échelle spatio-temporelle fine des dynamiques paysagères (évolution du maillage bocager, de la trame parcellaire et de l’occupation du sol) et (2) la reconstitution de l’évolution de la mosaïque des parcellaires d’exploitations par appariement de plusieurs millésimes du registre parcellaire graphique. L’exploitation de cette base de données spatio-temporelle a permis de mieux comprendre le rôle de la transformation foncière des exploitations agricoles dans la dynamique des paysages bocagers. Enfin, une enquête de terrain a été réalisée auprès de 150 agriculteurs équitablement répartis dans les quatre espaces d’étude, afin d’appréhender les conséquences sociales, techniques et productives de l’agrandissement à l’échelle des exploitations agricoles, qui diffèrent singulièrement selon le type de trajectoire foncière suivie. / Symbolic landscapes of the countryside of the West of France, the bocage landscapes have undergone a series of transformations these last forty years : decrease in hedgerow density, land uses changes, plots extension, normalization and enlargement of farm buildings, spatial extension of wilderness… The intensity of landscape transformations highlights the contradiction between these landscape forms produced by a long agrarian history and the contemporary evolutions of farming systems. The transformation of hedgerow landscapes is generally attributed to the "productivist" turn of the French agricultural model. However, the socio-technical processes behind these changes are more rarely explained.The first purpose of this geography work is to study the effects of changing agricultural systems on agricultural spatial structures, based on a statistical analysis at the scale of the West of France. In a second step, the landscape and land dynamics of four study areas (Bessin, Bocage Virois, Sud Manche, Pays d'Auge), located in the dairy and bocage domain, have been studied between 2003 and 2016. This work is based on an original methodological device, set up in a geographical information system. This structuration of geographic information makes possible to (1) monitor the landscape dynamics (evolution of the hedgerow density, land cover and plot morphology changes) at a fine spatial and temporal scale and (2) to reconstruct the evolution of the mosaic of farm plots, by matching land-parcell identification systems across the time (2007, 2011, 2013). From this spatio-temporal database, we characterized the coevolution of landscape structures and farm territories across the time, in order to better understand the landscape consequences of farm enlargment.Finally, a field survey was carried out among 150 farmers equitably distributed in the four study areas, in order to apprehend the social, technical and productive consequences of the farms enlargment, which differ singularly according to the type of land trajectory followed.

The development of spatio–temporal geoscience information systems (TGSIS) as the next generation of geographic information systems (GIS) and geoscience information systems (GSIS) was investigated with respect to the following four aspects: concepts, data models, software, and applications. These systems are capable of capturing, storing, managing, and querying data of geo–objects subject to dynamic processes, thereby causing the evolution of their geometry, topology and geoscience properties. In this study, five data models were proposed. The first data model represents static geo–objects whose geometries are in the 3–dimensional space. The second and third data models represent geological surfaces evolving in a discrete and continuous manner, respectively. The fourth data model is a general model that represents geo–objects whose geometries are n–dimensional embedding in the m–dimensional space R^m, m >= 3. The topology and the properties of these geo–objects are also represented in the data model. In this model, time is represented as one dimension (valid time). Moreover, the valid time is an independent variable, whereas geometry, topology, and the properties are dependent (on time) variables. The fifth data model represents multiple indexed geoscience data in which time and other non–spatial dimensions are interpreted as larger spatial dimensions. To capture data in space and time, morphological interpolation methods were reviewed, and a new morphological interpolation method was proposed to model geological surfaces evolving continuously in a time interval. This algorithm is based on parameterisation techniques to locate the cross–reference and then compute the trajectories complying with geometrical constraints. In addition, the long transaction feature was studied, and the data schema, functions, triggers, and views were proposed to implement the long transaction feature and the database versioning in PostgreSQL. To implement database versioning tailored to geoscience applications, an algorithm comparing two triangulated meshes was also proposed. Therefore, TGSIS enable geologists to manage different versions of geoscience data for different geological paradigms, data, and authors. Finally, a prototype software system was built. This system uses the client/server architecture in which the server side uses the PostgreSQL database management system and the client side uses the gOcad geomodeling system. The system was also applied to certain sample applications.