Modelling geographic phenomena at multiple levels of detail: A model generalisation approach based on aggregation

Considerable interest remains in capturing once geographical information at the fine scale, and from this, automatically deriving information at various levels of detail and scale via the process of map generalisation. This research aims to develop a methodology for transformation of geographic phenomena at a high level of detail directly into geographic phenomena at higher levels of abstraction. Intuitive and meaningful interpretation of geographical phenomena requires their representation at multiple levels of detail. This is due to the scale dependent nature of their properties. Prior to the cartographic portrayal of that information, model generalisation is required in order to derive higher order phenomena typically associated with the smaller scales. This research presents a model generalisation approach able to support the derivation of phenomena typically present at 1:250,000 scale mapping, directly from a large scale topographic database (1:1250/1:2500/1:10,000). Such a transformation involves creation of higher order or composite objects, such as settlement, forest, hills and ranges, from lower order or component objects, such as buildings, trees, streets, and vegetation, in the source database. In order to perform this transformation it is important to model the meaning and relationships among source database objects rather than to consider the object in terms of their geometric primitives (points, lines and polygons). This research focuses on two types of relationships: taxonomic and partonomic. These relationships provide different but complimentary strategies for transformation of source database objects into required target database objects. The proposed methodology highlights the importance of partonomic relations for transformation of spatial databases over large changes in levels of detail. The proposed approach involves identification of these relationships and then utilising these relationships to create higher order objects. The utility of the results obtained, via the implementation of the proposed methodology, is demonstrated using spatial analysis techniques and the creation of ‘links’ between objects at different representations needed for multiple representation databases. The output database can then act as input to cartographic generalisation in order to create maps (digital or paper). The results are evaluated using manually generalised datasets

A process-oriented data model for fuzzy spatial objects

The complexity of the natural environment, its polythetic and dynamic character, requires appropriate new methods to represent it in GISs, if only because in the past there has been a tendency to force reality into sharp and static objects. A more generalized spatio-temporal data model is required to deal with fuzziness and dynamics of objects. This need is the motivation behind the research reported in this thesis. In particular, the objective of this research was to develop a spatio-temporal data model for objects with fuzzy spatial extent.This thesis discusses three aspects related to achieving this objective:identification of fuzzy objects,detection of dynamic changes in fuzzy objects, andrepresentation of objects and their dynamics in a spatio-temporal data model.For the identification of fuzzy objects, a six-step procedure was proposed to extract objects from field observation data: sampling, interpolation, classification, segmentation, merging and identification. The uncertainties involved in these six steps were investigated and their effect on the mapped objects was analyzed. Three fuzzy object models were proposed to represent fuzzy objects of different application contexts. The concepts of conditional spatial extent, conditional boundary and transition zones of fuzzy objects were put forward and formalized based upon the formal data structure (FDS). In this procedure, uncertainty was transferred from thematic aspects to geometric aspects of objects, i.e. the existential uncertainty was converted to extensional uncertainty. The spatial effect of uncertainty in thematic aspect was expressed by the relationship between uncertainty of a cell belonging to the spatial extent of an object and the uncertainty of the cell belonging to classes.To detect dynamic changes in fuzzy objects, a method was proposed to identify objects and their state transitions from fuzzy spatial extents (regions) at different epochs. Similarity indicators of fuzzy regions were calculated based upon overlap between regions at consecutive epochs. Different combinations of indicator values imply different relationships between regions. Regions that were very similar represent the consecutive states of one object. By linking the regions, the historic lifelines of objects are built automatically. Then the relationship between regions became the relationship or interactions between objects, which were expressed in terms of processes, such as shift, merge or split. By comparing the spatial extents of objects at consecutive epochs, the change of objects was detected. The uncertainty of the change was analyzed by a series of change maps at different certainty levels. These can provide decision makers with more accurate information about change.For the third, and last, a process-oriented spatio-temporal data model was proposed to represent change and interaction of objects. The model was conceptually designed based upon the formalized representation of state and process of objects and was represented by a star-styled extended entity relationship, which I have called the Star Model. The conceptual design of the Star Model was translated into a relational logical design since many commercial relational database management systems are available. A prototype of the process-oriented spatio-temporal data model was implemented in ArcView based upon the case of Ameland. The user interface and queries of the prototype were developed using Avenue, the programming language of ArcView.The procedure of identification of fuzzy objects, which extracts fuzzy object data from field observations, unifies the existing field-oriented and object-oriented approaches. Therefore a generalized object concept - object with fuzzy spatial extent - has been developed. This concept links the object-oriented and the field-oriented characteristics of natural phenomena. The objects have conditional boundaries, representing their object characteristics; the interiors of the objects have field properties, representing their gradual and continuous distribution. Furthermore, the concept can handle both fuzzy and crisp objects. In the fuzzy object case, the objects have fuzzy transition or boundary zones, in which conditional boundaries may be defined; whereas crisp objects can be considered as a special case, i.e. there are sharp boundaries for crisp objects. Beyond that, both the boundary-oriented approach and the pixel-oriented approach of object extraction can use this generalized object concept, since the uncertainties of objects are expressed in the formal data structures (FDSs), which is applicable for either approach.The proposed process-oriented spatio-temporal data model is a general one, from which other models can be derived. It can support analysis and queries of time series data from varying perspectives through location-oriented, time-oriented, feature-oriented and process-oriented queries, in order to understand the behavior of dynamic spatial complexes of natural phenomena. Multi-strands of time can also be generated in this Star Model, each representing the (spatio-temporal) lifeline of an object. The model can represent dynamic processes affecting the spatial and thematic aspects of individual objects and object complexes. Because the model explicitly stores change (process) relative to time, procedures for answering queries relating to temporal relationships, as well as analytical tasks for comparing different sequences of change, are facilitated.The research findings in this thesis contribute theoretically and practically to the development of spatio-temporal data models for objects with fuzzy spatial extent.</p

Il contributo della idro-geomorfologia nella valutazione delle piene in Campania

2010 - 2011Italy and, in particular, the Campania region, has been exposed to Hydraulic Risk since long ago. In hydraulic risk analysis the definition of maximum flood discharge with a specific return time (T) is crucial and, to this aim, the VAPI- Campania procedure (1995) was adopted in the Campania region. The VAPI method is based on a geo-morphoclimatic model, identifying 7 climatic homogenous areas with respect to the rainfall probability density function and 3 classes of permeability for the rainfall-runoff transformation model. At the XXX National Congress on the Hydraulic and Hydraulic Engineering (IDRA 2006), the hydrological working group of Salerno University (Rossi and Villani (2006)), pointed out guidelines for up-dating the VAPI-Campania and, in particular the role of: orographic barriers in the evaluation of intensity and persistence of the extreme rainfalls; and the individuation of hydro-geomorphotypes for the rainfall-runoff modeling at the catchments and sub-catchments scales. In this framework, the present thesis gives a contribution to a hydro-geomorphological approach to achieve the two guidelines mentioned above. This research focuses first on the automatic individuation and objective delimitation of the orographic barriers in order to upgrade the heuristic delimitation (expert judgment) used in the simplified model of orographically induced rainfall of Rossi et al. (2005). The proposed procedure is based on the basic concepts of the hierarchic orometry (hierarchical mountain geomorphometry), prominence and parent relationships, to delineate the 'orographic mountain' in various spatial scale (hierarchical- multiscale approach). Also, the procedure defines the 'morphologic mountains' and its components (ridge, plain and hillslope) using slope, altitude, relief ratio and exposition with respect to the dominant perturbation fronts and its moving direction. The second topic of research deals with the individuation of the hydrogeomorphotypes. To this aim, the prototypal work of Guida et al. (2007), was taken into account as a guideline in the identification of the hydrogeomorphotypes and the decisional scheme of Scherrer and Naef (2003), here modify, allowed the identification of the three dominant runoff mechanisms on the Campania region. In particular, the prototypal procedure of Guida has been here objectified and automatized, defining the 9 elementary landscape forms (Troch et al., 2002), characterized in terms of sub-surface flow and soil moisture storage, under an objectbased GIS environment. The procedure here presented allowed identification on the hydro-geomorphological map, and of the runoff mechanisms: Hortonian overland flow for excess of saturation, subsurface flow, and deep percolation. In order to test the procedure some hydro-geomorphological analysis have been carried out based on data from two instrumented experimental catchments and on rainfall data from the Regional Functional Center of the Campania Civil Protection Sector. The results allowed to calculate the hydrologic index named Runoff Index, which improves the evaluation of the runoff coefficient (Cf) for un-gauged basins. Other analyses were performed on further 4 catchments with similar hydrologic and geologic behavior in order to extended the procedure to the whole Campania region. Also, conceptual discussions on the implementation of the Runoff Index in the rainfall-runoff transformation operated with a largely used hydrologic software, HECHMS, was made, in order to evaluate the feasibility of the procedure proposed in the present research and improve the RI in hydraulic risk evaluation at a regional scale. [edited by author]X n.s

Integrated modelling for 3D GIS

A three dimensional (3D) model facilitates the study of the real world objects it represents. A geoinformation system (GIS) should exploit the 3D model in a digital form as a basis for answering questions pertaining to aspects of the real world. With respect to the earth sciences, different kinds of objects of reality can be realized. These objects are components of the reality under study. At the present state-of-the-art different realizations are usually situated in separate systems or subsystems. This separation results in redundancy and uncertainty when different components sharing some common aspects are combined. Relationships between different kinds of objects, or between components of an object, cannot be represented adequately. This thesis aims at the integration of those components sharing some common aspects in one 3D model. This integration brings related components together, minimizes redundancy and uncertainty. Since the model should permit not only the representation of known aspects of reality, but also the derivation of information from the existing representation, the design of the model is constrained so as to afford these capabilities. The tessellation of space by the network of simplest geometry, the simplicial network, is proposed as a solution. The known aspects of the reality can be embedded in the simplicial network without degrading their quality. The model provides finite spatial units useful for the representation of objects. Relationships between objects can also be expressed through components of these spatial units which at the same time facilitate various computations and the derivation of information implicitly available in the model. Since the simplicial network is based on concepts in geoinformation science and in mathematics, its design can be generalized for n-dimensions. The networks of different dimension are said to be compatible, which enables the incorporation of a simplicial network of a lower dimension into another simplicial network of a higher dimension.The complexity of the 3D model fulfilling the requirements listed calls for a suitable construction method. The thesis presents a simple way to construct the model. The raster technique is used for the formation of the simplicial network embedding the representation of the known aspects of reality as constraints. The prototype implementation in a software package, ISNAP, demonstrates the simplicial network's construction and use. The simplicial network can facilitate spatial and non spatial queries, computations, and 2D and 3D visualizations. The experimental tests using different kinds of data sets show that the simplicial network can be used to represent real world objects in different dimensionalities. Operations traditionally requiring different systems and spatial models can be carried out in one system using one model as a basis. This possibility makes the GIS more powerful and easy to use