Contour lines are important for quantitatively displaying relief and identifying morphometric features on a map. Contour trees are often used to represent spatial relationships between contours and assist the user in analysing the terrain. However, automatic analysis from the contour tree is still limited as features identified on a map by sets of contours are not only characterised by local relationships between contours but also by relationships with other features at different levels of representation. In this paper, a new method based on adjacency and inclusion relationships between regions defined by sets of contours is presented. The method extracts terrain features and stores them in a feature tree providing a description of the landscape at multiple levels of detail. The method is applied to terrain analysis and generalisation of a contour map by selecting the most relevant features according to the purpose of the map. Experimental results are presented and discussed.
The urban heat island phenomenon occurring within urban areas or city-clusters is increasingly becoming a severe problem in the urbanization process. Previous research mainly focusing on static urban heat island modeled at fixed time instants is not capable to track the evolutionary process of the urban heat islands in both time and space domains. This research designs an object-oriented dynamic model to reconstruct the evolutionary process of urban heat islands. Each urban heat island is modeled as a spatiotemporal field-object with it own life-cycle. The dynamic behavior of an urban heat island is defined by a series of filiations (e.g. expansion and contraction). The model was implemented in an object-relational database and applied to air temperature data collected from weather stations in hourly-basis over seven days. The behaviors of UHI were extracted from the data. Results suggest that the model can effectively identify different behaviors and status of urban heat islands, and reveal the spatiotemporal behavior of each of them.
In both GIS and terrain analysis, drainage systems are important components. Owing to local topography and subsurface geology, a drainage system achieves a particular drainage pattern based on the form and texture of its network of stream channels and tributaries. Although research has been done on the description of drainage patterns in geography and hydrology, automatic drainage pattern recognition in river networks is not well developed. This paper introduces a new method for automatic classification of drainage systems in different patterns. The method applies to river networks and the terrain model is not required in the process. A series of geometric indicators describing each pattern are introduced. Network classification is based on fuzzy set theory. For each pattern, the level of membership of the network is given by the different indicator values. The method was implemented and experimental results are presented and discussed.
The present paper provides a review of two research topics that are central to geospatial semantics: information modeling and elicitation. The first topic deals with the development of ontologies at different levels of generality and formality, tailored to various needs and uses. The second topic involves a set of processes that aim to draw out latent knowledge from unstructured or semi-structured content: semantic-based extraction, enrichment, search, and analysis. These processes focus on eliciting a structured representation of information in various forms such as: semantic metadata, links to ontology concepts, a collection of topics, etc. The paper reviews the progress made over the last five years in these two very active areas of research. It discusses the problems and the challenges faced, highlights the types of semantic information formalized and extracted, as well as the methodologies and tools used, and identifies directions for future research.
A landform is a physical feature of the terrain with its own recognisable shape. Its definition is often qualitative and inherently vague. Hence, landforms are difficult to formalise in a logical model that can be implemented. We propose for that purpose a framework where these qualitative and vague definitions are transformed successively during different phases to yield an implementable data structure. Our main consideration is that landforms are characterised by salient elements as perceived by users. Hence, a common prototype based on an object-oriented approach is defined that shall apply to all landforms. This framework shall facilitate the definition of conceptual models for other landforms and relies on the use of ontology design patterns to express common elements and structures. The model is illustrated on examples from the literature, showing that existing works undertaken separately can be developed under a common framework.
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