1,721,005 research outputs found
A Graph-based Approach for Higher Order Gis Topological Analysis
No full textRetrieving structured information from an initial random collection of objects may be carried out by understanding the spatial
arrangement between them, assuming no prior knowledge about those objects. As far as topology is concerned, contemporary
desktop GIS packages do not generally support further analysis beyond adjacency. Thus, one of the original motivations of this work
was to develop new ideas for scene analysis by building up a graph-based technique for better interpretation and understanding of
spatial relationships between GIS vector-based objects beyond its first level of adjacency; the final aim is the performance of some
kind of local feature organization into a more meaningful global scene by using graph theory. As the example scenario, a LiDAR
data set is being used to test the technique that we plan to develop and implement. After the generation of the respective TIN, two
different binary classifications were applied to the TIN facets (based on two different slope thresholds) and TIN facets have been
aggregated into homogeneous polygons according to their slope characteristics. A graph-based clustering procedure inside these
polygonal regions, by establishing a neighbourhood graph, followed by the delineation of cluster shapes and the derivation of cluster
characteristics in order to obtain higher level geographic entities information (regarding sets of buildings, vegetation areas, and say,
land-use parcels) is object of further work. The results we are expecting to obtain might be useful to support land-use mapping,
image understanding or, generally speaking, to support clustering analysis and generalization processes
A containment-first search algorithm for higher-order analysis of urban topology
Full text linkResearch has revealed the importance of the concepts from the mathematical areas of both topology and graph theory for interpreting the spatial arrangement of spatial entities. Graph theory in particular has been used in different applications of a wide range of fields for that purpose, however not many graph-theoretic approaches to analyse entities within the urban environment are available in the literature. Some examples should be mentioned though such as, Bafna (2003), Barr and Barnsley (2004), Bunn et al. (2000), Krüger (1999), Nardinochi et al. (2003), and Steel et al. (2003).
Very little work has been devoted in particular to the interpretation of initially unstructured geospatial datasets. In most of the applications developed up-to-date for the interpretation and analysis of spatial phenomena within the urban context, the starting point is to some extent a meaningful dataset in terms of the urban scene. Starting at a level further back, before meaningful data are obtained, the interpretation and analysis of spatial phenomena are more challenging tasks and require further investigation.
The aim of retrieving structured information from initial unstructured spatial data, translated into more meaningful homogeneous regions, can be achieved by identifying meaningful structures within the initial random collection of objects and by understanding their spatial arrangement (Anders et al., 1999). It is believed that the task of understanding topological relationships between objects can be accomplished by both applying graph theory and carrying out graph analysis (de Almeida et al., 2007)
A Graph-based Approach for Higher Order Gis Topological Analysis
Full text linkRetrieving structured information from an initial random collection of objects may be carried out by understanding the spatial
arrangement between them, assuming no prior knowledge about those objects. As far as topology is concerned, contemporary
desktop GIS packages do not generally support further analysis beyond adjacency. Thus, one of the original motivations of this work
was to develop new ideas for scene analysis by building up a graph-based technique for better interpretation and understanding of
spatial relationships between GIS vector-based objects beyond its first level of adjacency; the final aim is the performance of some
kind of local feature organization into a more meaningful global scene by using graph theory. As the example scenario, a LiDAR
data set is being used to test the technique that we plan to develop and implement. After the generation of the respective TIN, two
different binary classifications were applied to the TIN facets (based on two different slope thresholds) and TIN facets have been
aggregated into homogeneous polygons according to their slope characteristics. A graph-based clustering procedure inside these
polygonal regions, by establishing a neighbourhood graph, followed by the delineation of cluster shapes and the derivation of cluster
characteristics in order to obtain higher level geographic entities information (regarding sets of buildings, vegetation areas, and say,
land-use parcels) is object of further work. The results we are expecting to obtain might be useful to support land-use mapping,
image understanding or, generally speaking, to support clustering analysis and generalization processes
A containment-first search algorithm for higher-order analysis of urban topology
No full textResearch has revealed the importance of the concepts from the mathematical areas of both topology and graph theory for interpreting the spatial arrangement of spatial entities. Graph theory in particular has been used in different applications of a wide range of fields for that purpose, however not many graph-theoretic approaches to analyse entities within the urban environment are available in the literature. Some examples should be mentioned though such as, Bafna (2003), Barr and Barnsley (2004), Bunn et al. (2000), Krüger (1999), Nardinochi et al. (2003), and Steel et al. (2003).
Very little work has been devoted in particular to the interpretation of initially unstructured geospatial datasets. In most of the applications developed up-to-date for the interpretation and analysis of spatial phenomena within the urban context, the starting point is to some extent a meaningful dataset in terms of the urban scene. Starting at a level further back, before meaningful data are obtained, the interpretation and analysis of spatial phenomena are more challenging tasks and require further investigation.
The aim of retrieving structured information from initial unstructured spatial data, translated into more meaningful homogeneous regions, can be achieved by identifying meaningful structures within the initial random collection of objects and by understanding their spatial arrangement (Anders et al., 1999). It is believed that the task of understanding topological relationships between objects can be accomplished by both applying graph theory and carrying out graph analysis (de Almeida et al., 2007)
A Graph-based Technique for Higher Order Topological Data Structure Visualisation
No full textEsta publicação foi agraciada com o prémio GISRUK 2005 “Whittles Publishing” Best Paper Award.Interpretation and analysis of spatial phenomena is a highly time consuming and laborious
task in several fietds of the Geomatics world (Anders et al., 1999). That is why the
automation of those tasks is especially needed in areas such as Geographical Information
Science (GlScience). Carrying out these tasks in the context of an urban scene is
particulariy challenging given its complexity: relatively small component elements and
itt"it g"nrially complei spatial pattern (Eyton, 1993, and Barr & Barnsley, 1996, both
cited in Barnsley and Barr, 1997).
Topology is a particularly important research area in the field of GlScience, for it is a
central àefining feature of a geographical information system (GIS). But, as far as
topological relàtionships between spatial objects are concerned, "generally speaking
.ottt.Àporary desktop bIS packages do not support further information beyond the first
level oi adjâcency" (Theobald, 2001). Therefore, this research project focused on scene
analysis bi buiiding up a technique for the better understanding of topological
relationships between vector-based GIS objects, beyond the fnst level of adjacency.
Another initial interest was to investigate the possible use of graph theory for this purpose.
To date, this mathematical framework has been used in different applications in a wide
range of fields to represent connections and relationships between spatial entities. Several
u,rtùo6 (including Laurini and Thompson, 1992) have maintained that "this particular tool
is extremely valuable and efficient in storing and describing the spatial structure of
geographicil entities and their spatial arrangement". Theobald (2001) added that "concepts
àf gruptt theory allow us to extend the standard notion of adjacency".
The aim of retrieving structured information translated into more meaningful homogeneous
regions, for instancJ fro* an initial unstructured data set, may be achieved by identifuing
mJaningful structures within the initial random collection of objects and by understanding the spatial arrangement between them. We believe that applying graph theory and carrying out graph
analysis may accomplish this
Evaluating the potential of the forthcoming commercial US high-resolution satellite sensor imagery at the Ordnance Survey
No full textAs the National Mapping Agency of Great Britain, the Ordinance Survey® (OS) is driven by a need to reduce costs and commercialize operations, and as such has been investigating photogrammetric methods to improve existing products, streamline existing production, and increase the current portfolio of products. Over the last 18 months, the OS has been involved in a major research project to tackle these issues through an evaluation of the forthcoming commercial U.S. high spatial resolution satellite sensors which are offering 1-m panchromatic and 4-m multispectral spatial resolutions. Work has focused on improving the existing National Height Dataset (NHD), reducing the cost of photogrammetric survey, automatic topographic feature change detection, production of DEMs; three-dimensional (3D) urban models, and land-use classification. Results from the project using simulated imagery indicate that it would have potential within the OS in all areas evaluated. The work now needs to be followed up when real high spatial resolution satellite imagery becomes commercially available
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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