Why and How Evaluating Generalised Data ?

Bard, Sylvain; Ruas, Anne

doi:10.1007/3-540-26772-7_25

Cited by 17 publications

(30 citation statements)

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“…'acceptable' or 'unacceptable'). According to Bard (2004) an idealized evolution function (Figure 4a) can be specified for each preservation constraint, where target characteristic values should be equal to initial values. In order to be more flexible, an acceptable range (tolerance) is introduced (dark gray areas in Figure 4).…”

Section: Interpret the Quantitative Evaluation Resultsmentioning

confidence: 99%

“…In order to be more flexible, an acceptable range (tolerance) is introduced (dark gray areas in Figure 4). In our research, we slightly modify the interpretation function as proposed by Bard (2004) to be more appropriate for the pattern preservation constraint as follows. If a measured homogeneity property falls into the dark gray area in Figure 4b (|MeasuredVal -TargetVal|  tolerance), then this property is considered as being well preserved (marked The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol.…”

Section: Interpret the Quantitative Evaluation Resultsmentioning

confidence: 99%

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Formalization and Data Enrichment for Automated Evaluation of Building Pattern Preservation

Zhang

Stoter

et al. 2012

Lecture Notes in Geoinformation and Cartography

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ABSTRACT:Automated evaluation of generalization output relies to a large extent on that requirements (e.g. specifications, constraints) being formalized in machine-readable formats. Previous studies suggest that the formalization and automated evaluation are relatively easier for legibility constraints (improve the readability of maps) than for preservation constraints (preserving important real-world phenomena). Three major difficulties, i.e., pattern classification and characterization, pattern matching, and constraint formalization, in the automated evaluation of building pattern preservation constraint are analyzed in this paper. A classification of available building patterns is reviewed based on a previous work. In addition, the transition events describing allowed changes for building patterns to preserve during generalization are obtained through the study of existing maps series (from 1:10k to 1:100k). Based on the obtained knowledge on pattern types and acceptable transition events, an approach to automatically match corresponding building patterns at different scales is presented. The methodology proposed is validated by applying it to the interactively generalized data. The result shows promising results and also further improvement in order to apply the method in an overall evaluation to indicate acceptable generalization solutions.

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Section: Interpret the Quantitative Evaluation Resultsmentioning

confidence: 99%

Section: Interpret the Quantitative Evaluation Resultsmentioning

confidence: 99%

Formalization and Data Enrichment for Automated Evaluation of Building Pattern Preservation

Zhang

Stoter

et al. 2012

Lecture Notes in Geoinformation and Cartography

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“…Bard and Ruas (2004) define the quality using the deviation from a given ideal. In this way, specifications for ideals are used (e.g.…”

Section: Related Workmentioning

confidence: 99%

“…The problem of quality assessment in generalization is not new, it has been tackled in several approaches (e.g. van Smaalen, 2003;Galanda, 2003;Bard, 2004;Skopeliti, Tsoulos, 2001). …”

Section: Introductionmentioning

confidence: 99%

Quality Assessment for Polygon Generalization

Anders¹,

Haunert²,

Podolskaya³

et al. 2008

Quality Aspects in Spatial Data Mining

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ABSTRACT:Different methods for map generalization have been developed. However, there are only a few publications that discuss the automatic quality assessment of generalized maps. This problem becomes crucial when the usefulness of a map has to be evaluated or different methods need to be compared, e.g. to find the best algorithm for a specific application. In this paper we present a new approach for the quality assessment of generalized polygons. In particular the simplification of buildings and the generalization of polygons that represent land use in a topographic database are discussed. Our approach distinguishes between two aims of generalization: Reducing the amount of data and keeping the map similar to the input map. A measure of quality that defines a compromise between these conflicting objectives is introduced. The proposed method was tested for a German cadastral data set and the official German topographic database ATKIS.

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“…Thus, only a single element of the McMaster and Shea model (1992) was considered: how to generalize spatial and attribute transformations. More recently, scientific studies have aimed to formalize map specifications to evaluate the generalization operators applied to single features or on the whole map (Bard and Ruas 2004;Filippovska et al 2008;Stoter et al 2009). …”

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confidence: 99%

Methodology for Automating the Cartometric Evaluation of Urban Topographic Maps of Brazil

Castro

Sluter

2016

Lecture Notes in Geoinformation and Cartography

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Cartometric evaluation is part of the cartographic generalization process and can indicate which operator should be applied and which features should be generalized. Those decisions are based on the occurrence of geometric conditions and spatial and holistic measures. Those aspects can be understood as legibility and visibility problems, and this knowledge can be described as rules of an expert system. The automation of cartographic generalization is a challenge partly because of subjective decisions made during the process. Cartometric evaluation show this subjectivity. The formalization and automated identification of the representation problems can make this process more holistic and less dependent on human control and influence and, therefore, more efficient. The objective of this paper is to present a method for developing a cartometric evaluation for topographic maps at 1:5000 derived from 1:2000 scale that is appropriate for the Brazilian landscape. Our approach consists of designing an expert system based on a decision tree. We present the first results of the expert system developed using ArcGIS and its application ModelBuilder to detect automatically map representation problems.

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Why and How Evaluating Generalised Data ?

Cited by 17 publications

References 1 publication

Formalization and Data Enrichment for Automated Evaluation of Building Pattern Preservation

Formalization and Data Enrichment for Automated Evaluation of Building Pattern Preservation

Quality Assessment for Polygon Generalization

Methodology for Automating the Cartometric Evaluation of Urban Topographic Maps of Brazil

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