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Dr. Anna Fiedukowicz
Warsaw University of Technology, Faculty of Geodesy and Cartography

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0 Cartography
0 Data Analysis
0 Data Mining
0 Fuzzy Logic
0 Spatial Analysis

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Journal article
Published: 01 July 2020 in ISPRS International Journal of Geo-Information
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Micro, small, and medium-sized enterprises (MSMEs) are an essential part of economies at the national, regional, and local levels. Understanding the determinants of the development of this sector is interesting not only for researchers but also for local governments to support the development of this sector. This paper analyses micro, small, and medium enterprises at the gmina (local) level in one region, the Kujawsko-Pomorskie voivodship (NUTS2) in Poland. The authors use multivariate linear regression, spatial econometrics, and classification trees to model the influence of different factors on the number of enterprises relative to population size. The authors found that the most crucial factor in all cases, independently of the method used, is the local government’s revenue from personal income tax per capita. This finding, together with the lack of significance of variables related to the distance to technological parks or economic zones, indicates that the enterprises in the region produce mainly for local consumption and lack innovativeness. The authors also examined the influence of spatial context on the number of enterprises. The most important factor seems to be the percentage of built-up areas, but there are also others, depending on the model type; again, this confirms the local character of the activity of micro, small, and medium enterprises in the region. Variables representing the spatial context can explain the relative number of enterprises with coefficient of determination (R2) between 0.30 and 0.45, which shows that this context played a relatively significant role in the development of the MSME sector in the region. On the other hand, the econometric models (that include the neighborhood) are only significant (improving R2) for medium enterprises, which means that medium enterprises expand their activity beyond the local range.

ACS Style

Agnieszka Chłoń-Domińczak; Anna Fiedukowicz; Robert Olszewski. Geographical and Economic Factors Affecting the Spatial Distribution of Micro, Small, and Medium Enterprises: An Empirical Study of The Kujawsko-Pomorskie Region in Poland. ISPRS International Journal of Geo-Information 2020, 9, 426 .

AMA Style

Agnieszka Chłoń-Domińczak, Anna Fiedukowicz, Robert Olszewski. Geographical and Economic Factors Affecting the Spatial Distribution of Micro, Small, and Medium Enterprises: An Empirical Study of The Kujawsko-Pomorskie Region in Poland. ISPRS International Journal of Geo-Information. 2020; 9 (7):426.

Chicago/Turabian Style

Agnieszka Chłoń-Domińczak; Anna Fiedukowicz; Robert Olszewski. 2020. "Geographical and Economic Factors Affecting the Spatial Distribution of Micro, Small, and Medium Enterprises: An Empirical Study of The Kujawsko-Pomorskie Region in Poland." ISPRS International Journal of Geo-Information 9, no. 7: 426.

Journal article
Published: 01 March 2020 in Polish Cartographical Review
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Selection is a key element of the cartographic generalisation process, often being its first stage. On the other hand it is a component of other generalisation operators, such as simplification. One of the approaches used in generalization is the condition-action approach. The author uses a condition-action approach based on three types of rough logics (Rough Set Theory (RST), Dominance-Based Rough Set Theory (DRST) and Fuzzy-Rough Set Theory (FRST)), checking the possibility of their use in the process of selecting topographic objects (buildings, roads, rivers) and comparing the obtained results. The complexity of the decision system (the number of rules and their conditions) and its effectiveness are assessed, both in terms of quantity and quality – through visual assessment. The conducted research indicates the advantage of the DRST and RST approaches (with the CN2 algorithm) due to the quality of the obtained selection, the greater simplicity of the decision system, and better refined IT tools enabling the use of these systems. At this stage, the FRST approach, which is characterised by the highest complexity of created rules and the worst selection results, is not recommended. Particular approaches have limitations resulting from the need to select appropriate measurement scales for the attributes used in them. Special attention should be paid to the selection of network objects, in which the use of only a condition-action approach, without maintaining consistency of the network, may not produce the desired results. Unlike approaches based on classical logic, rough approaches allow the use of incomplete or contradictory information. The proposed tools can (in their current form) find an auxiliary use in the selection of topographic objects, and potentially also in other generalisation operators.

ACS Style

Anna Fiedukowicz. The use of rough rules in the selection of topographic objects for generalizing geographical information. Polish Cartographical Review 2020, 52, 1 -15.

AMA Style

Anna Fiedukowicz. The use of rough rules in the selection of topographic objects for generalizing geographical information. Polish Cartographical Review. 2020; 52 (1):1-15.

Chicago/Turabian Style

Anna Fiedukowicz. 2020. "The use of rough rules in the selection of topographic objects for generalizing geographical information." Polish Cartographical Review 52, no. 1: 1-15.

Journal article
Published: 10 January 2020 in ISPRS International Journal of Geo-Information
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Generalization of geographic information enables cognition and understanding not only of objects and phenomena located in space but also the relations and processes between them. The automation of this process requires formalization of cartographic knowledge, including information on the spatial context of objects. However, the question remains which information is crucial to the decisions regarding the generalization (in this paper: selection) of objects. The article presents and compares the usability of three methods based on rough set theories (rough set theory, dominance-based rough set theory, fuzzy rough set theory) that facilitate the designation of the attributes relevant to a decision. The methods are using different types (levels of measurements) of attributes. The author determines reducts and their cores (common elements) that show the relevance of attributes stemming from the spatial context. The fuzzy rough set theory method proved the least useful, whereas the rough set theory and dominance-based rough set theory methods seem to be recommendable (depending on the governing level of measurement).

ACS Style

Anna Fiedukowicz. The Role of Spatial Context Information in the Generalization of Geographic Information: Using Reducts to Indicate Relevant Attributes. ISPRS International Journal of Geo-Information 2020, 9, 37 .

AMA Style

Anna Fiedukowicz. The Role of Spatial Context Information in the Generalization of Geographic Information: Using Reducts to Indicate Relevant Attributes. ISPRS International Journal of Geo-Information. 2020; 9 (1):37.

Chicago/Turabian Style

Anna Fiedukowicz. 2020. "The Role of Spatial Context Information in the Generalization of Geographic Information: Using Reducts to Indicate Relevant Attributes." ISPRS International Journal of Geo-Information 9, no. 1: 37.

Conference paper
Published: 16 February 2018 in Transactions on Petri Nets and Other Models of Concurrency XV
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The distribution of information has become an element of heritage conservation policy, as well as a tool aiming at sustainable use of historic resources, or even a prerequisite of effective conservation. This aspect is very often underestimated and reduced to simple popularization, which consequently oversimplifies such complex mater, what historic site conservation is. The issues described above are addressed by the authors of this article through the project run on behalf of the National Heritage Board (NHB) attempting to place and publish the information on all historic sites’ resources entered in the register of objects of cultural heritage (the heritage register). Hierarchical classification was prepared within this project in order to sequentially establish: general categories of monuments, separate classes for architectural and archaeological sites, and finally, formal/functional typology for architectural monuments. The signatures for each group were carefully designed and prepared. The efficient visualisation of historical sites was possible due to the common utilisation of advanced information technologies as well as modern cartographical solutions. Authors had shown the importance of spatial reference of historical sites achieved by visualising them jointly with up-to-date spatial topographical and a general database as well as a digital terrain model. Last but not least, the meaning of user interface has been highlighted as the tool of communication and interaction with the final user. The geoportal developed during this project can be seen as a modern digital tool supporting state heritage conservation policy and popularising knowledge about historical sites among the wide group of users.

ACS Style

Anna Fiedukowicz; Andrzej Głażewski; Arkadiusz Kołodziej; Krzysztof Koszewski; Paweł Kowalski; Robert Olszewski; Leszek Włochyński. Map Portal as a Tool to Share Information on Cultural Heritage Illustrated by the National Heritage Board Geoportal. Transactions on Petri Nets and Other Models of Concurrency XV 2018, 48 -64.

AMA Style

Anna Fiedukowicz, Andrzej Głażewski, Arkadiusz Kołodziej, Krzysztof Koszewski, Paweł Kowalski, Robert Olszewski, Leszek Włochyński. Map Portal as a Tool to Share Information on Cultural Heritage Illustrated by the National Heritage Board Geoportal. Transactions on Petri Nets and Other Models of Concurrency XV. 2018; ():48-64.

Chicago/Turabian Style

Anna Fiedukowicz; Andrzej Głażewski; Arkadiusz Kołodziej; Krzysztof Koszewski; Paweł Kowalski; Robert Olszewski; Leszek Włochyński. 2018. "Map Portal as a Tool to Share Information on Cultural Heritage Illustrated by the National Heritage Board Geoportal." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 48-64.

Conference paper
Published: 23 June 2015 in Transactions on Petri Nets and Other Models of Concurrency XV
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One of the most important objectives within the scope of current cartography is the creation of system controlling the process of geographical data generalisation. Firstly, it requires selection of the features crucial from the point of view of the decision making process. Such tools as reducts and fuzzy reducts, though useful, are still insufficient for the quantitative decisions, common in cartographical generalization. Thus the author proposed a modification in fuzzy reducts calculating, which can allow to calculate them with regard to a continuous decision variable. The proposed method is based on the t-norm of fuzzy indiscernibility based on attribute value and fuzzy indiscernibility based on decision, which is calculated for each pair of objects. The solution seems to be more intuitive than the ones established previously.

ACS Style

Anna Fiedukowicz. Fuzzy Rough Sets Theory Reducts for Quantitative Decisions – Approach for Spatial Data Generalization. Transactions on Petri Nets and Other Models of Concurrency XV 2015, 314 -324.

AMA Style

Anna Fiedukowicz. Fuzzy Rough Sets Theory Reducts for Quantitative Decisions – Approach for Spatial Data Generalization. Transactions on Petri Nets and Other Models of Concurrency XV. 2015; ():314-324.

Chicago/Turabian Style

Anna Fiedukowicz. 2015. "Fuzzy Rough Sets Theory Reducts for Quantitative Decisions – Approach for Spatial Data Generalization." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 314-324.

Book chapter
Published: 01 January 2014 in Transactions on Petri Nets and Other Models of Concurrency XV
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The present article attempts to support the process of classification of multi-characteristic spatial data in order to develop the correct cartographic visualisation of complex geographical information in the thematic geoportal. Rough sets, decision rules and artificial neural networks were selected as relevant methods of spatially distributed monument classification. Basing on the obtained results it was determined that the attributes reflecting the spatial relations between specific objects play an extremely significant role in the process of classification, reducts allow to select exclusively essential attributes of objects and neural networks and decision rules are highly useful for the purposes of classification of multi-characteristic spatial data.

ACS Style

Robert Olszewski; Anna Fiedukowicz. Supporting the Process of Monument Classification Based on Reducts, Decision Rules and Neural Networks. Transactions on Petri Nets and Other Models of Concurrency XV 2014, 8537, 327 -334.

AMA Style

Robert Olszewski, Anna Fiedukowicz. Supporting the Process of Monument Classification Based on Reducts, Decision Rules and Neural Networks. Transactions on Petri Nets and Other Models of Concurrency XV. 2014; 8537 ():327-334.

Chicago/Turabian Style

Robert Olszewski; Anna Fiedukowicz. 2014. "Supporting the Process of Monument Classification Based on Reducts, Decision Rules and Neural Networks." Transactions on Petri Nets and Other Models of Concurrency XV 8537, no. : 327-334.

Journal article
Published: 01 January 2013 in Geoinformatica Polonica
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ACS Style

Anna Fiedukowicz. Construction of fuzzy interference system for generalization of geographic information – selection of road segments. Geoinformatica Polonica 2013, 12, 53 -62.

AMA Style

Anna Fiedukowicz. Construction of fuzzy interference system for generalization of geographic information – selection of road segments. Geoinformatica Polonica. 2013; 12 (1):53-62.

Chicago/Turabian Style

Anna Fiedukowicz. 2013. "Construction of fuzzy interference system for generalization of geographic information – selection of road segments." Geoinformatica Polonica 12, no. 1: 53-62.

Journal article
Published: 01 November 2012 in Geodesy and Cartography
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The wide access to source data, published by numerous websites, results in situation, when information acquisition is not a problem any more. The real problem is how to transform information in the useful knowledge. Cartographic method of research, dealing with spatial data, has been serving this purpose for many years. Nowadays, it allows conducting analyses at the high complexity level, thanks to the intense development in IT technologies, The vast majority of analytic methods utilizing the so-called data mining and data enrichment techniques, however, concerns non-spatial data. According to the Authors, utilizing those techniques in spatial data analysis (including analysis based on statistical data with spatial reference), would allow the evolution of the Spatial Information Infrastructure (SII) into the Spatial Knowledge Infrastructure (SKI). The SKI development would benefit from the existence of statistical geoportal. Its proposed functionality, consisting of data analysis as well as visualization, is outlined in the article. The examples of geostatistical analyses (ANOVA and the regression model considering the spatial neighborhood), possible to implement in such portal and allowing to produce the “cartographic added value”, are also presented here.

ACS Style

Anna Fiedukowicz; Jedrzej Gasiorowski; Paweł Kowalski; Robert Olszewski; Agata Pillich-Kolipinska. The statistical geoportal and the “cartographic added value” – creation of the spatial knowledge infrastructure. Geodesy and Cartography 2012, 61, 47 -70.

AMA Style

Anna Fiedukowicz, Jedrzej Gasiorowski, Paweł Kowalski, Robert Olszewski, Agata Pillich-Kolipinska. The statistical geoportal and the “cartographic added value” – creation of the spatial knowledge infrastructure. Geodesy and Cartography. 2012; 61 (1):47-70.

Chicago/Turabian Style

Anna Fiedukowicz; Jedrzej Gasiorowski; Paweł Kowalski; Robert Olszewski; Agata Pillich-Kolipinska. 2012. "The statistical geoportal and the “cartographic added value” – creation of the spatial knowledge infrastructure." Geodesy and Cartography 61, no. 1: 47-70.