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Articles

Geographic Representation in GIS and Art: Common Threads as Exemplified in Paintings by Seurat, Signac, Mondrian, and Diebenkorn

Pages 178-195 | Received 20 Jan 2017, Accepted 21 Nov 2017, Published online: 24 Jan 2018
 

Abstract

This article explores the relationship between geographic representation in geographic information systems (GIS) and in art, as illustrated by the vector and raster spatial data models used in GIS and their affinity with representational painting techniques employed by the painters Georges Seurat (1859–1891), Paul Signac (1863–1935), Piet Mondrian (1872–1944), and Richard Diebenkorn (1922–1993). The location-based raster data model is discussed in the context of the pointillism painting technique espoused by the French neo-Impressionist painters Seurat and Signac, whereas the object-based vector data model is related to the geometric abstraction techniques employed by the Dutch abstract painter Mondrian and the American abstract painter Diebenkorn. Commonalities between the spatial data models used in GIS and the representational techniques employed by these painters are explored within the context of both the cognitive basis of geographic representation and the representational objectives embodied by the artistic and scientific movements within which such representational approaches were developed.

本文探讨地理信息系统(GIS)和艺术中的地理再现之间的关联性,并由GIS所使用的向量与光栅空间数据模型,及其与画家乔治.秀拉(1859-1891)、保罗.希涅克(1863-1935)、皮特.蒙德里安(1872-1944)和理查.迪本科恩(1922-1993)所使用的再现绘画技术之间的相似性进行阐述。根据区位的光栅数据模型,在法国新印象派画家秀拉和希涅克所拥护的点描派绘画技术的脉络中进行探讨,而以物件为基础的向量数据模型,则连结至荷兰抽象派画家蒙德里安与美国抽象派画家迪本科恩所运用的几何抽象技术。本文同时在地理再现的认知基础与在发展再现方法的艺术和科学运动所体现的再现目标之脉络中,探讨GIS所使用的空间数据模型和这些画家所运用的再现技术之间的共通性。

Este artículo explora la relación entre la representación geográfica en los sistemas de información geográfica (SIG) y el arte, como se ilustra con los modelos de vectores y ráster de datos espaciales que se usan en SIG, y su afinidad con las técnicas de pintura representacional utilizadas por los pintores Georges Seurat (1859–1891), Paul Signac (1863–1935), Piet Mondrian (1872–1944) y Richard Diebenkorn (1922–1993). El modelo ráster de datos basado en localización se discute en el contexto de la técnica de pintura del puntillismo promovida por los pintores neo-impresionistas franceses Seurat y Signac, mientras que el modelo vector de datos basado en objeto se relaciona con las técnicas de abstracción geométrica empleadas por el pintor holandés abstraccionista Mondrian y por el también pintor abstraccionista americano Diebenkorn. Se exploran las cosas en común que se presentan entre los modelos de datos espaciales usados en SIG y las técnicas representacionales empleadas por estos pintores, tanto dentro del contexto de las bases cognitivas de la representación geográfica como de los objetivos representacionales encarnados por los movimientos artísticos y científicos dentro de los cuales fueron desarrollados tales enfoques representacionales.

ACKNOWLEDGMENTS

I would like to thank the editors and anonymous reviewers for their helpful comments on earlier version of this article. Thanks also to the Richard Diebenkorn Foundation for providing the digital image of Diebenkorn’s painting Ocean Park No. 128.

Additional information

Notes on contributors

Jeremy Mennis

JEREMY MENNIS is a Professor in the Department of Geography and Urban Studies at Temple University, Philadelphia, PA 19122. E-mail: [email protected]. His research interests address issues of representation in geographic information systems and science.

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