Automating the selection of standard parallels for conic map projections

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• 作者：Bojan &Scaron ; avriǒ^a ; ^b ; ^{savricb@onid.orst.edu" class="auth_mail" title="E-mail the corresponding author} ; Bernhard Jenny^a ; ^c
• 关键词：Standard parallels ; Conic map projections ; Albers conic projection ; Lambert conic projection ; Equidistant conic projection ; Adaptive composite map projections
• 刊名：Computers & Geosciences
• 出版年：2016
• 出版时间：May 2016
• 年：2016
• 卷：90
• 期：part_PA
• 页码：202-212
• 全文大小：2609 K

文摘

Conic map projections are appropriate for mapping regions at medium and large scales with east–west extents at intermediate latitudes. Conic projections are appropriate for these cases because they show the mapped area with less distortion than other projections. In order to minimize the distortion of the mapped area, the two standard parallels of conic projections need to be selected carefully. Rules of thumb exist for placing the standard parallels based on the width-to-height ratio of the map. These rules of thumb are simple to apply, but do not result in maps with minimum distortion. There also exist more sophisticated methods that determine standard parallels such that distortion in the mapped area is minimized. These methods are computationally expensive and cannot be used for real-time web mapping and GIS applications where the projection is adjusted automatically to the displayed area. This article presents a polynomial model that quickly provides the standard parallels for the three most common conic map projections: the Albers equal-area, the Lambert conformal, and the equidistant conic projection. The model defines the standard parallels with polynomial expressions based on the spatial extent of the mapped area. The spatial extent is defined by the length of the mapped central meridian segment, the central latitude of the displayed area, and the width-to-height ratio of the map. The polynomial model was derived from 3825 maps—each with a different spatial extent and computationally determined standard parallels that minimize the mean scale distortion index. The resulting model is computationally simple and can be used for the automatic selection of the standard parallels of conic map projections in GIS software and web mapping applications.