PYTHON-BASED AUTOMATION OF GEOPROCESSING IN DIGITAL TOPOGRAPHIC MAP PRODUCTION: CONTENT ALIGNMENT BETWEEN MAP SHEET BORDERS

This paper presents a semi-automated geoprocessing workflow for the 1:25 000 digital topographic map (DTM25) production at the Military Geographic Institute (MGI). Traditional manual alignment of adjacent sheet boundaries is labor-intensive, error-prone, and demands detailed visual inspection of vector features. We developed a Python toolbox for ArcGIS Desktop that encapsulates MGI’s cartographic rules within object-oriented classes and leverages ArcPy to automatically process and refine sheet-boundary geometries according to user-defined tolerances. Three specialized tools support unidirectional, bidirectional, and preparatory alignment scenarios, and automatically flag any residual misalignments for operator review. Deployment as a native ArcGIS toolbox lowers the barrier for non-programmers, while the modular architecture permits future enhancements such as automated quality control or adaptation to other map scales. Experimental application across multiple DTM25 sheet pairs demonstrated substantial reductions in manual effort, improved topological consistency, and enhanced geometric precision. This approach offers a replicable model for GIS organizations seeking to modernize and scale their cartographic workflows.

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Publication Details

Journal
Faculty of Geography (University of Belgrade)
Published
2025-11-20
DOI
https://doi.org/10.5281/zenodo.17533755
Primary Topic
Geographic Information Systems Studies
Type
article
Field-Weighted Citation Impact
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article

PYTHON-BASED AUTOMATION OF GEOPROCESSING IN DIGITAL TOPOGRAPHIC MAP PRODUCTION: CONTENT ALIGNMENT BETWEEN MAP SHEET BORDERS

Faculty of Geography (University of Belgrade)
Geographic Information Systems Studies
article

PYTHON-BASED AUTOMATION OF GEOPROCESSING IN DIGITAL TOPOGRAPHIC MAP PRODUCTION: CONTENT ALIGNMENT BETWEEN MAP SHEET BORDERS

article en

Abstract

This paper presents a semi-automated geoprocessing workflow for the 1:25 000 digital topographic map (DTM25) production at the Military Geographic Institute (MGI). Traditional manual alignment of adjacent sheet boundaries is labor-intensive, error-prone, and demands detailed visual inspection of vector features. We developed a Python toolbox for ArcGIS Desktop that encapsulates MGI’s cartographic rules within object-oriented classes and leverages ArcPy to automatically process and refine sheet-boundary geometries according to user-defined tolerances. Three specialized tools support unidirectional, bidirectional, and preparatory alignment scenarios, and automatically flag any residual misalignments for operator review. Deployment as a native ArcGIS toolbox lowers the barrier for non-programmers, while the modular architecture permits future enhancements such as automated quality control or adaptation to other map scales. Experimental application across multiple DTM25 sheet pairs demonstrated substantial reductions in manual effort, improved topological consistency, and enhanced geometric precision. This approach offers a replicable model for GIS organizations seeking to modernize and scale their cartographic workflows.

Faculty of Geography (University of Belgrade)
Geographical Institute (HU), Military Geographical Institute (RS)
Decent work and economic growth
Openalex Percentile: Top 33%
Geographic Information Systems Studies
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