Spatial pattern analysis of built-up land use and zoning conformity using polygon-based statistics: a case study of Tegal city, Indonesia
DOI: https://doi.org/10.3846/gac.2026.25842Abstract
Rapid urban expansion in coastal cities increasingly challenges the effectiveness of spatial planning enforcement. Tegal city, located on Java’s northern coast, is experiencing intensive built-up land development accompanied by growing spatial clustering. This study analyses polygon-level built-up land patterns using Ripley’s K-function to identify multi-scale clustering, Global Moran’s I to assess spatial autocorrelation, and Local Moran’s I (LISA) to detect local clusters. Built-up Land Use/Land Cover (LULC) polygons derived from OpenStreetMap (2024) were compared with the official Spatial Plan (RTRW 2021–2031). The objectives are to identify the clustering behaviour of built-up areas and assess conformity between actual land development and planned zoning. The results reveal a concentric-clustered spatial structure and localized zones of spatial non-conformity with the official spatial plan. Transitional areas exhibit significant land-use mismatches, indicating weaknesses in spatial-use control. A Global Moran’s I value of 0.145 (p < 0.05) indicates weak but statistically significant positive spatial autocorrelation. These findings highlight the importance of strengthening zoning enforcement and updating detailed spatial plans (RDTR). The study demonstrates how integrated polygon-based spatial statistics can support routine spatial planning evaluation and zoning enforcement in rapidly developing coastal cities.
Keywords:
spatial pattern analysis, Ripley’s K-function, global Moran’s I, Local Moran’s I (LISA), built-up land, land-use clustering, spatial plan conformity, coastal city, Tegal city, GISHow to Cite
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Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University.
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