Evolusi dan Tipologi Data OpenStreetMap di Daerah Istimewa Yogyakarta Tahun 2015–2025
Abstract
OpenStreetMap (OSM) data in the Special Region of Yogyakarta grew rapidly during 2015–2025, but the distribution of this growth across object types and administrative areas remains insufficiently understood. This study aims to examine the evolution of road networks, buildings, and points of interest (POIs), develop a cross-object growth typology, and evaluate the relative structure of OSM data. Historical data were obtained through the ohsome API and aggregated at the subdistrict/kemantren level. The analysis covered absolute change, growth rates, percentile-rank scores, and the Road–Building Ratio (RBR), Building–POI Ratio (BPR), and Amenity–Tourism Ratio (ATR). Buildings showed the strongest growth, roads developed through coverage expansion and segment refinement, while POIs grew more moderately despite sharp increases in shop and tourism features. The typology identified multi-object growth, road-dominant, building-dominant, POI-dominant, and low-growth patterns. Structural ratios indicated the growing dominance of buildings and an imbalance between physical objects and functional information.
Keywords: Special Region of Yogyakarta; spatio-temporal evolution; OpenStreetMap; POI; growth typology
Abstrak
Data OpenStreetMap (OSM) di Daerah Istimewa Yogyakarta berkembang pesat selama 2015–2025, tetapi pemerataan pertumbuhan antarobjek dan antarwilayah belum dipahami secara sistematis. Penelitian ini bertujuan menganalisis evolusi jaringan jalan, bangunan, dan points of interest (POI), menyusun tipologi pertumbuhan lintas objek, serta mengevaluasi struktur relatif data OSM. Data historis diperoleh melalui ohsome API dan diagregasikan pada tingkat kecamatan/kemantren. Analisis mencakup perubahan absolut, laju pertumbuhan, skor percentile rank, serta Road–Building Ratio (RBR), Building–POI Ratio (BPR), dan Amenity–Tourism Ratio (ATR). Hasil menunjukkan bahwa bangunan tumbuh paling kuat, jaringan jalan berkembang melalui perluasan cakupan dan pendetailan segmen, sedangkan POI tumbuh lebih moderat meskipun kategori shop dan tourism meningkat tajam. Tipologi menghasilkan pola multi-object growth, road-dominant, building-dominant, POI-dominant, dan low-growth. Rasio struktural menunjukkan penguatan dominasi bangunan dan ketidakseimbangan antara objek fisik dan informasi fungsi ruang.
Kata kunci: Daerah Istimewa Yogyakarta; evolusi spasio-temporal; OpenStreetMap; POI; tipologi pertumbuhan
References
M. F. Goodchild, “Citizens as sensors: the world of volunteered geography,” GeoJournal, vol. 69, no. 4, pp. 211–221, Nov. 2007, doi: 10.1007/s10708-007-9111-y.
M. Haklay, “How Good is Volunteered Geographical Information? A Comparative Study of OpenStreetMap and Ordnance Survey Datasets,” Environ Plann B Plann Des, vol. 37, no. 4, pp. 682–703, Aug. 2010, doi: 10.1068/b35097.
A. Y. Grinberger, M. Minghini, L. Juhász, P. Mooney, and G. Yeboah, “Bridging the Map? Exploring Interactions between the Academic and Mapping Communities in OpenStreetMap,” Sep. 2019, doi: 10.5281/ZENODO.3408639.
P. Mooney and M. Minghini, “A Review of OpenStreetMap Data,” in Mapping and the Citizen Sensor, Ubiquity Press, 2017, pp. 37–59. doi: 10.5334/bbf.c.
P. Neis and D. Zielstra, “Recent Developments and Future Trends in Volunteered Geographic Information Research: The Case of OpenStreetMap,” Future Internet, vol. 6, no. 1, pp. 76–106, Jan. 2014, doi: 10.3390/fi6010076.
S. Borkowska and K. Pokonieczny, “Analysis of OpenStreetMap Data Quality for Selected Counties in Poland in Terms of Sustainable Development,” Sustainability, vol. 14, no. 7, p. 3728, Mar. 2022, doi: 10.3390/su14073728.
H. Senaratne, A. Mobasheri, A. L. Ali, C. Capineri, and M. (Muki) Haklay, “A review of volunteered geographic information quality assessment methods,” International Journal of Geographical Information Science, vol. 31, no. 1, pp. 139–167, Jan. 2017, doi: 10.1080/13658816.2016.1189556.
G. Yeboah et al., “Analysis of OpenStreetMap Data Quality at Different Stages of a Participatory Mapping Process: Evidence from Slums in Africa and Asia,” IJGI, vol. 10, no. 4, p. 265, Apr. 2021, doi: 10.3390/ijgi10040265.
A. N. L. Kusumo, D. Reckien, and J. Verplanke, “Volunteered Geographic Information (VGI) for the Spatial Planning of Flood Evacuation Shelters in Jakarta, Indonesia,” in GIS in Sustainable Urban Planning and Management, 1st ed., Boca Raton: CRC Press, 2018, pp. 307–324. doi: 10.1201/9781315146638-18.
I. Meidodga, A. Syahrin, R. T. Putra, F. Warfandu, and A. N. Bimasena, “Pemanfaatan Data Geospasial dalam Mewujudkan Sistem Informasi Pertanahan Multiguna Bagi Multipihak,” WB, vol. 3, no. 1, pp. 62–80, Jul. 2023, doi: 10.31292/wb.v3i1.51.
I. E. Noviandi et al., “Mendukung Sistem Basis Data Spasial Desa Cibodas dengan Kegiatan Pemetaan Partisipatif Menggunakan Platform Openstreetmap,” JPIG, vol. 6, no. 2, pp. 125–133, Sep. 2021, doi: 10.21067/jpig.v6i2.5939.
B. Pahlupi, L. Afriani, and D. Despa, “Revitalisasi Pengelolaan Data Spasial dalam mewujudkan Penyelenggaraan Informasi Geospasial Berkualitas dan Satu Data Indonesia Provinsi Lampung serta Pelayanan Publik,” JPI Unila, vol. 5, no. 1, pp. 42–47, Jul. 2024, doi: 10.23960/jpi.v5n1.125.
M. Raifer et al., “OSHDB: a framework for spatio-temporal analysis of OpenStreetMap history data,” Open geospatial data, softw. stand., vol. 4, no. 1, p. 3, Dec. 2019, doi: 10.1186/s40965-019-0061-3.
C. Barron, P. Neis, and A. Zipf, “A Comprehensive Framework for Intrinsic OpenStreetMap Quality Analysis,” Transactions in GIS, vol. 18, no. 6, pp. 877–895, Dec. 2014, doi: 10.1111/tgis.12073.
C. Barrington-Leigh and A. Millard-Ball, “The world’s user-generated road map is more than 80% complete,” PLoS ONE, vol. 12, no. 8, p. e0180698, Aug. 2017, doi: 10.1371/journal.pone.0180698.
M. Moradi, S. Roche, and M. A. Mostafavi, “Exploring five indicators for the quality of OpenStreetMap road networks: a case study of Québec, Canada,” Geomatica, vol. 75, no. 4, 2021, doi: https://doi.org/10.1139/geomat-2021-0012.
D. Li et al., “Mapping the Completeness and Positional Accuracy of OpenStreetMap Road Data at the County Level in the Contiguous United States,” Transactions in GIS, vol. 29, no. 4, p. e70077, Jun. 2025, doi: 10.1111/tgis.70077.
W. Wang, A. Zipf, and L. Meng, “Intrinsic assessment of the attribute completeness and accuracy in OpenStreetMap road data,” Abstr. Int. Cartogr. Assoc., vol. 10, pp. 1–2, Dec. 2025, doi: 10.5194/ica-abs-10-297-2025.
M. A. Brovelli and G. Zamboni, “A New Method for the Assessment of Spatial Accuracy and Completeness of OpenStreetMap Building Footprints,” IJGI, vol. 7, no. 8, p. 289, Jul. 2018, doi: 10.3390/ijgi7080289.
Y. Zhang, Q. Zhou, M. A. Brovelli, and W. Li, “Assessing OSM building completeness using population data,” International Journal of Geographical Information Science, vol. 36, no. 7, pp. 1443–1466, Jul. 2022, doi: 10.1080/13658816.2021.2023158.
B. Herfort, S. Lautenbach, J. Porto De Albuquerque, J. Anderson, and A. Zipf, “A spatio-temporal analysis investigating completeness and inequalities of global urban building data in OpenStreetMap,” Nat Commun, vol. 14, no. 1, p. 3985, Jul. 2023, doi: 10.1038/s41467-023-39698-6.
T. Ullah, S. Lautenbach, B. Herfort, M. Reinmuth, and D. Schorlemmer, “Assessing Completeness of OpenStreetMap Building Footprints Using MapSwipe,” IJGI, vol. 12, no. 4, p. 143, Mar. 2023, doi: 10.3390/ijgi12040143.
L. Zhang and D. Pfoser, “Using OpenStreetMap point-of-interest data to model urban change—A feasibility study,” PLoS ONE, vol. 14, no. 2, p. e0212606, Feb. 2019, doi: 10.1371/journal.pone.0212606.
C. Klinkhardt, T. Woerle, L. Briem, M. Heilig, M. Kagerbauer, and P. Vortisch, “Using OpenStreetMap as a Data Source for Attractiveness in Travel Demand Models,” Transportation Research Record: Journal of the Transportation Research Board, vol. 2675, no. 8, pp. 294–303, Aug. 2021, doi: 10.1177/0361198121997415.
C. Klinkhardt et al., “Quality Assessment of OpenStreetMap’s Points of Interest with Large-Scale Real Data,” Transportation Research Record: Journal of the Transportation Research Board, vol. 2677, no. 12, pp. 661–674, Dec. 2023, doi: 10.1177/03611981231169280.
A. Yang, H. Fan, N. Jing, Y. Sun, and A. Zipf, “Temporal Analysis on Contribution Inequality in OpenStreetMap: A Comparative Study for Four Countries,” IJGI, vol. 5, no. 1, p. 5, Jan. 2016, doi: 10.3390/ijgi5010005.
M. Schott et al., “Analyzing and Improving the Quality and Fitness for Purpose of OpenStreetMap as Labels in Remote Sensing Applications,” in Volunteered Geographic Information, D. Burghardt, E. Demidova, and D. A. Keim, Eds., Cham: Springer Nature Switzerland, 2024, pp. 21–42. doi: 10.1007/978-3-031-35374-1_2.
J. Xu and Q. Zhou, “Temporal-spatial Analysis of Contributors’ Mapping Behavior for Building Data in OpenStreetMap,” Proc. Int. Cartogr. Assoc., vol. 2, pp. 1–10, Jul. 2019, doi: 10.5194/ica-proc-2-149-2019.
E. N. N. Elias, F. R. Amorim, M. A. R. Schmidt, and S. P. Camboim, “Exploring spatio-temporal patterns of OpenStreetMap (OSM) contributions in heterogeneous urban areas,” Bol. Ciênc. Geod., vol. 29, no. 2, p. e2023005, 2023, doi: 10.1590/s1982-21702023000200005.
J. Thebault-Spieker, B. Hecht, and L. Terveen, “Geographic Biases are ‘Born, not Made’: Exploring Contributors’ Spatiotemporal Behavior in OpenStreetMap,” in Proceedings of the 2018 ACM Conference on Supporting Groupwork, Sanibel Island Florida USA: ACM, Jan. 2018, pp. 71–82. doi: 10.1145/3148330.3148350.
How To Cite This :
Refbacks
- There are currently no refbacks.
