2026-10-13T08:00:58Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33977599 2026-09-23T19:36:36Z category_25051 item_type_3 month_year_09_2026

Dual Friction Mapping of Urban Pedestrian Spaces — Data Yusuf Eminoğlu (25099695) Kemal Mert Çubukçu (25099625) Urban informatics Pedestrian friction Street view imagery Geographically Neural Network Weighted Regression Urban Heat Island Walkability Izmir GNNWR Pedestrian Friction Index Semantic segmentation Land surface temperature Türkiye Urban planning <p dir="ltr">Supplementary data archive for: Eminoğlu, Y., Çubukçu, K.M. (2026). Dual friction mapping of urban pedestrian spaces: Integrating street-view visual analytics and Geographically Neural Network Weighted Regression in Izmir, Türkiye. Sustainable Cities and Society, 107913. https://doi.org/10.1016/j.scs.2026.107913</p><p><br></p><p dir="ltr">Code and analysis scripts are maintained separately in the public companion repository: https://gitlab.com/yusufeminoglu/pfi_paper (mirrored at https://github.com/YusufEminoglu/pfi_paper).</p><p><br></p><p dir="ltr">This archive contains: (1) six GeoPackage layers (EPSG:4326): pfi_merged (5,663 street-view points with the Pedestrian Friction Index, its components and predictors), gnnwr_results (5,663 points with GNNWR local coefficients, predictions and residuals), hex_all (8,191 H3 hexagons), hex_clustered (397 eligible hexagons with GMM morphological clusters), hex_sampled (126 sampled hexagons) and sam3_hex_summary (126 sampled hexagons with hexagon-level visual metrics); (2) processed_tables_csv.zip, the CSV tables of the analysis pipeline (merged PFI dataset, GNNWR results, SegFormer-B5 visual metrics and SAM 3 validation scores, Street View node list, thermal/park-access metrics and street-network metrics); (3) gsv_validation_sample.zip, a small illustrative sample (10 nodes x 4 directions = 40 images) of raw Google Street View crops and their SegFormer-B5/ADE20K segmentation overlays used for the SAM 3 vs. SegFormer-B5 validation exercise reported in the article.</p><p><br></p><p dir="ltr">The full Google Street View image corpus (5,663 points x 4 directions) is not redistributed here due to third-party (Google) licensing restrictions on bulk re-publication of Street View imagery; only the small illustrative validation subset above is included. Node-level metadata (node ID, coordinates, hexagon ID, district, morphological cluster) for the full corpus is included in processed_tables/sampling/gsv_nodes.csv. Additional research materials may be requested from the corresponding author.</p><p><br></p><p dir="ltr">License: the CC BY 4.0 license of this dataset applies only to material created by the authors (the GeoPackage layers and CSV tables); it does not apply to third-party Google Street View imagery in gsv_validation_sample.zip. The figures of the published article are © Elsevier and are not included.</p><p><br></p><p dir="ltr">If you use this dataset, please cite the article above together with this dataset.</p> 2026-09-23T19:36:36Z Dataset Dataset 10.6084/m9.figshare.33977599.v1 https://figshare.com/articles/dataset/Dual_Friction_Mapping_of_Urban_Pedestrian_Spaces_Data/33977599 CC BY 4.0