{"name": "LUCIA", "package_name": "lucia_cityimage", "description": "LUCIA Lynch Urban Computational Image Analyzer is a QGIS plugin for evaluating urban legibility, imageability, and cognitive urban structure using Kevin Lynch's five elements: Paths, Edges, Districts, Nodes, and Landmarks.\n\nThe plugin translates spatial proxies such as road hierarchy, path continuity, edge barriers, land use dominance, POI concentration, building coverage, building height, building occupancy, transit stops, manual landmarks, and optional Nighttime Light data into measurable city-image indicators.\n\nLUCIA produces a regular analysis grid, five-element scores, a composite Urban Legibility Index, node hotspot layers, computational city-image mapping, planning recommendations, modern PNG visualizations, CSV summaries, QGIS style files, GeoPackage outputs, JSON manifest, and an HTML report.", "about": "LUCIA Lynch Urban Computational Image Analyzer provides an integrated spatial analytics framework for diagnosing the legibility, structure, identity, and imageability of urban areas.\n\nThe plugin operationalizes Kevin Lynch's five urban image elements by measuring Path Clarity from road and movement corridor continuity, Edge Definition from linear barriers or seams, District Identity from land use and built-form coherence, Node Strength from junctions, POI concentration, transit, activity buildings, and Nighttime Light support, and Landmark Visibility from manual landmarks or inferred tall-building anchors.\n\nLUCIA extends conventional urban morphology and accessibility analysis into computational city-image analytics by combining network structure, land-use character, functional activity, building form, occupancy pattern, and optional VIIRS Nighttime Light as support evidence for urban legibility interpretation.\n\nThe plugin generates interpretable scores, legibility classes, node hotspots, recommendation themes, recommendation priorities, and map-based visual diagnostics to support urban design, spatial planning, public realm improvement, wayfinding strategy, district identity strengthening, edge/barrier treatment, and landmark reinforcement.\n\nLUCIA is designed for Kevin Lynch-based city image analysis, urban design diagnostics, cognitive mapping support, urban morphology assessment, spatial planning evaluation, placemaking strategy, corridor and node planning, district character analysis, urban legibility mapping, and evidence based planning recommendations.", "homepage": "https://github.com/firmanaf/LUCIA", "repository": "https://github.com/firmanaf/LUCIA", "tracker": "https://github.com/firmanaf/LUCIA/issues", "author": "Maya Safira, Firman Afrianto", "tags": ["poi", "paths", "spatial planning", "qgis", "points of interest", "urban planning", "urban morphology", "street network", "nodes", "land use", "transit", "network centrality", "districts", "regional planning", "nighttime light", "priority mapping", "urban design", "urban legibility", "node strength", "edges", "landmarks", "kevin lynch", "edge definition", "planning recommendation", "building occupancy", "viirs ntl", "pola ruang", "wayfinding", "lynch elements", "city image", "placemaking", "imageability", "building height", "landmark visibility", "cognitive mapping", "district character", "urban identity", "urban legibility index", "path continuity", "computational city image", "path clarity", "district identity", "landmark mapping", "junctions", "road hierarchy"], "downloads": 11, "latest_version": "1.0.0", "versions": [{"version": "1.0.0", "experimental": false, "qgis_min": "3.38.0", "qgis_max": "3.99.0", "downloads": 11, "uploaded_by": "firmanafrianto", "upload_datetime": "2026-06-28T01:13:59.057767"}]}