[general]
name=LUCIA
email=firmanafrianto@mail.ugm.ac.id
author=Maya Safira, Firman Afrianto
qgisMinimumVersion=3.38
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.

    The 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.

    LUCIA 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.

    The 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.

    LUCIA 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.

    The 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.

    LUCIA 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.

version=1.0.0
tracker=https://github.com/firmanaf/LUCIA/issues
repository=https://github.com/firmanaf/LUCIA

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; start of optional metadata
category=Urban and Regional Planning Analysis
changelog=1.0.0 - Initial release of LUCIA Lynch Urban Computational Image Analyzer.
tags=urban legibility,imageability,Kevin Lynch,Lynch elements,city image,computational city image,urban morphology,urban design,spatial planning,regional planning,urban planning,paths,edges,districts,nodes,landmarks,path clarity,edge definition,district identity,node strength,landmark visibility,urban legibility index,road hierarchy,path continuity,street network,junctions,network centrality,POI,points of interest,land use,pola ruang,building height,building occupancy,transit,landmark mapping,Nighttime Light,VIIRS NTL,wayfinding,placemaking,district character,urban identity,cognitive mapping,planning recommendation,priority mapping,QGIS
homepage=https://github.com/firmanaf/LUCIA
icon=icon.png
experimental=False
deprecated=False
qgisMaximumVersion=3.99
