PlanX is the flagship of the PlanX ecosystem: a self-contained urban analytics studio for city planners and researchers. It embeds real implementations of the methods urban analysts usually need separate tools for - space syntax segment angular analysis (integration, choice, NACH/NAIN), the full centrality family (degree, closeness, straightness, eigenvector, betweenness), urban morphology (building form metrics, morphological tessellation, Spacematrix GSI/FSI/OSR, street orientation entropy), network accessibility (OD cost matrix, service-area isochrones, nearest-facility allocation, multi-amenity 15-minute-city scores with population-weighted summaries), public transport straight from a GTFS zip (feed import with clear validation errors and per-day stop/route service stats, stop frequency and headway maps for any time window, and door-to-door transit travel times that walk to a stop on the street network, ride a RAPTOR-style timetable with transfers and walk to each destination, always compared against walking all the way), accessibility-equity analysis (population-weighted Gini, a Theil index split into between- and within-group inequality, P90/P10 ratio and access-poverty share, plus a Lorenz/concentration curve export and the Atkinson index at a chosen inequality-aversion, and demographic equity cross-tabs that cut any per-unit value into population-weighted classes and report each subgroup's representation ratio among the worst- and best-served together with Duncan dissimilarity - the spatial-justice view), microclimate screening (date-and-time shadow casting with an embedded NOAA solar-position model, whole-day sun-hours maps, clear-sky daily solar irradiation combining shadow-aware beam with SVF-weighted diffuse light, annual solar potential summing twelve representative average-day sweeps into a yearly kWh/m2 map with an optional 12-band monthly raster, sky view factor, frontal area index, and a vector heat-island risk grid built from buildings, green and water layers, plus a screening-quality road noise grid: RLS-90-style emission from traffic volumes and heavy shares, line-calibrated point sampling with geometric spreading and a fixed insertion loss behind buildings, with per-receiver levels and population exposure bands), green infrastructure (park-hierarchy access that tests minimum-size-within-maximum-distance standards on real network distances with per-class population coverage, and patch connectivity with the Probability-of-Connectivity index and each patch's dPC importance - the stepping-stone argument, quantified), cycling analysis (Level of Traffic Stress 1-4 from speed, lanes, AADT and infrastructure fields with editable thresholds, plus low-stress island connectivity and destination-reach population summaries), visibility analysis (DSM viewsheds from observer points with observer and target heights, an isovist field that samples Benedikt's 2-D visibility measures - area, radials, circularity, occlusivity - on a point grid between buildings, and landmark visual exposure that counts from where a landmark's outline can be seen, the skyline/heritage screening view), plan standards QA (land-use balance against configurable per-capita standards, facility adequacy combining capacity with network distance, dasymetric density grids), the demographic backbone of plan-making (a cohort-component population projection as a Leslie matrix - per-age-group survival, fertility and net migration, rates as table fields, no locale assumptions; a housing needs assessment turning the horizon population into dwellings to deliver with vacancy allowance, replacement losses and backlog; and residential capacity that converts each parcel's FAR minus existing floorspace into whole dwelling units with a district roll-up - projection feeds needs, capacity tests whether the zoning can deliver them), a walkability studio (a Walkability Audit that scores every street segment 0-100 from the classic walkability-index ingredients - intersection density, land-use mix entropy, destination counts, block length and slope, each normalised with editable breakpoints and weights - and Pedestrian Route Quality, which routes over quality-weighted streets and reports the detour ratio, the mean walk score along the route and the share spent on low-scoring segments), location-allocation optimization (greedy maximal coverage and Teitz-Bart p-median on network distances, with candidate-site screening and support for existing facilities, plus a capacity-respecting allocation that sends demand to the nearest facility with free capacity and spills to the next when it is full, capacitated facility siting with capacity-aware Teitz-Bart swap improvement, and a multi-objective land-use allocation optimizer that assigns parcels to land uses to maximise total suitability while meeting a target area for each use, with optional compactness, adjacency, and hard contiguity objectives that shape contiguous, compatible zones, and a land-use Pareto front that runs the allocation across a sweep of compactness weights and reports the non-dominated suitability-versus-compactness trade-off with its knee, instead of committing to one weighted run), urban growth analytics (a land-cover transition matrix with per-class gains, losses and persistence in hectares; a deterministic constrained cellular-automaton growth simulation in the SLEUTH tradition - suitability times a neighbourhood term, top scorers convert until the land demand is met, same seed same map in any process - writing a year-of-conversion raster; and urban sprawl metrics around the SDG 11.3.1 land-consumption-to-population-growth ratio with patch counts, largest-patch share and edge density), seismic risk screening in four chained tools (a Ground Motion Scenario that runs the Akkar-Sandikkaya-Bommer 2014 ground-motion model - one of the four in the logic tree of Turkey's 2018 national seismic hazard map - over any receiver layer, from a point source with a focal depth or an extended fault trace, reporting peak ground acceleration, peak ground velocity and any spectral periods you name at a chosen fault mechanism, distance metric, Vs30 site velocity and epsilon, with the Joyner-Boore, epicentral or hypocentral distance written to every row, receivers whose Vs30 field is empty flagged rather than quietly given rock, and every row outside the model's published magnitude, distance, depth or site range carrying an explicit caveat code instead of being silently extrapolated; and a Hazus equivalent-PGA fragility model that turns a joined peak-ground-acceleration field - or this tool's own output - into a full none-to-complete damage distribution per building, sampled damage states, solid, bulked and tonnage debris volumes, network blockage, open evacuation corridors and a navigable core narrowed to a minimum clear vehicle width; and a Seismic Human Impact tool that carries that same damage distribution into Hazus Section 12 and Section 13, giving every building the expected injured and killed at four severities, unhoused households and people needing public shelter, with the manual's occupancy and time-of-day population shares - a school empty at 2 a.m., a hotel a fifth full at 2 p.m. - and the demographic shelter modifiers present but neutral by default, so the shelter figure is reported as an upper bound rather than a forecast; and a Liquefaction Screening that answers the ground-failure question the other three never ask - whether the soil itself loses its strength - with two published models behind one interface: the Zhu, Daley, Baise, Thompson, Wald and Knudsen 2015 logistic regression on shaking, topographic wetness and shear-wave velocity, whose wetness index and slope come from one D8 pass on a DEM and whose Vs30 comes from the slope through the Allen and Wald 2007 USGS piecewise table, a field, a raster or a constant, with the tectonic setting deliberately having no default because the table's two columns differ by a factor of 1.96 in velocity at the same slope; and the Hazus 6.1 Section 4.2.2.1 susceptibility model, Equations 4-9 to 4-11 and Tables 4-10 to 4-13, which reads a map-unit layer somebody already classified Very High to None and gives each unit the probability and the expected settlement in inches, refusing to run without that layer and refusing a category it does not recognise rather than reading it as zero - both applied exactly as printed, both reported as UNCALIBRATED for Turkish soils, and both documented as screening for planning rather than a geotechnical investigation or a code check; and a Coseismic Landslide Screening that asks the third ground-failure question - whether the hillside itself moves - with the Newmark sliding-block displacement of Jibson 2007 Equation 8, a length in centimetres rather than a probability, whose critical acceleration comes from a field you already have, from the Hazus 6.1 Section 4.2.2.2 geologic-group and susceptibility-category tables transcribed from the manual, or from a map unit somebody else already classified, and whose slope is read from a DEM in every route: dry and wet ground are up to four susceptibility categories apart at one slope and group, so the groundwater state has no default; an unset route stops the run rather than choosing one; a zero critical acceleration is refused because the regression diverges there; a Hazus category of None reports an empty acceleration rather than a zero, because zero is the value the equation blows up on; and every row carries the route it took, the ratio the regression turns on, and the p90 beside the median), and a plan dashboard/reporting workflow with live score cards in PlanX Studio, a Plan Performance Index history sparkline, one-click access to the Batch Plan Auditor (give the plan's core layers once and it chains the access, walkability, balance, adequacy, green-access and equity tools into one scenario snapshot and report), batchable scenario snapshots (auto-detected PlanX output layers captured to JSON, model-designer friendly) compared metric by metric A/B (each metric knows which direction is better), plus a one-click single-file HTML Plan Dashboard & Performance Report (inline SVG charts, balance bars and score maps - shareable with stakeholders). Everything is computed inside the plugin with NumPy (SciPy used automatically when available, identical pure-Python fallback otherwise): no QNEAT3, no GRASS dependency, no UMEP, no servers, no pip installs. All tools are Processing algorithms - model-designer and batch friendly - and every tool carries its own icon in the toolbox and the PlanX Studio dock. Developed with feedback from educational workflows at Dokuz Eylul University, Department of City and Regional Planning. Online User Manual & Documentation: https://geophilo.com/planx/ | If you find this plugin helpful, please consider starring the repository on GitLab (https://gitlab.com/geophilo1/planx)!