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+++ b/.gitignore
@@ -1 +1,2 @@
 node_modules/
+raw/
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diff --git a/README.md b/README.md
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--- a/README.md
+++ b/README.md
@@ -1 +1,127 @@
-Add a readme for your dashboard here. Include content overview, data citations, and any relevant technical details.
\ No newline at end of file
+# Houston Grocery Gap
+
+This is a decision support tool for decisionmakers to assess and plan where to put new grocery stores in and around the city of Houston. It maps where Harris County residents live far from a grocery store, ranks the places a new store would do the most good (based on the data available), and lets staff test a recruitment plan against a budget.
+
+The live tool is at https://gbd2.github.io/dashboard-project/.
+
+## Who is this tool for?
+
+The main users are City of Houston and Harris County economic development staff, and the councils they report to who decide where/how recruitment incentives will get spent.
+
+The secondary users are grocers' site selection teams. Grocery profit margins are tight, so staff have to make a case to a chain, and a chain wants to know whether a location can support a store, not only whether it needs one.
+
+## What decisions does it support?
+
+The question a decisionmaker will typically start with is where grocery access is worst and how many people that affects, so the first step maps low income + low access tracts and lets you change what counts as a grocery store (as there are varying definitions). Need alone will not recruit a grocery chain, though. The second step weighs need against the size of the local market and whether incentives apply there, using weights you set, and produces a shortlist. Before any funds are put towards an initiative, staff need to know what the impact is of a specific deal, so the last step lets you place stores within a fixed fund and see who they reach, what they would likely sell and what the city gets back in tax revenues.
+
+## What one can find with the tool
+
+USDA's new 2025 food access map counts every SNAP-authorized store as food access, including convenience stores, dollar stores and pharmacies. By that measure only 8 tracts in Harris County are low income and low access. Count only supermarkets, supercenters and large grocers, the same store types USDA's own older map used, and the number is 175 tracts with about 759,000 residents. Of the 3,547 SNAP stores USDA lists in Harris County, 2,027 are convenience stores. So, someone relying on the official definition of what food access is today would conclude there's little need, though the majority of these c-stores are not sufficient to eliminate food insecurity in an area.
+
+Also, nearly all of a new store's sales come from shoppers who already buy groceries somewhere nearby when modeled. Though, there is an innate bias built into the model's data, as new shoppers that would choose the new store are not fully represented since they might not be getting groceries on a regular schedule if they have no means of getting to another grocery store. If those residents shifted from eating out to cooking at home, that would actually cost the city a little sales tax, since restaurant meals are taxed and groceries aren't. Further, Texas doesn't tax groceries for home use, so only about 28% of a grocery store's sales are taxable. At a typical top-ranked site inside city limits, a new supermarket would sell about $30 million a year, and the city would collect about $148,000 a year from it in sales and property tax, which repays a $3 million incentive in about 20 years. Counting only sales that are new to the city, it's about $63,000 a year, mostly property tax, and about 48 years. The return on a grocery incentive is the residents it reaches.
+
+## How it works
+
+### Step 1: find the gaps
+
+A tract is low access when at least 500 people, or a third of its residents, live more than 1 mile from a store (10 miles in rural tracts). Distances are measured from the center of every populated 2020 census block rather than from the middle of each census tract to get more representative distances. Low income follows USDA's tract definition.
+
+### Step 2: rank sites
+
+Each tract is scored from 0 to 100 on need, viability and incentives:
+
+- Need averages three percentile ranks: residents beyond reach of a grocery store, car-free households among them, and the poverty rate.
+- Viability is the yearly grocery spending of residents within 2 miles who have no store within reach, which is the sales a new store could win without taking them from an existing one.
+- Incentives is 100 for a tract nominated as a 2027 Opportunity Zone, 50 for an eligible tract, and 0 otherwise.
+
+The shortlist skips any tract within 2 miles of a higher pick, because one store would serve both.
+
+### Step 3: test a plan
+
+Stores can go only in food desert or Opportunity Zone eligible tracts. Each one draws its incentive from the fund. Sales come from a Huff model: each block's grocery spending is split among the stores within 5 miles by store size over distance squared, with an outside option standing in for online orders and farther stores.
+
+The Consumer Expenditure Survey's grocery spending runs low against real sales, and it leaves out everything a store sells besides food, so the model scales it up in two steps. First it's multiplied by 1.39, which makes Harris County's grocery stores and supercenters add up to their 2022 Economic Census sales: $13.2 billion at 836 supermarkets and other grocers, and $8.7 billion at 82 warehouse clubs and supercenters. That step takes food as 80% of a supermarket's sales and 45% of a supercenter's, the second based on Walmart's reported mix after taking out paper goods, cleaning supplies and other nonfood items it counts as grocery. Then it's divided by groceries' share of store sales, 80%, to get total store sales. A store below the sales it needs to stay open is flagged.
+
+City revenue is the city's 1% sales tax plus property tax on the building. Everything a store sells besides groceries is taxable, and so is 10% of its groceries (soda, candy and hot food), which makes 28% of sales taxable. That matches Texas: the Comptroller's 2022 sales tax collections from food stores, set against Census sales, work out to about 26 to 30% taxable once liquor and convenience stores are left out. The tool shows two paybacks, one on all the tax the stores collect and one on only the sales that are new to the city, leaving out sales taken from existing stores. Stores outside city limits bring the City of Houston nothing. The incentive amounts, sales floors, building values and both grocery shares are planning estimates, and are editable in the tool.
+
+Plans save to the browser. Export and import them as JSON to share with others!
+
+## The data
+
+All data the tool shows comes from seven files in `data/`, built ahead of time from public sources alongside Claude Opus 5.5 via a Python script (geopandas, pandas, numpy and scipy).
+
+| File | What it holds | Size |
+|---|---|---|
+| `tracts.geojson` | All 1,115 Harris County census tracts (2020 boundaries) with population, households, income, poverty, car-free and SNAP households, distance to groceries, food desert flags under both definitions, Opportunity Zone status, estimated grocery spending, the three site scores and a neighborhood name | 1.2 MB |
+| `blocks.json` | 37,201 populated 2020 census blocks: location, population, tract, distance to the nearest grocery store, whether a bus stop is within a quarter mile, its pull toward existing stores and its grocery spending | 1.8 MB |
+| `stores.geojson` | 4,224 SNAP-authorized stores in and within 10 miles of the county, each tagged grocery store, small grocer, dollar store or pharmacy, or convenience store | 0.9 MB |
+| `stops.json` | 8,803 METRO stop locations | 0.2 MB |
+| `houston-city.geojson` | City of Houston limits, to tell which stores bring the city tax revenue | 0.2 MB |
+| `harris-boundary.geojson`, `harris-mask.geojson` | The county outline and the mask that dims everything outside it | under 0.1 MB |
+
+The census tract is the unit because it's the smallest area every source shares. USDA's food access data, the Opportunity Zone designations and the income and poverty estimates are all published by 2020 tract, so they join on one ID with nothing to reconcile. The story map project mixed 2010 and 2020 boundaries. This one doesn't.
+
+Tracts are too coarse for distance, though. An outer Harris County tract can be several miles across, and measuring from its middle would treat residents who live next to a store the same as residents two miles out. So distance and reach are measured from census blocks, often a single city block, and summed up to tracts. Blocks are also what make step 3 honest: when someone places a store, the tool counts exactly which residents are now within a mile.
+
+Anything that doesn't change while someone uses the tool is computed ahead of time in Python, including distances, food desert flags, spending, scores and neighborhood names. The browser only does the math that depends on what the user does: reweighting scores, spacing the shortlist and evaluating a plan. That keeps the page fast and the files small. Blocks are stored as plain arrays instead of GeoJSON because only their center points are needed, which cuts the file to about a quarter of the size. Tract shapes are simplified to roughly 25 meters of detail, plenty for a county map.
+
+### Where the raw data and build script live
+
+The raw downloads are kept out of the repository, because the SNAP retailer file alone is 95 MB. The build script is `scripts/build_data.py`. The files in `data/` are everything the site needs to run.
+
+To rebuild the data, download each source in the "Data sources" section below into its own folder in `raw/`, using the folder and file names the build script reads, then run `python3 scripts/build_data.py` with geopandas, pandas, numpy and scipy installed.
+
+Data cleaning and processing for this project, including the build script, the food access and scoring calculations and the data checks, were done by Claude Opus 5.5 (Anthropic) working with Gavin Daves.
+
+## Data sources
+
+- **Grocery access.** U.S. Department of Agriculture, Economic Research Service. [Food Access Research Atlas](https://www.ers.usda.gov/data-products/food-access-research-atlas): SNAP-authorized Retailer Access Map, 2025 data, released July 2026, on 2020 census tracts.
+- **Store locations.** USDA Food and Nutrition Service. [Historical SNAP Retailer Locator Data](https://www.fns.usda.gov/snap/retailer-locator/data), stores authorized as of December 31, 2025.
+- **Where people live.** U.S. Census Bureau. 2020 Census block populations, via [TIGERweb](https://tigerweb.geo.census.gov/arcgis/rest/services/TIGERweb/tigerWMS_Census2020/MapServer).
+- **Income, poverty and vehicles.** [American Community Survey](https://www.census.gov/programs-surveys/acs) 2020 to 2024 5-year estimates, as published in the USDA and Texas files.
+- **Opportunity Zones.** Office of the Texas Governor, Economic Development and Tourism. [Opportunity Zone 2.0](https://gov.texas.gov/business/page/opportunity-zones) nominated and eligible tracts, September 2026, from the office's [public map layer](https://services6.arcgis.com/qBPMNP2zACwkFVPe/arcgis/rest/services/Opportunity_Zones_2.0_(EDT_Recommended_Tracts)/FeatureServer/0). The nominations are pending U.S. Treasury certification.
+- **Grocery spending.** U.S. Bureau of Labor Statistics. [Consumer Expenditure Survey](https://www.bls.gov/cex/tables/calendar-year/mean-item-share-average-standard-error.htm) 2024, food at home by income quintile.
+- **Store sales.** U.S. Census Bureau. [2022 Economic Census, retail trade](https://data.census.gov/table/ECNBASIC2022.EC2244BASIC) (table EC2244BASIC), sales and establishments by industry for Harris County.
+- **Taxable sales.** Texas Comptroller of Public Accounts. [Sales tax receipts by retail subsector](https://comptroller.texas.gov/transparency/revenue/watch/naics/naics-retail.php), fiscal 2022 and 2023.
+- **Supercenter sales mix.** Walmart Inc. [Form 10-K for fiscal 2025](https://www.sec.gov/Archives/edgar/data/104169/000010416925000021/wmt-20250131.htm), Walmart U.S. net sales by merchandise category.
+- **Neighborhood names.** City of Houston Planning and Development, [Super Neighborhoods](https://services2.arcgis.com/LYMgRMwHfrWWEg3s/arcgis/rest/services/City_Of_Houston_Super_Neighborhoods/FeatureServer). U.S. Census Bureau 2020 incorporated and census-designated places, via [TIGERweb](https://tigerweb.geo.census.gov/arcgis/rest/services/TIGERweb/tigerWMS_Census2020/MapServer). U.S. Geological Survey, [Geographic Names Information System](https://carto.nationalmap.gov/arcgis/rest/services/geonames/MapServer), for the remaining unincorporated tracts.
+- **Tax rates.** City of Houston, [tax year 2025 adopted property tax rate](https://www.houstontx.gov/2025-tax-rate/TY25-Notice-Meeting-Vote-Tax-Rate.pdf) ($0.519190 per $100). Texas Comptroller of Public Accounts, [sales tax guidance for grocery and convenience stores](https://comptroller.texas.gov/taxes/publications/96-280.php).
+- **Transit.** Metropolitan Transit Authority of Harris County. GTFS schedule data for the August 30, 2026 service change, via the [Mobility Database](https://mobilitydatabase.org/feeds/gtfs/mdb-2060).
+- **Basemap.** [Esri World Light Gray Canvas](https://server.arcgisonline.com/ArcGIS/rest/services/Canvas/World_Light_Gray_Base/MapServer), with data from HERE, Garmin and OpenStreetMap contributors.
+
+## Running it locally
+
+The site is static HTML, CSS and JavaScript with no build step. Serve the repository root with any static server:
+
+```bash
+npx http-server . -p 8080
+```
+
+Then open http://localhost:8080. Opening `index.html` straight from the file system won't work, because the browser blocks the data requests.
+
+## Project structure
+
+```
+index.html            page structure and the three steps
+css/index.css         all styles
+js/main.js            sets up the map, loads data, wires the steps together
+js/tracts.js          tract layer and its colors in each step
+js/headline.js        step 1 counts under both definitions
+js/stores.js          store dots by category
+js/scores.js          site scores and the spaced shortlist
+js/rank.js            step 2 sliders, shortlist and markers
+js/model.js           step 3 model: reach, Huff sales, city revenue
+js/results.js         step 3 results: reach, where sales come from, payback
+js/plan.js            step 3 interface, saving and comparing plans
+js/geo.js             distances and point-in-polygon
+js/profile.js         tract details panel
+js/legend.js          map legend for each step
+js/format.js          number formatting
+data/                 browser-ready data built by the script
+scripts/build_data.py data build from the raw downloads
+mockup/               the original sketch of the layout
+```
+
+## Credits
+
+Built by Gavin Daves for MUSA 6110, JavaScript for City Planning, at the University of Pennsylvania. Data cleaning and processing by Claude Opus 5.5 (Anthropic).
diff --git a/css/index.css b/css/index.css
new file mode 100644
index 00000000..a03d0bcc
--- /dev/null
+++ b/css/index.css
@@ -0,0 +1,1016 @@
+*,
+*::before,
+*::after {
+  box-sizing: border-box;
+}
+
+html,
+body {
+  height: 100%;
+  margin: 0;
+}
+
+/* Without these, browsers and extensions that darken pages can leave dark text on a dark page. */
+body {
+  background-color: #e9ebe6;
+  color: #1a211d;
+  font-family: 'Public Sans', system-ui, sans-serif;
+  line-height: 1.5;
+}
+
+.app-content {
+  display: grid;
+  grid-template-columns: 25rem 1fr;
+  height: 100vh;
+}
+
+/* Positioned so hidden inputs sit inside the rail's scroll instead of stretching the page. */
+.rail {
+  position: relative;
+  min-width: 0;
+  padding: 1.4rem 1.25rem;
+  overflow-y: auto;
+  border-right: 1px solid rgb(18 26 22 / 13%);
+  background-color: #f8f9f6;
+}
+
+h1 {
+  margin: 0 0 0.5rem;
+  font-size: 1.6rem;
+  font-weight: 800;
+  line-height: 1.12;
+  letter-spacing: -0.015em;
+  text-wrap: balance;
+}
+
+h2 {
+  margin: 0 0 0.65rem;
+  font-size: 0.95rem;
+  font-weight: 700;
+  line-height: 1.25;
+}
+
+/* Sections stack as flat bands split by hairlines, not boxed cards. */
+.panel {
+  padding: 1.1rem 0;
+  border-top: 1px solid rgb(18 26 22 / 13%);
+}
+
+/* The tabs already draw a line above whichever step is showing. */
+.panel[role='tabpanel'] {
+  border-top: 0;
+}
+
+.note {
+  margin: 0.75rem 0 0;
+  color: #545e58;
+  font-size: 0.85rem;
+}
+
+.tip-type {
+  display: block;
+  color: #545e58;
+  font-size: 0.72rem;
+}
+
+.map-wrap {
+  position: relative;
+  min-height: 0;
+}
+
+.map {
+  height: 100%;
+  background-color: #e9ebe6;
+}
+
+.leaflet-tooltip {
+  font-family: 'Public Sans', system-ui, sans-serif;
+}
+
+.layer-list {
+  display: flex;
+  flex-direction: column;
+  gap: 0.15rem;
+  margin: 0;
+  padding: 0;
+  list-style: none;
+}
+
+.layer-toggle {
+  display: grid;
+  grid-template-columns: auto auto 1fr auto;
+  align-items: center;
+  gap: 0.55rem;
+  padding: 0.3rem 0.25rem;
+  border-radius: 0.35rem;
+  font-size: 0.9rem;
+  cursor: pointer;
+}
+
+.layer-toggle:hover {
+  background-color: #e9ebe6;
+}
+
+.layer-toggle input {
+  margin: 0;
+  accent-color: #1f7a4d;
+}
+
+.layer-count {
+  color: #545e58;
+  font-size: 0.75rem;
+  font-variant-numeric: tabular-nums;
+}
+
+.swatch {
+  display: inline-block;
+  flex: 0 0 auto;
+  width: 0.75rem;
+  height: 0.75rem;
+}
+
+.swatch.dot {
+  border: 1.5px solid #fff;
+  border-radius: 50%;
+  box-shadow: 0 0 0 1px rgb(18 26 22 / 25%);
+}
+
+.swatch.fill {
+  border: 1px solid rgb(18 26 22 / 25%);
+  border-radius: 0.15rem;
+}
+
+.swatch[data-cat='grocery'] { background-color: #1f7a4d; }
+.swatch[data-cat='small'] { background-color: #2f8f9d; }
+.swatch[data-cat='dollar'] { background-color: #b0457b; }
+.swatch[data-cat='convenience'] { background-color: #8a8f96; }
+
+.legend {
+  position: absolute;
+  right: 0.75rem;
+  bottom: 1.75rem;
+  z-index: 500;
+  padding: 0.6rem 0.75rem;
+  border: 1px solid #d6dad3;
+  border-radius: 0.5rem;
+  background-color: rgb(255 255 255 / 94%);
+  font-size: 0.78rem;
+}
+
+.legend-title {
+  margin: 0 0 0.35rem;
+  font-weight: 700;
+}
+
+.legend-row {
+  display: flex;
+  align-items: center;
+  gap: 0.45rem;
+  margin: 0.15rem 0 0;
+}
+
+.visually-hidden {
+  position: absolute;
+  width: 1px;
+  height: 1px;
+  overflow: hidden;
+  clip-path: inset(50%);
+  white-space: nowrap;
+}
+
+:focus-visible {
+  outline: 2px solid #b86e00;
+  outline-offset: 2px;
+}
+
+.nowrap {
+  white-space: nowrap;
+}
+
+.choice {
+  display: flex;
+  flex-direction: column;
+  gap: 0.2rem;
+  margin: 0;
+  padding: 0;
+  border: 0;
+}
+
+.choice-row {
+  display: flex;
+  align-items: flex-start;
+  gap: 0.6rem;
+  padding: 0.35rem 0;
+  cursor: pointer;
+}
+
+.choice-row input {
+  flex: 0 0 auto;
+  width: 1rem;
+  height: 1rem;
+  margin: 0.2rem 0 0;
+}
+
+.choice-text {
+  display: flex;
+  flex: 1 1 auto;
+  flex-direction: column;
+  min-width: 0;
+}
+
+.choice-name {
+  font-weight: 700;
+}
+
+.choice-meta {
+  color: #545e58;
+  font-size: 0.8rem;
+}
+
+.headline {
+  margin-top: 1rem;
+}
+
+.stat-number {
+  margin: 0;
+  color: #c4441c;
+  font-size: 2.6rem;
+  font-weight: 800;
+  line-height: 1;
+  font-variant-numeric: tabular-nums;
+}
+
+.stat-label {
+  margin: 0.3rem 0 0;
+  font-weight: 600;
+}
+
+.stat-sub {
+  margin: 0.35rem 0 0;
+  color: #545e58;
+  font-size: 0.82rem;
+}
+
+
+.profile-name {
+  margin: 0 0 0.75rem;
+  font-size: 1.15rem;
+  font-weight: 700;
+}
+
+.facts {
+  display: grid;
+  grid-template-columns: 1fr auto;
+  gap: 0.35rem 1rem;
+  margin: 0;
+}
+
+.facts dt {
+  color: #545e58;
+  font-size: 0.85rem;
+}
+
+.facts dd {
+  margin: 0;
+  font-size: 0.85rem;
+  font-variant-numeric: tabular-nums;
+  text-align: right;
+}
+
+.sources summary {
+  font-size: 0.95rem;
+  font-weight: 700;
+  cursor: pointer;
+}
+
+.source-list {
+  display: flex;
+  flex-direction: column;
+  gap: 0.5rem;
+  margin: 0.75rem 0 0;
+  padding-left: 1rem;
+  font-size: 0.82rem;
+}
+
+
+.tabs {
+  display: grid;
+  grid-template-columns: repeat(3, 1fr);
+  margin-top: 0.6rem;
+  border-bottom: 1px solid rgb(18 26 22 / 13%);
+}
+
+/* The selected step is underlined, sitting on the line below the tabs. */
+.tab {
+  margin-bottom: -1px;
+  padding: 0.6rem 0.25rem 0.55rem;
+  border: 0;
+  border-bottom: 2px solid transparent;
+  background-color: transparent;
+  color: #545e58;
+  font: inherit;
+  font-size: 0.85rem;
+  font-weight: 600;
+  line-height: 1.2;
+  text-align: left;
+  cursor: pointer;
+}
+
+.tab:hover {
+  color: #1a211d;
+}
+
+.tab[aria-selected='true'] {
+  border-bottom-color: #1a211d;
+  color: #1a211d;
+}
+
+.weights {
+  display: flex;
+  flex-direction: column;
+  gap: 0.85rem;
+  margin-top: 0.85rem;
+}
+
+.weight label {
+  display: flex;
+  justify-content: space-between;
+  align-items: baseline;
+}
+
+.weight-name {
+  font-weight: 700;
+}
+
+.weight-value {
+  color: #14525e;
+  font-size: 0.8rem;
+  font-variant-numeric: tabular-nums;
+}
+
+.weight input {
+  width: 100%;
+  margin: 0.2rem 0 0;
+  accent-color: #14525e;
+}
+
+.weight-help {
+  margin: 0.1rem 0 0;
+  color: #545e58;
+  font-size: 0.8rem;
+  line-height: 1.4;
+}
+
+.shortlist-heading {
+  margin-top: 1.25rem;
+}
+
+.shortlist {
+  margin: 0;
+  padding: 0;
+  border-top: 1px solid rgb(18 26 22 / 13%);
+  list-style: none;
+}
+
+.shortlist li {
+  border-bottom: 1px solid rgb(18 26 22 / 13%);
+}
+
+.pick {
+  display: flex;
+  flex-direction: column;
+  gap: 0.2rem;
+  width: 100%;
+  padding: 0.65rem 0.15rem;
+  border: 0;
+  background-color: transparent;
+  color: #1a211d;
+  font: inherit;
+  text-align: left;
+  cursor: pointer;
+}
+
+.pick:hover {
+  background-color: rgb(18 26 22 / 3%);
+}
+
+.pick-head {
+  display: flex;
+  align-items: baseline;
+  gap: 0.55rem;
+}
+
+.pick-rank {
+  min-width: 1.1rem;
+  color: #545e58;
+  font-size: 0.8rem;
+  font-variant-numeric: tabular-nums;
+}
+
+.pick-name {
+  flex: 1 1 auto;
+  font-weight: 700;
+}
+
+.pick-score {
+  color: #14525e;
+  font-size: 1.05rem;
+  font-weight: 800;
+  font-variant-numeric: tabular-nums;
+}
+
+.pick-facts {
+  padding-left: 1.65rem;
+  color: #545e58;
+  font-size: 0.78rem;
+}
+
+.rank-marker {
+  border: 0;
+  background: none;
+}
+
+.rank-key,
+.rank-num {
+  display: inline-grid;
+  place-items: center;
+  width: 1.5rem;
+  height: 1.5rem;
+  border-radius: 50%;
+  background-color: #1a211d;
+  color: #fff;
+  font-size: 0.75rem;
+  font-weight: 500;
+  font-variant-numeric: tabular-nums;
+}
+
+.rank-num {
+  border: 2px solid #fff;
+  box-shadow: 0 1px 4px rgb(0 0 0 / 35%);
+}
+
+.rank-key {
+  width: 1rem;
+  height: 1rem;
+  font-size: 0.6rem;
+}
+
+.shortlist-options {
+  display: flex;
+  flex-direction: column;
+  gap: 0.3rem;
+  margin: 1rem 0 0;
+  padding-top: 0.85rem;
+  border-top: 1px solid #d6dad3;
+}
+
+.check {
+  display: flex;
+  align-items: center;
+  gap: 0.5rem;
+  font-size: 0.88rem;
+  cursor: pointer;
+}
+
+.check input {
+  margin: 0;
+  accent-color: #14525e;
+}
+
+.choice-head {
+  margin: 0;
+  color: #545e58;
+  font-size: 0.72rem;
+  text-align: right;
+}
+
+.choice-count {
+  color: #545e58;
+  font-size: 1.9rem;
+  font-weight: 800;
+  line-height: 1;
+  font-variant-numeric: tabular-nums;
+}
+
+.choice-row:has(input:checked) .choice-count {
+  color: #c4441c;
+}
+
+.profile-tract {
+  margin: 0 0 0.75rem;
+  color: #545e58;
+  font-size: 0.75rem;
+  font-variant-numeric: tabular-nums;
+}
+
+.pick-tract {
+  color: #545e58;
+  font-size: 0.75rem;
+  font-weight: 400;
+  font-variant-numeric: tabular-nums;
+}
+
+.sub-heading {
+  margin: 1.1rem 0 0.5rem;
+  font-size: 0.88rem;
+  font-weight: 700;
+}
+
+.format-choice {
+  display: grid;
+  grid-template-columns: 1fr 1fr;
+  gap: 0.4rem;
+  margin: 0.85rem 0 0;
+  padding: 0;
+  border: 0;
+}
+
+.format-choice legend {
+  margin-bottom: 0.35rem;
+  font-size: 0.85rem;
+  font-weight: 700;
+}
+
+.format {
+  position: relative;
+  display: flex;
+  flex-direction: column;
+  gap: 0.1rem;
+  padding: 0.55rem 0.6rem;
+  border: 1px solid rgb(18 26 22 / 13%);
+  border-radius: 0.45rem;
+  cursor: pointer;
+}
+
+.format input {
+  position: absolute;
+  opacity: 0;
+}
+
+.format:has(input:checked) {
+  border-color: #1f7a4d;
+  box-shadow: inset 0 0 0 1px #1f7a4d;
+  background-color: rgb(31 122 77 / 6%);
+}
+
+.format:has(input:focus-visible) {
+  outline: 2px solid #b86e00;
+  outline-offset: 2px;
+}
+
+.format-name {
+  font-size: 0.88rem;
+  font-weight: 700;
+}
+
+.format-meta {
+  color: #545e58;
+  font-size: 0.75rem;
+}
+
+.site-picker {
+  margin-top: 0.75rem;
+}
+
+.site-picker label {
+  display: block;
+  margin-bottom: 0.3rem;
+  font-size: 0.82rem;
+  font-weight: 600;
+}
+
+.site-picker-row {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 0.4rem;
+}
+
+.site-picker select {
+  flex: 1 1 100%;
+  min-width: 0;
+  padding: 0.35rem 1.6rem 0.35rem 0.4rem;
+  border: 1px solid rgb(18 26 22 / 13%);
+  border-radius: 0.4rem;
+  background-color: #fff;
+  background-image: url("data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' width='10' height='6'%3E%3Cpath d='M1 1l4 4 4-4' fill='none' stroke='%231a211d' stroke-width='1.5'/%3E%3C/svg%3E");
+  background-repeat: no-repeat;
+  background-position: right 0.55rem center;
+  color: #1a211d;
+  font: inherit;
+  font-size: 0.82rem;
+  appearance: none;
+}
+
+.budget {
+  margin-top: 0.9rem;
+}
+
+.budget-line {
+  display: flex;
+  justify-content: space-between;
+  gap: 0.5rem;
+  font-size: 0.85rem;
+  font-weight: 600;
+}
+
+.budget-amount {
+  color: #545e58;
+  font-size: 0.75rem;
+  font-weight: 400;
+  font-variant-numeric: tabular-nums;
+}
+
+.budget-track {
+  height: 0.5rem;
+  margin-top: 0.3rem;
+  overflow: hidden;
+  border-radius: 0.25rem;
+  background-color: #e9ebe6;
+}
+
+.budget-fill {
+  display: block;
+  width: 0;
+  height: 100%;
+  background-color: #1f7a4d;
+  transition: width 0.2s ease;
+}
+
+.plan-message {
+  min-height: 1.2em;
+  margin: 0.6rem 0 0;
+  color: #165c3a;
+  font-size: 0.82rem;
+  font-weight: 600;
+}
+
+.plan-stores {
+  margin: 0;
+  padding: 0;
+  border-top: 1px solid rgb(18 26 22 / 13%);
+  list-style: none;
+}
+
+.plan-store {
+  display: grid;
+  grid-template-columns: auto 1fr auto;
+  align-items: center;
+  gap: 0.55rem;
+  padding: 0.5rem 0;
+  border-bottom: 1px solid rgb(18 26 22 / 13%);
+}
+
+.plan-pin {
+  display: inline-grid;
+  place-items: center;
+  width: 1.6rem;
+  height: 1.6rem;
+  border: 2px solid #fff;
+  border-radius: 0.35rem;
+  background-color: #1f7a4d;
+  box-shadow: 0 1px 4px rgb(0 0 0 / 35%);
+  color: #fff;
+  font-size: 0.75rem;
+  font-variant-numeric: tabular-nums;
+}
+
+.plan-pin.is-small {
+  border-radius: 50%;
+}
+
+.plan-pin.is-weak {
+  background-color: #9b2c12;
+}
+
+.plan-marker {
+  border: 0;
+  background: none;
+  cursor: grab;
+}
+
+.legend-ring {
+  display: inline-block;
+  width: 0.75rem;
+  height: 0.75rem;
+  border: 1.5px dashed #1f7a4d;
+  border-radius: 50%;
+}
+
+.plan-actions {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 0.4rem;
+  margin-top: 0.75rem;
+}
+
+.btn {
+  padding: 0.4rem 0.75rem;
+  border: 1px solid rgb(18 26 22 / 13%);
+  border-radius: 0.4rem;
+  background-color: #f8f9f6;
+  color: #1a211d;
+  font: inherit;
+  font-size: 0.82rem;
+  font-weight: 600;
+  cursor: pointer;
+}
+
+.btn:hover {
+  border-color: #1a211d;
+}
+
+.btn.small {
+  padding: 0.2rem 0.5rem;
+  font-size: 0.75rem;
+}
+
+.plan-store-main {
+  display: flex;
+  flex-direction: column;
+  min-width: 0;
+}
+
+.plan-store-name {
+  font-size: 0.85rem;
+  font-weight: 700;
+}
+
+.plan-store-facts {
+  color: #545e58;
+  font-size: 0.72rem;
+}
+
+.plan-store-facts .weak {
+  color: #9b2c12;
+  font-weight: 700;
+}
+
+.results {
+  margin-top: 0.75rem;
+}
+
+.lead-number {
+  margin: 0;
+  color: #1f7a4d;
+  font-size: 2.2rem;
+  font-weight: 800;
+  line-height: 1;
+  font-variant-numeric: tabular-nums;
+}
+
+.lead-label {
+  margin: 0.3rem 0 0;
+  font-weight: 600;
+}
+
+.lead-sub {
+  margin: 0.2rem 0 0;
+  color: #545e58;
+  font-size: 0.82rem;
+}
+
+.ledger-group {
+  margin: 1rem 0 0.3rem;
+  color: #545e58;
+  font-size: 0.8rem;
+  font-weight: 700;
+}
+
+/* Gray is sales moved from stores already there; green is spending the area wasn't getting. */
+.split {
+  display: flex;
+  height: 0.75rem;
+  overflow: hidden;
+  border-radius: 0.2rem;
+}
+
+.split-old,
+.key-old {
+  background-color: #8a8f96;
+}
+
+.split-new,
+.key-new {
+  background-color: #1f7a4d;
+}
+
+.split-key {
+  display: flex;
+  flex-wrap: wrap;
+  justify-content: space-between;
+  gap: 0.25rem 1rem;
+  margin: 0.35rem 0 0;
+  color: #545e58;
+  font-size: 0.78rem;
+}
+
+.split-key i {
+  display: inline-block;
+  width: 0.6rem;
+  height: 0.6rem;
+  margin-right: 0.35rem;
+}
+
+.payback {
+  margin: 0 0 0.6rem;
+  font-size: 0.88rem;
+}
+
+.payback b {
+  font-size: 1.2rem;
+  font-weight: 800;
+  white-space: nowrap;
+}
+
+.payback-note {
+  margin: 0 0 0.6rem;
+  color: #545e58;
+  font-size: 0.8rem;
+}
+
+.ledger {
+  margin: 0;
+  border-top: 1px solid rgb(18 26 22 / 13%);
+}
+
+.ledger div {
+  display: flex;
+  justify-content: space-between;
+  align-items: baseline;
+  gap: 1rem;
+  padding: 0.35rem 0;
+  border-bottom: 1px solid rgb(18 26 22 / 13%);
+  font-size: 0.85rem;
+}
+
+.ledger dd {
+  margin: 0;
+  font-variant-numeric: tabular-nums;
+  text-align: right;
+  white-space: nowrap;
+}
+
+.assumptions {
+  margin-top: 1rem;
+  padding-top: 0.75rem;
+  border-top: 1px solid rgb(18 26 22 / 13%);
+}
+
+.assumptions summary {
+  font-size: 0.88rem;
+  font-weight: 700;
+  cursor: pointer;
+}
+
+.assume-grid {
+  display: grid;
+  grid-template-columns: 1fr 5rem;
+  align-items: center;
+  gap: 0.35rem 0.6rem;
+  margin-top: 0.6rem;
+  font-size: 0.8rem;
+}
+
+.assume-grid input {
+  width: 100%;
+  padding: 0.25rem 0.4rem;
+  border: 1px solid rgb(18 26 22 / 13%);
+  border-radius: 0.3rem;
+  font: inherit;
+  font-variant-numeric: tabular-nums;
+  text-align: right;
+}
+
+.btn.primary {
+  border-color: #1f7a4d;
+  background-color: #1f7a4d;
+  color: #fff;
+}
+
+label.btn:has(+ input:focus-visible) {
+  outline: 2px solid #b86e00;
+  outline-offset: 2px;
+}
+
+.plan-actions input[type='text'] {
+  flex: 1 1 8rem;
+  min-width: 0;
+  padding: 0.4rem 0.55rem;
+  border: 1px solid rgb(18 26 22 / 13%);
+  border-radius: 0.4rem;
+  font: inherit;
+  font-size: 0.85rem;
+}
+
+.compare-wrap {
+  overflow-x: auto;
+}
+
+.compare {
+  width: 100%;
+  border-collapse: collapse;
+  font-size: 0.78rem;
+}
+
+.compare th,
+.compare td {
+  padding: 0.35rem 0.4rem;
+  border-bottom: 1px solid rgb(18 26 22 / 13%);
+  text-align: left;
+  vertical-align: middle;
+}
+
+.compare thead th {
+  color: #545e58;
+  font-size: 0.7rem;
+  font-weight: 600;
+}
+
+.compare .num {
+  text-align: right;
+  font-variant-numeric: tabular-nums;
+}
+
+.row-actions {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 0.25rem;
+  justify-content: flex-end;
+}
+
+.map-status {
+  position: absolute;
+  top: 50%;
+  left: 50%;
+  z-index: 600;
+  max-width: 20rem;
+  margin: 0;
+  padding: 0.6rem 0.85rem;
+  border: 1px solid rgb(18 26 22 / 13%);
+  background-color: #fff;
+  font-size: 0.9rem;
+  text-align: center;
+  transform: translate(-50%, -50%);
+}
+
+.map-status.is-error {
+  border-color: #9b2c12;
+  color: #9b2c12;
+  font-weight: 600;
+}
+
+@media (prefers-reduced-motion: reduce) {
+  .budget-fill {
+    transition: none;
+  }
+}
+
+/* Phone has map on top with controls scroll below it. */
+@media (width <= 760px) {
+  .app-content {
+    grid-template-columns: minmax(0, 1fr);
+    grid-template-rows: 55vh auto;
+    height: auto;
+  }
+
+  .map-wrap {
+    order: -1;
+  }
+
+  .rail {
+    overflow-y: visible;
+    border-right: 0;
+  }
+
+  .legend {
+    right: 0.5rem;
+    bottom: 2.25rem;
+    padding: 0.4rem 0.55rem;
+    font-size: 0.68rem;
+  }
+
+  .tab,
+  .btn,
+  .layer-toggle,
+  .check,
+  .choice-row,
+  .site-picker select,
+  .plan-actions input[type='text'] {
+    min-height: 2.75rem;
+  }
+
+  .sources summary,
+  .assumptions summary {
+    padding-block: 0.7rem;
+  }
+
+  .btn {
+    display: inline-flex;
+    align-items: center;
+    justify-content: center;
+  }
+
+  .row-actions .btn {
+    min-width: 2.75rem;
+  }
+}
\ No newline at end of file
diff --git a/data/blocks.json b/data/blocks.json
new file mode 100644
index 00000000..8565922e
--- /dev/null
+++ b/data/blocks.json
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/data/harris-boundary.geojson b/data/harris-boundary.geojson
new file mode 100644
index 00000000..c6d828df
--- /dev/null
+++ b/data/harris-boundary.geojson
@@ -0,0 +1 @@
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diff --git a/data/harris-mask.geojson b/data/harris-mask.geojson
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index 00000000..d695d597
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diff --git a/data/houston-city.geojson b/data/houston-city.geojson
new file mode 100644
index 00000000..9557d5c4
--- /dev/null
+++ b/data/houston-city.geojson
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diff --git a/data/stops.json b/data/stops.json
new file mode 100644
index 00000000..7681a2e6
--- /dev/null
+++ b/data/stops.json
@@ -0,0 +1 @@
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\ No newline at end of file
diff --git a/data/stores.geojson b/data/stores.geojson
new file mode 100644
index 00000000..32557b2e
--- /dev/null
+++ b/data/stores.geojson
@@ -0,0 +1,4230 @@
+{
+"type": "FeatureCollection",
+"crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:OGC:1.3:CRS84" } },
+"features": [
+{ "type": "Feature", "properties": { "name": "#1 Pick N Go", "type": "Convenience Store", "addr": "4408 Broadway St", "cat": "convenience" }, "geometry": { "type": "Point", "coordinates": [ -95.29074, 29.56334 ] } },
+{ "type": "Feature", "properties": { "name": "1 Stop Express #16", "type": "Convenience Store", "addr": "2104 N Main St", "cat": "convenience" }, "geometry": { "type": "Point", "coordinates": [ -95.28655, 29.56894 ] } },
+{ "type": "Feature", "properties": { "name": "7-Eleven 36522H", "type": "Convenience Store", "addr": "2480 S Bypass 35", "cat": "convenience" }, "geometry": { "type": "Point", "coordinates": [ -95.22801, 29.40962 ] } },
+{ "type": "Feature", "properties": { "name": "7-Eleven 42060H", "type": "Convenience Store", "addr": "3321 Meridiana Pkwy", "cat": "convenience" }, "geometry": { "type": "Point", "coordinates": [ -95.4307, 29.43924 ] } },
+{ "type": "Feature", "properties": { "name": "7-Eleven, Inc. Dba Stripes 40976H", "type": "Convenience Store", "addr": "20135 Morris Ave", "cat": "convenience" }, "geometry": { "type": "Point", "coordinates": [ -95.35674, 29.46742 ] } },
+{ "type": "Feature", "properties": { "name": "Ab World Food Market", "type": "Medium Grocery Store", "addr": "11901 Shadow Creek Pkwy", "cat": "small" }, "geometry": { "type": "Point", "coordinates": [ -95.40351, 29.57834 ] } },
+{ "type": "Feature", "properties": { "name": "Aizen'S Food Mart", "type": "Convenience Store", "addr": "2850 Fm 528 Rd", "cat": "convenience" }, "geometry": { "type": "Point", "coordinates": [ -95.23763, 29.44811 ] } },
+{ "type": "Feature", "properties": { "name": "Aldi 78004", "type": "Supermarket", "addr": "11510 Broadway", "cat": "grocery" }, "geometry": { "type": "Point", "coordinates": [ -95.39861, 29.55554 ] } },
+{ "type": "Feature", "properties": { "name": "Aldi 12", "type": "Supermarket", "addr": "2373 S Bypass 35", "cat": "grocery" }, "geometry": { "type": "Point", "coordinates": [ -95.23404, 29.40516 ] } },
+{ "type": "Feature", "properties": { "name": "Aldi 78034", "type": "Supermarket", "addr": "3412 E Broadway St", "cat": "grocery" }, "geometry": { "type": "Point", "coordinates": [ -95.2765, 29.56149 ] } },
+{ "type": "Feature", "properties": { "name": "Alvin Corner Station", "type": "Convenience Store", "addr": "1920 E Highway 6", "cat": "convenience" }, "geometry": { "type": "Point", "coordinates": [ -95.22685, 29.42254 ] } },
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diff --git a/data/tracts.geojson b/data/tracts.geojson
new file mode 100644
index 00000000..c398c43e
--- /dev/null
+++ b/data/tracts.geojson
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+}
diff --git a/index.html b/index.html
new file mode 100644
index 00000000..8949e476
--- /dev/null
+++ b/index.html
@@ -0,0 +1,265 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Fixing the Houston Grocery Gap</title>
+    <meta name="description" content="A decision support tool for deciding where Houston should recruit new grocery stores.">
+    <link rel="stylesheet" href="https://unpkg.com/leaflet@1.9.4/dist/leaflet.css">
+    <link rel="preconnect" href="https://fonts.googleapis.com">
+    <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
+    <link href="https://fonts.googleapis.com/css2?family=Public+Sans:wght@400;600;700;800&display=swap" rel="stylesheet">
+    <link rel="stylesheet" href="css/index.css">
+</head>
+<body>
+    <main class="app-content">
+        <aside class="rail" aria-label="Controls and tract details">
+            <header class="rail-header">
+                <h1>Where should Houston's next grocery stores go?</h1>
+            </header>
+
+            <div class="tabs" role="tablist" aria-label="Tool steps">
+                <button class="tab" type="button" role="tab" id="tab-access" aria-controls="panel-access" aria-selected="true">Find gaps</button>
+                <button class="tab" type="button" role="tab" id="tab-rank" aria-controls="panel-rank" aria-selected="false" tabindex="-1">Rank locations</button>
+                <button class="tab" type="button" role="tab" id="tab-plan" aria-controls="panel-plan" aria-selected="false" tabindex="-1">Test plans</button>
+            </div>
+            <section class="panel" id="panel-access" role="tabpanel" aria-labelledby="tab-access">
+                <h2 id="definition-heading">What do we count as a grocery store?</h2>
+                <fieldset class="choice" aria-labelledby="definition-heading">
+                    <legend class="visually-hidden">Food access definition</legend>
+                    <p class="choice-head" aria-hidden="true">Food desert tracts</p>
+                    <label class="choice-row">
+                        <input type="radio" name="definition" value="grocery" checked>
+                        <span class="choice-text">
+                            <span class="choice-name">Grocery stores only</span>
+                            <span class="choice-meta">Supermarkets, supercenters and large grocers, <span data-count="grocery">726</span> in and near the county</span>
+                        </span>
+                        <span class="choice-count" data-desert="grocery"></span>
+                    </label>
+                    <label class="choice-row">
+                        <input type="radio" name="definition" value="usda">
+                        <span class="choice-text">
+                            <span class="choice-name">Any SNAP store</span>
+                            <span class="choice-meta">USDA's 2025 map; adds convenience, dollar and drug stores</span>
+                        </span>
+                        <span class="choice-count" data-desert="usda"></span>
+                    </label>
+                </fieldset>
+
+                <div class="headline" id="headline" aria-live="polite"></div>
+
+                <p class="note" id="definition-note"></p>
+            </section>
+
+            <section class="panel" id="panel-rank" role="tabpanel" aria-labelledby="tab-rank" hidden>
+                <h2>What is important when ranking new locations?</h2>
+                <p class="note">Set how much each factor counts. Scores run 0 to 100 and count only grocery stores as food access.</p>
+
+                <div class="weights">
+                    <div class="weight">
+                        <label for="w-need">
+                            <span class="weight-name">Need</span>
+                            <span class="weight-value" id="w-need-value">33%</span>
+                        </label>
+                        <input type="range" id="w-need" min="0" max="5" step="1" value="3" aria-describedby="w-need-help">
+                        <p class="weight-help" id="w-need-help">Residents beyond reach of a grocery store, car-free households among them, and poverty.</p>
+                    </div>
+                    <div class="weight">
+                        <label for="w-viability">
+                            <span class="weight-name">Viability</span>
+                            <span class="weight-value" id="w-viability-value">33%</span>
+                        </label>
+                        <input type="range" id="w-viability" min="0" max="5" step="1" value="3" aria-describedby="w-viability-help">
+                        <p class="weight-help" id="w-viability-help">Grocery spending by unserved residents within 2 miles, the sales a new store could win.</p>
+                    </div>
+                    <div class="weight">
+                        <label for="w-leverage">
+                            <span class="weight-name">Incentives</span>
+                            <span class="weight-value" id="w-leverage-value">33%</span>
+                        </label>
+                        <input type="range" id="w-leverage" min="0" max="5" step="1" value="3" aria-describedby="w-leverage-help">
+                        <p class="weight-help" id="w-leverage-help">Opportunity Zone status: 100 for 2027 nominees, 50 for eligible tracts, 0 otherwise.</p>
+                    </div>
+                </div>
+
+                <div class="shortlist-options">
+                    <label class="check">
+                        <input type="checkbox" id="opt-spacing" checked>
+                        Spread picks at least 2 miles apart
+                    </label>
+                    <label class="check">
+                        <input type="checkbox" id="opt-deserts">
+                        Only food desert tracts
+                    </label>
+                </div>
+
+                <h2 class="shortlist-heading">Top 10 sites</h2>
+                <ol class="shortlist" id="shortlist" aria-live="polite"></ol>
+            </section>
+
+            <section class="panel" id="panel-plan" role="tabpanel" aria-labelledby="tab-plan" hidden>
+                <h2>What would a plan buy?</h2>
+                <p class="note">Click a shaded tract to place a store, or add one from the list below. Drag a store to move it.</p>
+
+                <fieldset class="format-choice">
+                    <legend>Store type</legend>
+                    <label class="format">
+                        <input type="radio" name="format" value="full" checked>
+                        <span class="format-name">Full supermarket</span>
+                        <span class="format-meta">Large footprint, <span data-cost="full">$3M</span> incentive</span>
+                    </label>
+                    <label class="format">
+                        <input type="radio" name="format" value="small">
+                        <span class="format-name">Neighborhood grocer</span>
+                        <span class="format-meta">Smaller footprint, <span data-cost="small">$1M</span> incentive</span>
+                    </label>
+                </fieldset>
+
+                <div class="site-picker">
+                    <label for="site-pick">Or add one at a top-ranked site</label>
+                    <div class="site-picker-row">
+                        <select id="site-pick"></select>
+                        <button type="button" class="btn nowrap" id="site-add">Add store</button>
+                    </div>
+                </div>
+
+                <div class="budget">
+                    <div class="budget-line">
+                        <span>Recruitment fund</span>
+                        <span class="budget-amount" id="budget-text">$0 of $10M committed</span>
+                    </div>
+                    <div class="budget-track" aria-hidden="true"><span class="budget-fill" id="budget-fill"></span></div>
+                </div>
+
+                <p class="plan-message" id="plan-message" role="status"></p>
+                <div class="results" id="plan-results"></div>
+                <h3 class="sub-heading">Stores in this plan</h3>
+                <ol class="plan-stores" id="plan-stores"></ol>
+                <p class="note" id="plan-empty">No stores placed yet.</p>
+
+                <div class="plan-actions">
+                    <label class="visually-hidden" for="plan-name">Plan name</label>
+                    <input type="text" id="plan-name" placeholder="Name this plan" maxlength="40">
+                    <button type="button" class="btn primary" id="plan-save">Save</button>
+                    <button type="button" class="btn" id="plan-clear">Clear</button>
+                </div>
+
+                <h3 class="sub-heading">Saved plans</h3>
+                <div class="compare-wrap" tabindex="0" role="region" aria-label="Saved plans compared">
+                    <table class="compare" id="compare">
+                        <thead>
+                            <tr>
+                                <th scope="col">Plan</th>
+                                <th scope="col" class="num">Stores</th>
+                                <th scope="col" class="num">Cost</th>
+                                <th scope="col" class="num">Newly in reach</th>
+                                <th scope="col" class="num">City tax revenue a year</th>
+                                <th scope="col"><span class="visually-hidden">Actions</span></th>
+                            </tr>
+                        </thead>
+                        <tbody id="compare-rows"></tbody>
+                    </table>
+                </div>
+                <div class="plan-actions">
+                    <button type="button" class="btn" id="plan-export">Export plans</button>
+                    <label class="btn" for="plan-import">Import plans</label>
+                    <input type="file" id="plan-import" accept="application/json,.json" class="visually-hidden">
+                </div>
+
+                <details class="assumptions">
+                    <summary>Planning assumptions</summary>
+                    <div class="assume-grid">
+                        <label for="a-budget">Recruitment fund ($M)</label>
+                        <input type="number" id="a-budget" min="0" step="0.5" value="10">
+                        <label for="a-incentive-full">Incentive, full supermarket ($M)</label>
+                        <input type="number" id="a-incentive-full" min="0" step="0.25" value="3">
+                        <label for="a-incentive-small">Incentive, neighborhood grocer ($M)</label>
+                        <input type="number" id="a-incentive-small" min="0" step="0.25" value="1">
+                        <label for="a-floor-full">Sales needed to stay open, full ($M a year)</label>
+                        <input type="number" id="a-floor-full" min="0" step="1" value="15">
+                        <label for="a-floor-small">Sales needed to stay open, neighborhood ($M a year)</label>
+                        <input type="number" id="a-floor-small" min="0" step="1" value="5">
+                        <label for="a-value-full">Taxable building value, full ($M)</label>
+                        <input type="number" id="a-value-full" min="0" step="1" value="12">
+                        <label for="a-value-small">Taxable building value, neighborhood ($M)</label>
+                        <input type="number" id="a-value-small" min="0" step="1" value="4">
+                        <label for="a-grocery-share">Groceries' share of store sales (%)</label>
+                        <input type="number" id="a-grocery-share" min="10" max="100" step="5" value="80">
+                        <label for="a-taxable-grocery">Share of groceries that is taxed (%)</label>
+                        <input type="number" id="a-taxable-grocery" min="0" max="100" step="1" value="10">
+                    </div>
+                    <p class="note">City tax revenue: 1% sales tax on everything but groceries, plus the taxed part of groceries (soda, candy, hot food), and property tax at $0.519190 per $100. Sales: a Huff model over stores within 5 miles, scaled to 2022 Census sales for Harris County.</p>
+                </details>
+            </section>
+
+            <section class="panel profile" id="profile" aria-labelledby="profile-heading" aria-live="polite">
+                <h2 id="profile-heading">Tract details</h2>
+                <p class="note" id="profile-empty">Select a tract on the map to see who lives there and how far they are from groceries.</p>
+                <div id="profile-body" hidden></div>
+            </section>
+
+            <section class="panel" aria-labelledby="layers-heading">
+                <h2 id="layers-heading">Map layers</h2>
+                <ul class="layer-list">
+                    <li>
+                        <label class="layer-toggle">
+                            <input type="checkbox" name="layer" value="grocery" checked>
+                            <span class="swatch dot" data-cat="grocery"></span>
+                            <span class="layer-name">Grocery stores</span>
+                            <span class="layer-count" data-count="grocery"></span>
+                        </label>
+                    </li>
+                    <li>
+                        <label class="layer-toggle">
+                            <input type="checkbox" name="layer" value="small">
+                            <span class="swatch dot" data-cat="small"></span>
+                            <span class="layer-name">Small grocers</span>
+                            <span class="layer-count" data-count="small"></span>
+                        </label>
+                    </li>
+                    <li>
+                        <label class="layer-toggle">
+                            <input type="checkbox" name="layer" value="dollar">
+                            <span class="swatch dot" data-cat="dollar"></span>
+                            <span class="layer-name">Dollar stores and pharmacies</span>
+                            <span class="layer-count" data-count="dollar"></span>
+                        </label>
+                    </li>
+                    <li>
+                        <label class="layer-toggle">
+                            <input type="checkbox" name="layer" value="convenience">
+                            <span class="swatch dot" data-cat="convenience"></span>
+                            <span class="layer-name">Convenience stores</span>
+                            <span class="layer-count" data-count="convenience"></span>
+                        </label>
+                    </li>
+                </ul>
+            </section>
+            <details class="panel sources">
+                <summary>About the data</summary>
+                <ul class="source-list">
+                    <li><b>Grocery access:</b> USDA Economic Research Service, Food Access Research Atlas: SNAP-authorized Retailer Access Map, 2025 (released July 2026), on 2020 census tracts.</li>
+                    <li><b>Store locations:</b> USDA Food and Nutrition Service, Historical SNAP Retailer Locator Data, stores authorized as of December 31, 2025, within 10 miles of the county line, since residents near the edge of the boundary may shop outside city limits. "Grocery stores" are the supermarket, super store and large grocery store types, which matches USDA's Large Retailer Access Map.</li>
+                    <li><b>Population data:</b> U.S. Census Bureau, 2020 Census block populations, via TIGERweb.</li>
+                    <li><b>Income, poverty and vehicles:</b> American Community Survey 2020 to 2024 5-year estimates, as published in the USDA file above.</li>
+                    <li><b>Grocery spending:</b> U.S. Bureau of Labor Statistics, Consumer Expenditure Survey 2024, food at home by income quintile, applied to each tract's households by median family income.</li>
+                    <li><b>Opportunity Zones:</b> Office of the Texas Governor, Economic Development and Tourism, Opportunity Zone 2.0 nominated and eligible tracts, September 2026.</li>
+                    <li><b>Neighborhoods:</b> City of Houston Planning and Development, Super Neighborhoods. Outside the city, U.S. Census Bureau 2020 incorporated and census-designated places.</li>
+                    <li><b>Store sales:</b> U.S. Census Bureau, 2022 Economic Census, retail trade sales for Harris County; Texas Comptroller, sales tax receipts by retail subsector, 2022.</li>
+                    <li><b>Tax rates:</b> City of Houston, tax year 2025 adopted property tax rate; Texas Comptroller, sales tax on grocery and convenience stores.</li>
+                    <li><b>Transit:</b> Metropolitan Transit Authority of Harris County, GTFS schedule data, August 30, 2026 service change.</li>
+                    <li><i>A tract is low access when at least 500 people, or a third of its residents, live more than 1 mile from a store (10 miles in rural tracts), measured from 2020 census block centers. Low income comes from the USDA's definition.</i></li>
+                    <li><i>Plan sales come from a Huff model: each block's grocery spending is split among stores within 5 miles by store size over distance squared. Sales a new store takes from existing stores move around the city instead of adding to it, so only the remainder counts as new city sales tax. Groceries for home use are exempt from Texas sales tax, so only nonfood and prepared items are taxed.</i></li>
+                </ul>
+            </details>
+        </aside>
+        <div class="map-wrap">
+            <div id="map" class="map" role="region" aria-label="Map of Harris County census tracts and food stores"></div>
+            <p class="map-status" id="map-status" role="status">Loading map data</p>
+            <div class="legend" id="legend" aria-hidden="true"></div>
+        </div>
+    </main>
+    <script src="https://unpkg.com/leaflet@1.9.4/dist/leaflet.js"></script>
+    <script type="module" src="js/main.js"></script>
+</body>
+</html>
\ No newline at end of file
diff --git a/js/format.js b/js/format.js
new file mode 100644
index 00000000..0d98fd9a
--- /dev/null
+++ b/js/format.js
@@ -0,0 +1,37 @@
+// Number formatting shared by the rail and the map.
+// Source: Claude Opus 5.5 High
+
+const intFmt = new Intl.NumberFormat('en-US');
+
+function int(n) {
+  return n == null ? 'n/a' : intFmt.format(Math.round(n));
+}
+
+function compact(n) {
+  if (n == null) { return 'n/a'; }
+  if (n >= 1e6) { return `${(n / 1e6).toFixed(n >= 1e7 ? 0 : 1)}M`; }
+  if (n >= 1e3) { return `${Math.round(n / 1e3)}k`; }
+  return int(n);
+}
+function dollars(n) {
+  if (n == null) { return 'n/a'; }
+  if (n >= 1e6) { return `$${(n / 1e6).toFixed(1)}M`; }
+  return `$${intFmt.format(Math.round(n))}`;
+}
+
+function pct(part, whole) {
+  if (!whole) { return 'n/a'; }
+  return `${Math.round((part / whole) * 100)}%`;
+}
+
+function miles(n) {
+  return n == null ? 'n/a' : `${n.toFixed(1)} mi`;
+}
+
+function money(n) {
+  if (n >= 1e6) { return `$${(n / 1e6).toFixed(n >= 1e7 ? 0 : 1)}M`; }
+  if (n >= 1e3) { return `$${Math.round(n / 1e3)}k`; }
+  return `$${Math.round(n)}`;
+}
+
+export { int, compact, dollars, pct, miles, money };
diff --git a/js/geo.js b/js/geo.js
new file mode 100644
index 00000000..c2b6d9dc
--- /dev/null
+++ b/js/geo.js
@@ -0,0 +1,34 @@
+// Point-in-polygon lookup for finding which tract a click is in.
+
+// Ray casting: count how many edges a line running east from the point
+// crosses. An odd count means the point is inside.
+// Source: Claude Opus 5.5
+function inRing(lon, lat, ring) {
+  let inside = false;
+  for (let i = 0, j = ring.length - 1; i < ring.length; j = i++) {
+    const [xi, yi] = ring[i];
+    const [xj, yj] = ring[j];
+    if ((yi > lat) !== (yj > lat) && lon < ((xj - xi) * (lat - yi)) / (yj - yi) + xi) {
+      inside = !inside;
+    }
+  }
+  return inside;
+}
+
+// Recursive check for polygons with holes
+function inPolygon(lon, lat, rings) {
+  return inRing(lon, lat, rings[0]) && !rings.slice(1).some((hole) => inRing(lon, lat, hole));
+}
+
+function inFeature(lon, lat, feature) {
+  const { type, coordinates } = feature.geometry;
+  if (type === 'Polygon') { return inPolygon(lon, lat, coordinates); }
+  if (type === 'MultiPolygon') { return coordinates.some((rings) => inPolygon(lon, lat, rings)); }
+  return false;
+}
+
+function findFeature(lon, lat, collection) {
+  return collection.features.find((f) => inFeature(lon, lat, f)) || null;
+}
+
+export { findFeature, inFeature };
diff --git a/js/headline.js b/js/headline.js
new file mode 100644
index 00000000..41f88ae0
--- /dev/null
+++ b/js/headline.js
@@ -0,0 +1,15 @@
+// How many food desert tracts the chosen definition corresponds to.
+
+import { int, compact } from './format.js';
+
+const STORE_WORD = { grocery: 'a grocery store', usda: 'any SNAP store' };
+
+function renderHeadline(el, stats, def) {
+  for (const span of document.querySelectorAll('[data-desert]')) {
+    span.innerHTML = `${int(stats[span.dataset.desert].count)}<span class="visually-hidden"> food desert tracts</span>`;
+  }
+  const s = stats[def];
+  el.innerHTML = `<p class="stat-sub">${compact(s.residents)} residents live in those tracts, and ${compact(s.farTotal)} people countywide live beyond reach of ${STORE_WORD[def]}.</p>`;
+}
+
+export { renderHeadline };
diff --git a/js/legend.js b/js/legend.js
new file mode 100644
index 00000000..67f952d7
--- /dev/null
+++ b/js/legend.js
@@ -0,0 +1,36 @@
+// Map legend for whatever the current mode is
+
+import { FILLS, SCORE_BREAKS, SCORE_FILLS, UNSCORED, PLAN_FILLS } from './tracts.js';
+
+function row(fill, label) {
+  return `<p class="legend-row"><span class="swatch fill" style="background-color: ${fill}"></span>${label}</p>`;
+}
+
+function renderLegend(el, mode) {
+  if (mode === 'plan') {
+    el.innerHTML = `
+      <p class="legend-title">Where recruitment funds can go</p>
+      ${row(PLAN_FILLS.desert, 'Food desert tract')}
+      ${row(PLAN_FILLS.zone, 'Opportunity Zone eligible')}
+      ${row(PLAN_FILLS.closed, 'Not eligible')}
+      <p class="legend-row"><span class="legend-ring"></span>1 mile reach of a new store</p>`;
+    return;
+  }
+  if (mode === 'rank') {
+    const edges = [0, ...SCORE_BREAKS, 100];
+    const rows = SCORE_FILLS.map((fill, i) => row(fill, `${edges[i]} to ${edges[i + 1]}`)).reverse();
+    el.innerHTML = `
+      <p class="legend-title">Site score</p>
+      ${rows.join('')}
+      ${row(UNSCORED, 'Not scored')}
+      <p class="legend-row"><span class="rank-key">1</span>Shortlist pick</p>`;
+    return;
+  }
+  el.innerHTML = `
+    <p class="legend-title">Census tracts</p>
+    ${row(FILLS.lila, 'Low income and low access')}
+    ${row(FILLS.la, 'Low access only')}
+    ${row(FILLS.ok, 'Within reach of a store')}`;
+}
+
+export { renderLegend };
diff --git a/js/main.js b/js/main.js
new file mode 100644
index 00000000..1ee4ae1b
--- /dev/null
+++ b/js/main.js
@@ -0,0 +1,191 @@
+import { createTractLayer, summarize } from './tracts.js';
+import { createStoreLayers, countStores } from './stores.js';
+import { renderLegend } from './legend.js';
+import { renderHeadline } from './headline.js';
+import { int } from './format.js';
+import { showProfile } from './profile.js';
+import { createRanking } from './rank.js';
+import { createPlanner } from './plan.js';
+
+const state = {
+  mode: 'access',
+  definition: 'grocery',
+  selected: null,
+  weights: { need: 3, viability: 3, leverage: 3 },
+};
+
+const NOTES = {
+  grocery: '',
+  usda: 'By this measure, a gas station is food access.',
+};
+
+const map = L.map('map', {
+  maxBounds: [[28.9, -96.4], [30.6, -94.4]],
+  maxBoundsViscosity: 1.0,
+  minZoom: 9,
+  zoomSnap: 0.5,
+}).setView([29.76, -95.37], 10);
+
+L.tileLayer('https://server.arcgisonline.com/ArcGIS/rest/services/Canvas/World_Light_Gray_Base/MapServer/tile/{z}/{y}/{x}', {
+  maxZoom: 16,
+  attribution: 'Tiles &copy; <a href="https://www.esri.com">Esri</a>, HERE, Garmin, &copy; OpenStreetMap contributors',
+}).addTo(map);
+
+map.createPane('rankPane');
+map.getPane('rankPane').style.zIndex = 460;
+map.createPane('zonePane');
+map.getPane('zonePane').style.zIndex = 430;
+map.createPane('maskPane');
+map.getPane('maskPane').style.zIndex = 420;
+map.getPane('maskPane').style.pointerEvents = 'none';
+map.createPane('storePane');
+map.getPane('storePane').style.zIndex = 450;
+
+const statusEl = document.getElementById('map-status');
+
+async function getJson(path) {
+  const r = await fetch(path);
+  if (!r.ok) { throw new Error(`${path} returned ${r.status}`); }
+  return r.json();
+}
+
+// If any file fails, say so on the map instead of leaving "Loading" up forever.
+let data;
+try {
+  data = await Promise.all([
+    'data/tracts.geojson', 'data/stores.geojson', 'data/harris-mask.geojson',
+    'data/harris-boundary.geojson', 'data/blocks.json', 'data/stops.json',
+    'data/houston-city.geojson',
+  ].map(getJson));
+} catch (err) {
+  statusEl.textContent = "The map data didn't load. Check your connection and reload the page.";
+  statusEl.classList.add('is-error');
+  throw err;
+}
+statusEl.hidden = true;
+const [tracts, stores, mask, boundary, blocks, stops, city] = data;
+const legendEl = document.getElementById('legend');
+const tractsById = new Map(tracts.features.map((f) => [f.properties.geoid, f.properties]));
+
+const tractLayer = createTractLayer(tracts, state, selectTract);
+tractLayer.addTo(map);
+const storeLayers = createStoreLayers(stores);
+storeLayers.grocery.addTo(map);
+
+const maskRenderer = L.svg({ padding: 3, pane: 'maskPane' });
+
+L.geoJSON(mask, {
+  pane: 'maskPane',
+  renderer: maskRenderer,
+  interactive: false,
+  style: { stroke: false, fillColor: '#e9ebe6', fillOpacity: 0.85 },
+}).addTo(map);
+
+const county = L.geoJSON(boundary, {
+  pane: 'maskPane',
+  renderer: maskRenderer,
+  interactive: false,
+  style: { color: 'rgb(18 26 22 / 45%)', weight: 1.25, fill: false },
+}).addTo(map);
+
+map.fitBounds(county.getBounds(), { padding: [8, 8] });
+
+const counts = countStores(stores);
+counts.snap = counts.grocery + counts.small + counts.dollar + counts.convenience;
+for (const el of document.querySelectorAll('[data-count]')) {
+  el.textContent = int(counts[el.dataset.count] || 0);
+}
+
+for (const input of document.querySelectorAll('input[name="layer"]')) {
+  const layer = storeLayers[input.value];
+  if (input.checked) { layer.addTo(map); }
+  input.addEventListener('change', () => {
+    if (input.checked) {
+      layer.addTo(map);
+    } else {
+      layer.remove();
+    }
+  });
+}
+
+const headlineStats = { grocery: summarize(tracts, 'grocery'), usda: summarize(tracts, 'usda') };
+
+function refreshProfile() {
+  if (state.selected) { showProfile(tractsById.get(state.selected), state.definition); }
+}
+
+// Clicking a tract in the plan step places a store instead of selecting something.
+function onTractClick(geoid) {
+  if (state.mode !== 'plan') { selectTract(geoid); }
+}
+
+function selectTract(geoid) {
+  state.selected = geoid;
+  tractLayer.restyle();
+  refreshProfile();
+}
+
+function updateHeadline() {
+  renderHeadline(document.getElementById('headline'), headlineStats, state.definition);
+  const note = document.getElementById('definition-note');
+  note.textContent = NOTES[state.definition];
+  note.hidden = !note.textContent;
+}
+
+for (const input of document.querySelectorAll('input[name="definition"]')) {
+  input.addEventListener('change', () => {
+    state.definition = input.value;
+    tractLayer.restyle();
+    updateHeadline();
+    refreshProfile();
+  });
+}
+
+const ranking = createRanking({
+  map,
+  tracts,
+  state,
+  onSelect: selectTract,
+  onChange: () => {
+    if (state.mode === 'rank') { tractLayer.restyle(); }
+  },
+});
+
+const planner = createPlanner({ map, tracts, blocks: blocks.rows, stops, city });
+
+// A click that lands on a store dot still places a store.
+map.on('click', (e) => {
+  if (state.mode === 'plan') { planner.place(e.latlng); }
+});
+
+const tabs = [...document.querySelectorAll('[role="tab"]')];
+
+function setMode(tab) {
+  for (const t of tabs) {
+    const active = t === tab;
+    t.setAttribute('aria-selected', String(active));
+    t.tabIndex = active ? 0 : -1;
+    document.getElementById(t.getAttribute('aria-controls')).hidden = !active;
+  }
+  state.mode = { 'tab-rank': 'rank', 'tab-plan': 'plan' }[tab.id] || 'access';
+  ranking.show(state.mode === 'rank');
+  planner.show(state.mode === 'plan');
+  tractLayer.restyle();
+  renderLegend(legendEl, state.mode);
+}
+
+// Left and right arrows move between tabs and wrap around
+tabs.forEach((tab, i) => {
+  tab.addEventListener('click', () => setMode(tab));
+  tab.addEventListener('keydown', (e) => {
+    if (e.key !== 'ArrowRight' && e.key !== 'ArrowLeft') { return; }
+    const next = tabs[(i + (e.key === 'ArrowRight' ? 1 : tabs.length - 1)) % tabs.length];
+    next.focus();
+    setMode(next);
+  });
+});
+
+updateHeadline();
+refreshProfile();
+
+renderLegend(legendEl, state.mode);
diff --git a/js/model.js b/js/model.js
new file mode 100644
index 00000000..dd177eaf
--- /dev/null
+++ b/js/model.js
@@ -0,0 +1,129 @@
+// What-if model new stores. This model simulates who a new store reaches,
+// what sales they take / generate, and what the city gets back in tax revenue.
+
+import { milesBetween } from './scores.js';
+
+const FORMATS = {
+  full: { label: 'Full supermarket', size: 1.0 },
+  small: { label: 'Neighborhood grocer', size: 0.33 },
+};
+
+// Planning assumptions (editable in interface)
+const DEFAULT_ASSUMPTIONS = {
+  budget: 10e6,
+  incentive: { full: 3e6, small: 1e6 },
+  floor: { full: 15e6, small: 5e6 },
+  buildingValue: { full: 12e6, small: 4e6 },
+  groceryShare: 0.8,
+  taxableGroceryShare: 0.1,
+};
+
+const CITY_SALES_TAX = 0.01;
+const CITY_PROPERTY_TAX = 0.0051919;
+// Scales food spending to match 2022 Census grocery and supercenter sales in Harris County.
+const FOOD_SCALE = 1.39;
+
+const HUFF_MI = 5;
+const MIN_MI = 0.25;
+// The pull of everything else someone can buy groceries from (a supermarket
+// 5 miles away, online, warehouse clubs).
+const OUTSIDE_PULL = 1 / HUFF_MI ** 2;
+const STOP_WALK_MI = 0.25;
+
+// Each block row carries pull, the summed pull of the existing grocery
+// stores on it (store size over distance squared, within 5 miles),
+// new stores add their own pull on top.
+function evaluate(plan, { blocks, tracts, stops, inCity }) {
+  const stores = plan.stores.map((s) => ({
+    ...s,
+    size: FORMATS[s.format].size,
+    sales: 0,
+    shifted: 0,
+    stopsNearby: stops.filter(([lon, lat]) => milesBetween(s, { lat, lon }) <= STOP_WALK_MI).length,
+    inCity: inCity(s.lon, s.lat),
+  }));
+
+  let newlyReached = 0;
+  let desertReached = 0;
+  let carFreeReached = 0;
+
+  for (const [lon, lat, pop, t, dGrocery, , pull, spend] of blocks) {
+    const block = { lat, lon };
+    const tract = tracts[t];
+    const limit = tract.urban ? 1 : 10;
+    let newPull = 0;
+    let nearest = Infinity;
+    const pulls = [];
+    for (const s of stores) {
+      const d = milesBetween(block, s);
+      nearest = Math.min(nearest, d);
+      const p = d <= HUFF_MI ? s.size / Math.max(d, MIN_MI) ** 2 : 0;
+      pulls.push(p);
+      newPull += p;
+    }
+
+    if (dGrocery > limit && nearest <= limit) {
+      newlyReached += pop;
+      if (tract.lila_grocery) { desertReached += pop; }
+      if (tract.pop) { carFreeReached += tract.nocar * (pop / tract.pop); }
+    }
+
+    if (newPull === 0 || spend === 0) { continue; }
+    const total = pull + newPull + OUTSIDE_PULL;
+    // Existing stores lose the difference between their share before and after.
+    const shifted = spend * (pull / (pull + OUTSIDE_PULL) - pull / total);
+    stores.forEach((s, i) => {
+      if (!pulls[i]) { return; }
+      s.sales += (spend * pulls[i]) / total;
+      s.shifted += shifted * (pulls[i] / newPull);
+    });
+  }
+
+  const a = plan.assumptions;
+  let cost = 0;
+  let sales = 0;
+  let shifted = 0;
+  let taxable = 0;
+  let cityRevenue = 0;
+  let newCityRevenue = 0;
+  // Kept between 10% and 100% so a blank or zero entry can't divide by zero.
+  const groceryShare = Math.min(Math.max(a.groceryShare, 0.1), 1);
+  for (const s of stores) {
+    // Food spending, scaled to real food sales, then grossed up to the whole store.
+    const shiftedShare = s.sales ? s.shifted / s.sales : 0;
+    s.sales = (s.sales * FOOD_SCALE) / groceryShare;
+    s.shifted = s.sales * shiftedShare;
+    s.cost = a.incentive[s.format];
+    s.viable = s.sales >= a.floor[s.format];
+    // Everything but groceries is taxed, plus the taxed part of groceries (soda, candy, hot food).
+    s.taxable = s.sales * (1 - groceryShare + groceryShare * a.taxableGroceryShare);
+    const propertyTax = a.buildingValue[s.format] * CITY_PROPERTY_TAX;
+    // Collected counts every sale. New leaves out sales taken from existing stores,
+    // which the city was already taxing.
+    s.cityRevenue = s.inCity ? s.taxable * CITY_SALES_TAX + propertyTax : 0;
+    s.newCityRevenue = s.inCity ? s.taxable * (1 - shiftedShare) * CITY_SALES_TAX + propertyTax : 0;
+    cost += s.cost;
+    sales += s.sales;
+    shifted += s.shifted;
+    taxable += s.taxable;
+    cityRevenue += s.cityRevenue;
+    newCityRevenue += s.newCityRevenue;
+  }
+
+  return {
+    stores,
+    cost,
+    sales,
+    shifted,
+    taxable,
+    cityRevenue,
+    newCityRevenue,
+    payback: cityRevenue > 0 ? cost / cityRevenue : null,
+    newPayback: newCityRevenue > 0 ? cost / newCityRevenue : null,
+    newlyReached,
+    desertReached,
+    carFreeReached,
+  };
+}
+
+export { FORMATS, DEFAULT_ASSUMPTIONS, evaluate };
diff --git a/js/plan.js b/js/plan.js
new file mode 100644
index 00000000..2b264619
--- /dev/null
+++ b/js/plan.js
@@ -0,0 +1,350 @@
+// Plan step: place stores within the recruitment fund, see what the impact is,
+// and save plans to compare.
+
+import { FORMATS, DEFAULT_ASSUMPTIONS, evaluate } from './model.js';
+import { findFeature, inFeature } from './geo.js';
+import { money, compact } from './format.js';
+import { renderResults } from './results.js';
+import { shortlist } from './scores.js';
+
+const REACH_METERS = 1609.344;
+const STORAGE_KEY = 'houston-grocery-gap-plans';
+const SUMMARY_FIELDS = ['stores', 'cost', 'newlyReached', 'cityRevenue', 'sales'];
+
+const ESCAPES = { '&': '&amp;', '<': '&lt;', '>': '&gt;', '"': '&quot;', "'": '&#39;' };
+
+function escapeHtml(text) {
+  return String(text).replace(/[&<>"']/g, (c) => ESCAPES[c]);
+}
+
+// Storage can be full / blocked (private windows, settings), so
+// failures fall back to temporary storage.
+function readStorage() {
+  try {
+    return JSON.parse(localStorage.getItem(STORAGE_KEY)) || [];
+  } catch {
+    return [];
+  }
+}
+
+function writeStorage(plans) {
+  try {
+    localStorage.setItem(STORAGE_KEY, JSON.stringify(plans));
+    return true;
+  } catch {
+    return false;
+  }
+}
+
+// Funds can go to food deserts or Opportunity Zones.
+function isEligible(p) {
+  return Boolean(p && (p.lila_grocery || p.oz_eligible || p.oz_nominated));
+}
+
+function createPlanner({ map, tracts, blocks, stops, city }) {
+  const el = (id) => document.getElementById(id);
+  const tractRows = tracts.features.map((f) => f.properties);
+  const inCity = (lon, lat) => city.features.some((f) => inFeature(lon, lat, f));
+  const layer = L.layerGroup();
+  let assumptions = structuredClone(DEFAULT_ASSUMPTIONS);
+  let stores = [];
+  let nextId = 1;
+  let result = null;
+  let saved = readStorage();
+
+  function say(message) {
+    el('plan-message').textContent = message;
+  }
+
+  function currentFormat() {
+    return document.querySelector('input[name="format"]:checked').value;
+  }
+
+  // Input elements for the planning assumptions.
+  const ASSUME_INPUTS = [
+    ['a-budget', (v) => { assumptions.budget = v * 1e6; }, () => assumptions.budget / 1e6],
+    ['a-incentive-full', (v) => { assumptions.incentive.full = v * 1e6; }, () => assumptions.incentive.full / 1e6],
+    ['a-incentive-small', (v) => { assumptions.incentive.small = v * 1e6; }, () => assumptions.incentive.small / 1e6],
+    ['a-floor-full', (v) => { assumptions.floor.full = v * 1e6; }, () => assumptions.floor.full / 1e6],
+    ['a-floor-small', (v) => { assumptions.floor.small = v * 1e6; }, () => assumptions.floor.small / 1e6],
+    ['a-value-full', (v) => { assumptions.buildingValue.full = v * 1e6; }, () => assumptions.buildingValue.full / 1e6],
+    ['a-value-small', (v) => { assumptions.buildingValue.small = v * 1e6; }, () => assumptions.buildingValue.small / 1e6],
+    ['a-grocery-share', (v) => { assumptions.groceryShare = v / 100; }, () => assumptions.groceryShare * 100],
+    ['a-taxable-grocery', (v) => { assumptions.taxableGroceryShare = v / 100; }, () => assumptions.taxableGroceryShare * 100],
+  ];
+
+  // Read the current values of the assumption inputs.
+  function readAssumptions() {
+    for (const [id, set] of ASSUME_INPUTS) {
+      const v = Number(el(id).value);
+      if (el(id).value !== '' && Number.isFinite(v) && v >= 0) { set(v); }
+    }
+  }
+
+  function writeAssumptions() {
+    for (const [id, , get] of ASSUME_INPUTS) {
+      el(id).value = String(get());
+    }
+  }
+
+  function committed() {
+    return stores.reduce((sum, s) => sum + assumptions.incentive[s.format], 0);
+  }
+
+  function place(latlng, known = null) {
+    const tract = known ? null : findFeature(latlng.lng, latlng.lat, tracts);
+    const p = known || (tract && tract.properties);
+    if (!isEligible(p)) {
+      say("Recruitment funds can't go here. Choose a shaded tract.");
+      return;
+    }
+    const format = currentFormat();
+    const cost = assumptions.incentive[format];
+    if (committed() + cost > assumptions.budget) {
+      say(`Over budget. This ${FORMATS[format].label.toLowerCase()} needs ${money(cost)} and the fund has ${money(assumptions.budget - committed())} left.`);
+      return;
+    }
+    stores.push({ id: nextId++, format, lat: latlng.lat, lon: latlng.lng, hood: p.hood });
+    say(`Placed a ${FORMATS[format].label.toLowerCase()} in ${p.hood}.`);
+    update();
+  }
+
+  // A store dropped outside an eligible tract snaps back on the redraw.
+  function move(id, latlng) {
+    const store = stores.find((s) => s.id === id);
+    const tract = findFeature(latlng.lng, latlng.lat, tracts);
+    if (!isEligible(tract && tract.properties)) {
+      say('That spot is not eligible for recruitment funds, so the store went back.');
+    } else {
+      store.lat = latlng.lat;
+      store.lon = latlng.lng;
+      store.hood = tract.properties.hood;
+      say(`Moved the store to ${store.hood}.`);
+    }
+    update();
+  }
+
+  function remove(id) {
+    stores = stores.filter((s) => s.id !== id);
+    say('Removed the store.');
+    update();
+  }
+
+  // Stores that won't reach break-even sales turn red on the map and the list.
+  function pinHtml(s, i) {
+    return `<span class="plan-pin${s.viable ? '' : ' is-weak'}${s.format === 'small' ? ' is-small' : ''}">${i + 1}</span>`;
+  }
+
+  function drawMap() {
+    layer.clearLayers();
+    result.stores.forEach((s, i) => {
+      const color = s.viable ? '#1f7a4d' : '#9b2c12';
+      L.circle([s.lat, s.lon], {
+        radius: REACH_METERS,
+        pane: 'zonePane',
+        interactive: false,
+        color,
+        weight: 1.5,
+        dashArray: '4 4',
+        fillColor: color,
+        fillOpacity: 0.08,
+      }).addTo(layer);
+      const icon = L.divIcon({ className: 'plan-marker', html: pinHtml(s, i), iconSize: [28, 28] });
+      L.marker([s.lat, s.lon], { icon, pane: 'rankPane', draggable: true, keyboard: false, title: `Store ${i + 1}, drag to move` })
+        .on('dragend', (e) => move(s.id, e.target.getLatLng()))
+        .addTo(layer);
+    });
+  }
+
+  function storeFacts(s) {
+    const facts = [`${money(s.sales)} a year`, `${s.stopsNearby} bus stops within &frac14; mile`];
+    if (!s.viable) { facts.unshift('<b class="weak">Below break-even sales</b>'); }
+    if (!s.inCity) { facts.push('outside city limits'); }
+    return facts.join(', ');
+  }
+
+  function drawList() {
+    const spent = result.cost;
+    el('budget-text').textContent = `${money(spent)} of ${money(assumptions.budget)} committed`;
+    el('budget-fill').style.width = `${assumptions.budget ? Math.min(100, (spent / assumptions.budget) * 100) : 0}%`;
+    for (const span of document.querySelectorAll('[data-cost]')) {
+      span.textContent = money(assumptions.incentive[span.dataset.cost]);
+    }
+
+    el('plan-empty').hidden = stores.length > 0;
+    if (!stores.length) {
+      el('plan-results').innerHTML = '';
+      el('plan-stores').innerHTML = '';
+      return;
+    }
+    renderResults(el('plan-results'), result);
+    el('plan-stores').innerHTML = result.stores.map((s, i) => `
+      <li class="plan-store">
+        ${pinHtml(s, i)}
+        <span class="plan-store-main">
+          <span class="plan-store-name">${FORMATS[s.format].label}, ${escapeHtml(s.hood)}</span>
+          <span class="plan-store-facts">${storeFacts(s)}</span>
+        </span>
+        <button type="button" class="btn small" data-remove="${s.id}" aria-label="Remove store ${i + 1}">Remove</button>
+      </li>`).join('');
+  }
+
+  function drawSaved() {
+    el('compare-rows').innerHTML = saved.map((p, i) => `
+      <tr>
+        <th scope="row">${escapeHtml(p.name)}</th>
+        <td class="num">${p.summary.stores}</td>
+        <td class="num">${money(p.summary.cost)}</td>
+        <td class="num">${compact(p.summary.newlyReached)}</td>
+        <td class="num">${money(p.summary.cityRevenue)}</td>
+        <td class="row-actions">
+          <button type="button" class="btn small" data-load="${i}">Load</button>
+          <button type="button" class="btn small" data-delete="${i}" aria-label="Delete ${escapeHtml(p.name)}">Delete</button>
+        </td>
+      </tr>`).join('');
+    el('compare').hidden = saved.length === 0;
+  }
+
+  function update() {
+    readAssumptions();
+    result = evaluate({ stores, assumptions }, { blocks, tracts: tractRows, stops, inCity });
+    drawMap();
+    drawList();
+  }
+
+  el('plan-stores').addEventListener('click', (e) => {
+    const button = e.target.closest('[data-remove]');
+    if (button) { remove(Number(button.dataset.remove)); }
+  });
+
+  el('plan-clear').addEventListener('click', () => {
+    stores = [];
+    el('plan-name').value = '';
+    say('Cleared the plan.');
+    update();
+  });
+
+  // ## Saving, loading, export and import
+
+  function summarize() {
+    return {
+      stores: result.stores.length,
+      cost: result.cost,
+      newlyReached: Math.round(result.newlyReached),
+      cityRevenue: Math.round(result.cityRevenue),
+      sales: Math.round(result.sales),
+    };
+  }
+
+  function load(p) {
+    stores = p.stores.map((s) => ({ ...s, id: nextId++ }));
+    assumptions = { ...structuredClone(DEFAULT_ASSUMPTIONS), ...structuredClone(p.assumptions) };
+    writeAssumptions();
+    el('plan-name').value = p.name;
+    update();
+  }
+
+  // Saving under a name that's already taken replaces that plan.
+  el('plan-save').addEventListener('click', () => {
+    if (!stores.length) {
+      say('Place at least one store before saving.');
+      return;
+    }
+    const name = el('plan-name').value.trim() || `Plan ${saved.length + 1}`;
+    const entry = {
+      name,
+      stores: stores.map(({ format, lat, lon, hood }) => ({ format, lat, lon, hood })),
+      assumptions: structuredClone(assumptions),
+      summary: summarize(),
+    };
+    const existing = saved.findIndex((p) => p.name === name);
+    if (existing >= 0) { saved[existing] = entry; } else { saved.push(entry); }
+    say(writeStorage(saved) ? `Saved "${name}".` : `Saved "${name}" for this visit only. This browser is blocking storage, so export it to keep it.`);
+    drawSaved();
+  });
+
+  el('compare-rows').addEventListener('click', (e) => {
+    const loadButton = e.target.closest('[data-load]');
+    const deleteButton = e.target.closest('[data-delete]');
+    if (loadButton) {
+      const p = saved[Number(loadButton.dataset.load)];
+      load(p);
+      say(`Loaded "${p.name}".`);
+    } else if (deleteButton) {
+      const [p] = saved.splice(Number(deleteButton.dataset.delete), 1);
+      writeStorage(saved);
+      say(`Deleted "${p.name}".`);
+      drawSaved();
+    }
+  });
+
+  el('plan-export').addEventListener('click', () => {
+    if (!saved.length) {
+      say('Save a plan before exporting.');
+      return;
+    }
+    const blob = new Blob([JSON.stringify({ app: 'houston-grocery-gap', plans: saved }, null, 2)], { type: 'application/json' });
+    const a = document.createElement('a');
+    a.href = URL.createObjectURL(blob);
+    a.download = 'grocery-plans.json';
+    a.click();
+    URL.revokeObjectURL(a.href);
+  });
+
+  // Keep only plans and stores that look right, and force the summary to
+  // numbers, since the table writes them straight into the page.
+  el('plan-import').addEventListener('change', async (e) => {
+    const [file] = e.target.files;
+    if (!file) { return; }
+    try {
+      const data = JSON.parse(await file.text());
+      const plans = (data.plans || []).filter((p) => p && p.name && Array.isArray(p.stores) && p.summary);
+      for (const p of plans) {
+        p.stores = p.stores.filter((s) => FORMATS[s.format] && Number.isFinite(s.lat) && Number.isFinite(s.lon));
+        p.summary = Object.fromEntries(SUMMARY_FIELDS.map((k) => [k, Number(p.summary[k]) || 0]));
+        const i = saved.findIndex((q) => q.name === p.name);
+        if (i >= 0) { saved[i] = p; } else { saved.push(p); }
+      }
+      writeStorage(saved);
+      drawSaved();
+      say(plans.length ? `Imported ${plans.length} plan${plans.length === 1 ? '' : 's'}.` : 'No plans found in that file.');
+    } catch {
+      say('That file could not be read. Choose a plans file exported from this tool.');
+    }
+    e.target.value = '';
+  });
+
+  for (const [id] of ASSUME_INPUTS) {
+    el(id).addEventListener('change', update);
+  }
+
+  const siteSelect = el('site-pick');
+
+  function refreshSites() {
+    const eligible = { features: tracts.features.filter((f) => isEligible(f.properties)) };
+    const sites = shortlist(eligible, { size: 40, spacingMi: 2 });
+    siteSelect.innerHTML = sites
+      .map((p) => `<option value="${p.geoid}">${Math.round(p.score)}: ${escapeHtml(p.hood)}, tract ${p.name}</option>`)
+      .join('');
+  }
+
+  el('site-add').addEventListener('click', () => {
+    const p = tractRows.find((q) => q.geoid === siteSelect.value);
+    if (p) { place(L.latLng(p.lat, p.lon), p); }
+  });
+
+  function show(visible) {
+    if (visible) {
+      refreshSites();
+      layer.addTo(map);
+    } else {
+      layer.remove();
+    }
+  }
+
+  update();
+  drawSaved();
+  return { place, show };
+}
+
+export { createPlanner };
diff --git a/js/profile.js b/js/profile.js
new file mode 100644
index 00000000..2e1d1ded
--- /dev/null
+++ b/js/profile.js
@@ -0,0 +1,44 @@
+// Tract details panel in the rail.
+
+import { int, dollars, pct, miles } from './format.js';
+import { accessClass } from './tracts.js';
+
+const STATUS = {
+  lila: 'Food desert',
+  la: 'Low access',
+  ok: 'Within reach',
+};
+
+function statusFor(p, definition) {
+  const parts = [STATUS[accessClass(p, definition)]];
+  if (p.low_income) { parts.push('Low income'); }
+  if (p.unincorporated) { parts.push('Unincorporated'); }
+  return parts.join(', ');
+}
+
+function renderProfile(p, definition) {
+  const far = definition === 'usda' ? p.far_any : p.far_grocery;
+  const farLabel = definition === 'usda' ? 'any SNAP store' : 'a grocery store';
+  return `
+    <p class="profile-name">${p.hood}</p>
+    <p class="profile-tract">Census tract ${p.name} (${statusFor(p, definition)})</p>
+    <dl class="facts">
+      <dt>Residents</dt><dd>${int(p.pop)}</dd>
+      <dt>Living over ${p.urban ? '1 mile' : '10 miles'} from ${farLabel}</dt><dd>${int(far)} (${pct(far, p.pop)})</dd>
+      <dt>Typical distance to a grocery store</dt><dd>${miles(p.dist_grocery)}</dd>
+      <dt>Households with no car</dt><dd>${int(p.nocar)} (${pct(p.nocar, p.hh)})</dd>
+      <dt>Households receiving SNAP</dt><dd>${int(p.snap)} (${pct(p.snap, p.hh)})</dd>
+      <dt>Median family income</dt><dd>${dollars(p.mfi)}</dd>
+      <dt>Poverty rate</dt><dd>${p.pov == null ? 'n/a' : `${p.pov}%`}</dd>
+      <dt>Annual grocery spending by residents</dt><dd>${dollars(p.spend)}</dd>
+    </dl>`;
+}
+
+function showProfile(p, definition) {
+  document.getElementById('profile-empty').hidden = true;
+  const body = document.getElementById('profile-body');
+  body.hidden = false;
+  body.innerHTML = renderProfile(p, definition);
+}
+
+export { showProfile };
diff --git a/js/rank.js b/js/rank.js
new file mode 100644
index 00000000..7fa8a0e8
--- /dev/null
+++ b/js/rank.js
@@ -0,0 +1,100 @@
+// Ranking step: weight sliders, the shortlist and numbered map markers.
+
+import { FACTORS, applyScores, shortlist } from './scores.js';
+import { int, dollars } from './format.js';
+
+const SPACING_MI = 2;
+
+function weightShare(weights, factor) {
+  const total = FACTORS.reduce((sum, f) => sum + weights[f], 0);
+  if (total === 0) { return '0%'; }
+  return `${Math.round((weights[factor] / total) * 100)}%`;
+}
+
+function itemHtml(p, i) {
+  const zone = p.oz_nominated ? 'zone nominee' : (p.oz_eligible ? 'zone eligible' : '');
+  return `
+    <li>
+      <button class="pick" type="button" data-geoid="${p.geoid}">
+        <span class="pick-head">
+          <span class="pick-rank">${i + 1}</span>
+          <span class="pick-name">${p.hood} <span class="pick-tract">tract ${p.name}</span></span>
+          <span class="pick-score"><span class="visually-hidden">Score </span>${Math.round(p.score)}</span>
+        </span>
+        <span class="pick-facts">${int(p.far_grocery)} beyond reach, ${dollars(p.market)} unserved${zone ? `, ${zone}` : ''}</span>
+      </button>
+    </li>`;
+}
+
+function createRanking({ map, tracts, state, onSelect, onChange }) {
+  const spacingEl = document.getElementById('opt-spacing');
+  const desertsEl = document.getElementById('opt-deserts');
+  const listEl = document.getElementById('shortlist');
+  const markers = L.layerGroup();
+  let picks = [];
+
+  function readWeights() {
+    for (const f of FACTORS) {
+      state.weights[f] = Number(document.getElementById(`w-${f}`).value);
+    }
+    for (const f of FACTORS) {
+      document.getElementById(`w-${f}-value`).textContent = weightShare(state.weights, f);
+    }
+  }
+
+  function drawMarkers() {
+    markers.clearLayers();
+    picks.forEach((p, i) => {
+      const icon = L.divIcon({
+        className: 'rank-marker',
+        html: `<span class="rank-num">${i + 1}</span>`,
+        iconSize: [24, 24],
+      });
+      L.marker([p.lat, p.lon], { icon, pane: 'rankPane', keyboard: false })
+        .on('click', () => onSelect(p.geoid))
+        .addTo(markers);
+    });
+  }
+
+  function update() {
+    readWeights();
+    applyScores(tracts, state.weights);
+    picks = shortlist(tracts, { size: 10, spacingMi: spacingEl.checked ? SPACING_MI : 0, desertsOnly: desertsEl.checked });
+    listEl.innerHTML = picks.map(itemHtml).join('');
+    drawMarkers();
+    onChange();
+  }
+
+  for (const f of FACTORS) {
+    document.getElementById(`w-${f}`).addEventListener('input', update);
+  }
+  spacingEl.addEventListener('change', update);
+  desertsEl.addEventListener('change', update);
+
+  // One listener on the list handles every pick, including ones drawn later.
+  listEl.addEventListener('click', (e) => {
+    const button = e.target.closest('.pick');
+    if (!button) { return; }
+    const p = picks.find((q) => q.geoid === button.dataset.geoid);
+    const zoom = Math.max(map.getZoom(), 12);
+    if (window.matchMedia('(prefers-reduced-motion: reduce)').matches) {
+      map.setView([p.lat, p.lon], zoom, { animate: false });
+    } else {
+      map.flyTo([p.lat, p.lon], zoom, { duration: 0.6 });
+    }
+    onSelect(p.geoid);
+  });
+
+  function show(visible) {
+    if (visible) {
+      markers.addTo(map);
+    } else {
+      markers.remove();
+    }
+  }
+
+  update();
+  return { show };
+}
+
+export { createRanking, weightShare };
diff --git a/js/results.js b/js/results.js
new file mode 100644
index 00000000..d53432c7
--- /dev/null
+++ b/js/results.js
@@ -0,0 +1,36 @@
+// Step 3 results
+
+import { int, money } from './format.js';
+
+function years(n) {
+  if (n == null) { return 'never'; }
+  if (n > 99) { return 'over 99 years'; }
+  const y = Math.max(Math.round(n), 1);
+  return y === 1 ? '1 year' : `${y} years`;
+}
+
+function renderResults(el, r) {
+  const fresh = Math.max(r.sales - r.shifted, 0);
+  const share = r.sales ? Math.round((r.shifted / r.sales) * 100) : 0;
+  const note = r.cityRevenue
+    ? `That's all the tax the stores collect. Counting only sales new to the city, it's ${money(r.newCityRevenue)} a year and ${years(r.newPayback)}.`
+    : 'Stores outside city limits pay the City of Houston no tax.';
+  el.innerHTML = `
+    <p class="lead-number">${int(r.newlyReached)}</p>
+    <p class="lead-label">residents newly within a mile of a grocery store</p>
+    <p class="lead-sub">${int(r.desertReached)} of them in food desert tracts, and ${int(r.carFreeReached)} car-free households</p>
+    <h3 class="ledger-group">Where the new stores' sales come from</h3>
+    <div class="split" role="img" aria-label="${share}% of new store sales come from existing stores">
+      <span class="split-old" style="width: ${share}%"></span><span class="split-new" style="width: ${100 - share}%"></span>
+    </div>
+    <p class="split-key"><span><i class="key-old"></i>${money(r.shifted)} from existing stores</span><span><i class="key-new"></i>${money(fresh)} new to the area</span></p>
+    <h3 class="ledger-group">What the city gets back</h3>
+    <p class="payback">${money(r.cost)} incentives &divide; ${money(r.cityRevenue)} a year in city tax = <b>${years(r.payback)}</b></p>
+    <p class="payback-note">${note}</p>
+    <dl class="ledger">
+      <div><dt>Projected store sales a year</dt><dd>${money(r.sales)}</dd></div>
+      <div><dt>Taxable sales a year</dt><dd>${money(r.taxable)}</dd></div>
+    </dl>`;
+}
+
+export { renderResults };
diff --git a/js/scores.js b/js/scores.js
new file mode 100644
index 00000000..bcbee1f6
--- /dev/null
+++ b/js/scores.js
@@ -0,0 +1,48 @@
+// Weighted site scores and the ranked shortlist.
+
+const FACTORS = ['need', 'viability', 'leverage'];
+
+// Weighted average of the three factor scores, each already 0 to 100. Tracts
+// with no need score (too few residents, or mostly group quarters) stay unscored.
+function scoreTract(p, weights) {
+  if (p.need == null) { return null; }
+  const total = FACTORS.reduce((sum, f) => sum + weights[f], 0);
+  if (total === 0) { return 0; }
+  return FACTORS.reduce((sum, f) => sum + p[f] * weights[f], 0) / total;
+}
+
+function applyScores(tracts, weights) {
+  for (const { properties: p } of tracts.features) {
+    p.score = scoreTract(p, weights);
+  }
+}
+
+// Straight-line distance in miles between two tract centers.
+function milesBetween(a, b) {
+  const toRad = Math.PI / 180;
+  const dLat = (b.lat - a.lat) * toRad;
+  const dLon = (b.lon - a.lon) * toRad;
+  const h = Math.sin(dLat / 2) ** 2 +
+    Math.cos(a.lat * toRad) * Math.cos(b.lat * toRad) * Math.sin(dLon / 2) ** 2;
+  return 7917.5 * Math.asin(Math.sqrt(h));
+}
+
+// Highest scores first; with spacing on, skip any tract whose center sits
+// within `spacingMi` of a something already on the list, since a store would
+// serve both of those tracts.
+function shortlist(tracts, { size = 10, spacingMi = 0, desertsOnly = false } = {}) {
+  const candidates = tracts.features
+    .map((f) => f.properties)
+    .filter((p) => p.score != null && (!desertsOnly || p.lila_grocery))
+    .sort((a, b) => b.score - a.score);
+
+  const picks = [];
+  for (const p of candidates) {
+    if (picks.length >= size) { break; }
+    if (spacingMi && picks.some((q) => milesBetween(p, q) < spacingMi)) { continue; }
+    picks.push(p);
+  }
+  return picks;
+}
+
+export { FACTORS, applyScores, shortlist, scoreTract, milesBetween };
diff --git a/js/stores.js b/js/stores.js
new file mode 100644
index 00000000..f5a47a6c
--- /dev/null
+++ b/js/stores.js
@@ -0,0 +1,50 @@
+const STORE_COLORS = {
+  grocery: '#1f7a4d',
+  small: '#2f8f9d',
+  dollar: '#b0457b',
+  convenience: '#8a8f96',
+};
+
+const STORE_LABELS = {
+  grocery: 'Grocery store',
+  small: 'Small grocer',
+  dollar: 'Dollar store or pharmacy',
+  convenience: 'Convenience store',
+};
+
+function createStoreLayers(stores) {
+  const renderer = L.svg({ pane: 'storePane' });
+  const layers = {};
+  for (const cat of Object.keys(STORE_COLORS)) {
+    layers[cat] = L.layerGroup();
+  }
+
+  for (const feature of stores.features) {
+    const { name, addr, cat } = feature.properties;
+    const [lon, lat] = feature.geometry.coordinates;
+    L.circleMarker([lat, lon], {
+      renderer,
+      pane: 'storePane',
+      radius: cat === 'grocery' ? 4.5 : 3.5,
+      color: '#fff',
+      weight: 1,
+      fillColor: STORE_COLORS[cat],
+      fillOpacity: 1,
+    })
+      .bindTooltip(`<b>${name}</b><span class="tip-type">${STORE_LABELS[cat]}, ${addr}</span>`)
+      .addTo(layers[cat]);
+  }
+
+  return layers;
+}
+
+function countStores(stores) {
+  const counts = {};
+  for (const feature of stores.features) {
+    const { cat } = feature.properties;
+    counts[cat] = (counts[cat] || 0) + 1;
+  }
+  return counts;
+}
+
+export { createStoreLayers, countStores, STORE_COLORS, STORE_LABELS };
diff --git a/js/tracts.js b/js/tracts.js
new file mode 100644
index 00000000..7426edce
--- /dev/null
+++ b/js/tracts.js
@@ -0,0 +1,103 @@
+// Census tract layer shaded by grocery access
+
+const FILLS = {
+  lila: '#c4441c',
+  la: '#f2b48c',
+  ok: '#f7f8f5',
+};
+const SCORE_BREAKS = [20, 40, 60, 80];
+const SCORE_FILLS = ['#eef4f3', '#c3dcdb', '#86b8b9', '#3f8589', '#14525e'];
+const UNSCORED = '#d9dbd6';
+
+const PLAN_FILLS = {
+  desert: FILLS.lila,
+  zone: SCORE_FILLS[2],
+  closed: UNSCORED,
+};
+
+const DEFINITIONS = {
+  grocery: { lila: 'lila_grocery', la: 'la_grocery', far: 'far_grocery' },
+  usda: { lila: 'lila_usda', la: 'la_usda', far: 'far_any' },
+};
+
+// lila = low income and low access (a food desert). la = low access only.
+function accessClass(p, definition) {
+  const fields = DEFINITIONS[definition];
+  if (p[fields.lila]) { return 'lila'; }
+  if (p[fields.la]) { return 'la'; }
+  return 'ok';
+}
+
+function scoreFill(score) {
+  if (score == null) { return UNSCORED; }
+  const i = SCORE_BREAKS.findIndex((b) => score < b);
+  return SCORE_FILLS[i === -1 ? SCORE_FILLS.length - 1 : i];
+}
+
+function tractStyle(p, state) {
+  const selected = p.geoid === state.selected;
+  const outline = {
+    color: selected ? '#1a211d' : 'rgb(18 26 22 / 22%)',
+    weight: selected ? 2.5 : 0.5,
+  };
+  if (state.mode === 'plan') {
+    const fill = p.lila_grocery ? PLAN_FILLS.desert : (p.oz_eligible || p.oz_nominated ? PLAN_FILLS.zone : PLAN_FILLS.closed);
+    return { ...outline, fillColor: fill, fillOpacity: fill === PLAN_FILLS.closed ? 0.2 : 0.6 };
+  }
+  if (state.mode === 'rank') {
+    return { ...outline, fillColor: scoreFill(p.score), fillOpacity: 0.8 };
+  }
+  const cls = accessClass(p, state.definition);
+  return { ...outline, fillColor: FILLS[cls], fillOpacity: cls === 'ok' ? 0.35 : 0.78 };
+}
+
+function tooltipFor(p, state) {
+  if (state.mode === 'plan') {
+    const open = p.lila_grocery || p.oz_eligible || p.oz_nominated;
+    return open ? `${p.hood}, tract ${p.name}` : `${p.hood}, tract ${p.name}<br>Not eligible for recruitment funds`;
+  }
+  if (state.mode === 'rank') {
+    const score = p.score == null ? 'not scored' : `score ${Math.round(p.score)}`;
+    return `${p.hood}, tract ${p.name}<br>${score}`;
+  }
+  return `${p.hood}, tract ${p.name}`;
+}
+
+function createTractLayer(tracts, state, onSelect) {
+  const layer = L.geoJSON(tracts, {
+    style: (f) => tractStyle(f.properties, state),
+    onEachFeature: (f, l) => {
+      l.bindTooltip(() => tooltipFor(f.properties, state), { sticky: true });
+      l.on('click', () => onSelect(f.properties.geoid));
+    },
+  });
+
+  // Recolor when the definition or selection changes instead of
+  // rebuilding the layer.
+  layer.restyle = () => {
+    layer.eachLayer((l) => {
+      l.setStyle(tractStyle(l.feature.properties, state));
+      if (l.feature.properties.geoid === state.selected) { l.bringToFront(); }
+    });
+  };
+
+  return layer;
+}
+
+// Headline numbers (desert tracts, population, and residents beyond reach of a store)
+function summarize(tracts, definition) {
+  const fields = DEFINITIONS[definition];
+  let count = 0;
+  let residents = 0;
+  let farTotal = 0;
+  for (const { properties: p } of tracts.features) {
+    farTotal += p[fields.far];
+    if (p[fields.lila]) {
+      count += 1;
+      residents += p.pop;
+    }
+  }
+  return { count, residents, farTotal };
+}
+
+export { FILLS, SCORE_BREAKS, SCORE_FILLS, UNSCORED, createTractLayer, summarize, accessClass, PLAN_FILLS };
diff --git a/scripts/build_data.py b/scripts/build_data.py
new file mode 100644
index 00000000..698b38eb
--- /dev/null
+++ b/scripts/build_data.py
@@ -0,0 +1,358 @@
+"""Build the browser data files for the Houston grocer placement tool.
+
+Reads the raw downloads in ../raw and writes small, browser-ready files to
+../data. Run from anywhere:  python3 -I scripts/build_data.py
+"""
+
+import csv
+import json
+from pathlib import Path
+
+import geopandas as gpd
+import numpy as np
+import pandas as pd
+from scipy.spatial import cKDTree
+
+ROOT = Path(__file__).resolve().parent.parent
+RAW = ROOT / 'raw'
+OUT = ROOT / 'data'
+OUT.mkdir(exist_ok=True)
+
+PROJ = 'EPSG:32615'          # UTM 15N, meters
+MILE = 1609.344
+URBAN_MI, RURAL_MI = 1, 10   # USDA's standard low access thresholds
+
+# ---------------------------------------------------------------- stores
+# Store types USDA's Large Retailer Access Map treats as grocery access.
+GROCERY_TYPES = {'Supermarket', 'Super Store', 'Large Grocery Store'}
+SMALL_GROCER_TYPES = {'Medium Grocery Store', 'Small Grocery Store'}
+EXCLUDED_FROM_SRAM = {"Farmers' Market", 'Delivery Route'}
+DOLLAR_DRUG = ('FAMILY DOLLAR', 'DOLLAR GENERAL', 'DOLLAR TREE', 'DOLLARTREE',
+               'WALGREENS', 'CVS')
+
+
+def store_category(name, kind):
+    upper = name.upper()
+    if kind in GROCERY_TYPES:
+        return 'grocery'
+    if kind in SMALL_GROCER_TYPES:
+        return 'small'
+    if any(upper.startswith(b) for b in DOLLAR_DRUG):
+        return 'dollar'
+    if kind == 'Convenience Store':
+        return 'convenience'
+    return 'other'
+
+
+# Stores are kept by location, not by the county the file lists: everything open
+# within 10 miles of the county line. Residents near the edge shop across it, and
+# a few stores listed as Harris County actually sit in Fort Bend or Montgomery.
+STORE_REACH_MI = 10
+with open(RAW / 'snap-retailers' / 'Historical SNAP Retailer Locator Data 2005-2025.csv',
+          encoding='utf-8-sig') as f:
+    rows = [r for r in csv.DictReader(f)
+            if r['State'] == 'TX' and not r['End Date'].strip()
+            and r['Store Type'] not in EXCLUDED_FROM_SRAM]
+
+stores = pd.DataFrame({
+    'name': [' '.join(r['Store Name'].split()).title() for r in rows],
+    'type': [r['Store Type'] for r in rows],
+    'addr': [' '.join(f"{r['Street Number']} {r['Street Name']}".split()).title() for r in rows],
+    'lon': [float(r['Longitude']) for r in rows],
+    'lat': [float(r['Latitude']) for r in rows],
+})
+stores['cat'] = [store_category(n, t) for n, t in zip(stores.name, stores.type)]
+stores = gpd.GeoDataFrame(stores, geometry=gpd.points_from_xy(stores.lon, stores.lat), crs=4326)
+harris = gpd.read_file(OUT / 'harris-boundary.geojson').to_crs(PROJ).geometry.unary_union
+stores = stores[stores.to_crs(PROJ).within(harris.buffer(STORE_REACH_MI * MILE))].reset_index(drop=True)
+stores_m = stores.to_crs(PROJ)
+print('stores by category:', stores.cat.value_counts().to_dict())
+
+# ---------------------------------------------------------------- tracts
+tracts = gpd.read_file(RAW / 'oz' / 'oz2-nominated-harris.geojson')
+tracts['geoid'] = tracts.GEO_ID.str[-11:]
+tracts['name'] = tracts.JOIN1.str.replace('Census Tract ', '', regex=False)
+tracts['oz_nominated'] = (tracts.EDT_REC == 'YES').astype(int)
+tracts['oz_eligible'] = (tracts.FED_RESULT == 'ELIGIBLE').astype(int)
+
+sram_g = pd.read_csv(RAW / 'usda-sram' / 'SRAM General Tract Characteristics Data.csv',
+                     dtype={'CensusTract20': str}, encoding='latin-1')
+sram_s = pd.read_csv(RAW / 'usda-sram' / 'SRAM Straight Line Distance Data.csv',
+                     dtype={'CensusTract20': str}, encoding='latin-1')
+sram = sram_g.merge(sram_s, on='CensusTract20', suffixes=('', '_s'))
+sram = sram[sram.CensusTract20.str.startswith('48201')].rename(columns={'CensusTract20': 'geoid'})
+tracts = tracts.merge(sram[['geoid', 'Urban', 'POP2020', 'OHU2020', 'MedianFamilyIncome',
+                            'PovertyRate', 'TractHUNV', 'TractSNAP', 'LowIncomeTracts',
+                            'GroupQuartersFlag', 'SD_SRAM_LA1and10', 'SD_SRAM_LILATracts_1And10',
+                            'SD_SRAM_lapop1']], on='geoid', how='left')
+tracts_m = tracts.to_crs(PROJ)
+
+# ---------------------------------------------------------------- blocks
+feats = []
+for p in sorted((RAW / 'census-blocks').glob('blocks-*.json')):
+    feats += [f['attributes'] for f in json.loads(p.read_text())['features']]
+blocks = pd.DataFrame(feats)
+blocks['tract'] = blocks.GEOID.str[:11]
+blocks = gpd.GeoDataFrame(blocks, geometry=gpd.points_from_xy(
+    blocks.INTPTLON.astype(float), blocks.INTPTLAT.astype(float)), crs=4326)
+blocks_m = blocks.to_crs(PROJ)
+bxy = np.c_[blocks_m.geometry.x, blocks_m.geometry.y]
+
+
+def nearest_mi(cats):
+    pts = stores_m[stores_m.cat.isin(cats)]
+    d, _ = cKDTree(np.c_[pts.geometry.x, pts.geometry.y]).query(bxy)
+    return d / MILE
+
+
+blocks['d_grocery'] = nearest_mi({'grocery'})
+blocks['d_any'] = nearest_mi({'grocery', 'small', 'dollar', 'convenience', 'other'})
+
+# transit: blocks within a quarter mile of a METRO stop
+stops = pd.read_csv(RAW / 'metro-gtfs' / 'stops.txt', dtype=str)
+stops = stops[stops.location_type.fillna('0').isin(['0', ''])]
+stops_g = gpd.GeoDataFrame(stops, geometry=gpd.points_from_xy(
+    stops.stop_lon.astype(float), stops.stop_lat.astype(float)), crs=4326).to_crs(PROJ)
+d_stop, _ = cKDTree(np.c_[stops_g.geometry.x, stops_g.geometry.y]).query(bxy)
+blocks['d_stop'] = d_stop / MILE
+
+# ---------------------------------------------------------------- tract measures
+urban = tracts.set_index('geoid').Urban.fillna(1).astype(int)
+blocks['limit'] = np.where(blocks.tract.map(urban).fillna(1) == 1, URBAN_MI, RURAL_MI)
+blocks['far_g'] = (blocks.d_grocery > blocks.limit) * blocks.POP100
+blocks['far_a'] = (blocks.d_any > blocks.limit) * blocks.POP100
+blocks['w_dist'] = blocks.d_grocery * blocks.POP100
+blocks['near_stop'] = (blocks.d_stop <= 0.25) * blocks.POP100
+agg = blocks.groupby('tract').agg(bpop=('POP100', 'sum'), far_g=('far_g', 'sum'),
+                                  far_a=('far_a', 'sum'), w_dist=('w_dist', 'sum'),
+                                  near_stop=('near_stop', 'sum'))
+tracts = tracts.merge(agg, left_on='geoid', right_index=True, how='left')
+for c in ['bpop', 'far_g', 'far_a', 'w_dist', 'near_stop']:
+    tracts[c] = tracts[c].fillna(0)
+
+
+def low_access(far, pop):
+    # USDA rule: 500+ people or a third of the tract beyond the distance limit
+    return ((far >= 500) | ((pop > 0) & (far / pop.replace(0, np.nan) >= 1 / 3))).astype(int)
+
+
+tracts['la_grocery'] = low_access(tracts.far_g, tracts.bpop)
+tracts['la_any'] = low_access(tracts.far_a, tracts.bpop)
+li = tracts.LowIncomeTracts.fillna(0).astype(int)
+tracts['lila_grocery'] = tracts.la_grocery * li
+tracts['lila_any_ours'] = tracts.la_any * li           # our replication of USDA's new map
+tracts['lila_usda'] = tracts.SD_SRAM_LILATracts_1And10.fillna(0).astype(int)
+
+# ---------------------------------------------------------------- grocery spending
+# BLS Consumer Expenditure Survey 2024, food at home by income quintile
+# (mean income before taxes, mean annual food-at-home spending per household).
+CE = json.loads((RAW / 'bls' / 'ce-food-by-quintile.json').read_text())
+series = {s['seriesID']: {d['year']: float(d['value']) for d in s['data']}
+          for s in CE['Results']['series']}
+inc = [series[f'CXUINCBEFTXLB010{q}M']['2024'] for q in range(2, 7)]
+food = [series[f'CXUFOODHOMELB010{q}M']['2024'] for q in range(2, 7)]
+mfi = tracts.MedianFamilyIncome
+tracts['food_hh'] = np.interp(mfi.fillna(np.nanmedian(mfi)), inc, food)
+tracts['spend'] = tracts.food_hh * tracts.OHU2020.fillna(0)
+
+# ---------------------------------------------------------------- scores
+# Each block's share of its tract's grocery spending, by population.
+per_cap = (tracts.set_index('geoid').spend / tracts.set_index('geoid').POP2020).replace(np.inf, 0)
+blocks['spend'] = blocks.POP100 * blocks.tract.map(per_cap).fillna(0)
+blocks['unserved'] = blocks.d_grocery > blocks.limit
+
+# Population-weighted center of each tract: where a store serving it would sit.
+blocks['wx'] = bxy[:, 0] * blocks.POP100
+blocks['wy'] = bxy[:, 1] * blocks.POP100
+cen = blocks.groupby('tract')[['wx', 'wy', 'POP100']].sum()
+cen['x'] = cen.wx / cen.POP100
+cen['y'] = cen.wy / cen.POP100
+
+# Viability: grocery spending by unserved residents within 2 miles of that center,
+# the market a new store could capture without fighting an existing one for it.
+TRADE_MI = 2
+tree = cKDTree(bxy)
+unserved_spend = blocks.spend.where(blocks.unserved, 0).to_numpy()
+cen['market'] = [unserved_spend[idx].sum()
+                 for idx in tree.query_ball_point(cen[['x', 'y']].to_numpy(), TRADE_MI * MILE)]
+cen_ll = gpd.GeoSeries(gpd.points_from_xy(cen.x, cen.y), crs=PROJ).to_crs(4326)
+cen['lon'] = cen_ll.x.to_numpy()
+cen['lat'] = cen_ll.y.to_numpy()
+tracts = tracts.merge(cen[['market', 'lon', 'lat']], left_on='geoid', right_index=True, how='left')
+
+# Neighborhood label at each tract's center: a City of Houston Super Neighborhood,
+# else the city or census-designated place it falls in, else unincorporated county.
+SMALL_WORDS = {'of', 'and', 'the'}
+ACRONYMS = {'OST', 'IAH'}
+
+
+def tidy(name):
+    words = name.replace('/', ' / ').split()
+    out = []
+    for i, w in enumerate(words):
+        if w in ACRONYMS:
+            out.append(w)
+        elif i and w.lower() in SMALL_WORDS:
+            out.append(w.lower())
+        else:
+            out.append('-'.join(part.capitalize() for part in w.split('-')))
+    return ' '.join(out).replace(' / ', '/')
+
+
+centers = gpd.GeoDataFrame(cen[['lon', 'lat']], geometry=gpd.points_from_xy(cen.lon, cen.lat), crs=4326)
+snb = gpd.read_file(RAW / 'neighborhoods' / 'super-neighborhoods.geojson')[['SNBNAME', 'geometry']]
+cities = gpd.read_file(RAW / 'neighborhoods' / 'places-26.geojson')[['BASENAME', 'geometry']]
+cdp = gpd.read_file(RAW / 'neighborhoods' / 'places-28.geojson')[['BASENAME', 'geometry']]
+
+
+def label_from(polys, col):
+    hit = gpd.sjoin(centers, polys, how='left', predicate='within')
+    return hit[~hit.index.duplicated()][col]
+
+
+in_city = label_from(cities, 'BASENAME')
+hood = label_from(snb, 'SNBNAME').map(lambda n: tidy(n) if isinstance(n, str) else None)
+hood = hood.fillna(in_city.where(in_city != 'Houston')).fillna(label_from(cdp, 'BASENAME'))
+
+# Tracts still unnamed sit in unincorporated areas with no census place. Name them
+# for the nearest well-known community in USGS's Geographic Names Information System.
+# Many GNIS names are old rail stops or crossroads few residents would recognize
+# ("Deco", "Hot Wells"), so only communities people still use as place names count.
+NEAR_MI = 6
+KNOWN_COMMUNITIES = {
+    'Addicks', 'Aldine', 'Alief', 'Atascocita', 'Barker', 'Barrett', 'Baytown',
+    'Beaumont Place', 'Bellaire', 'Bordersville', 'Cedar Bayou', 'Channelview', 'Cinco Ranch',
+    'Clear Lake City', 'Clodine', 'Cloverleaf', 'Crosby', 'Cypress', 'Deer Park', 'Dyersdale',
+    'Fairbanks', 'Friendswood', 'Galena Park', 'Highlands', 'Hockley', 'Huffman', 'Humble',
+    'Jacinto City', 'Jersey Village', 'Katy', 'Kingwood', 'Klein', 'La Porte',
+    'Louetta', 'McNair', 'Mission Bend', 'Missouri City', 'Pasadena', 'Pearland',
+    'Seabrook', 'Sheldon', 'South Houston', 'Spring', 'Stafford', 'The Woodlands', 'Tomball',
+    'Waller', 'Webster', 'Westfield',
+}
+gnis = gpd.read_file(RAW / 'neighborhoods' / 'gnis-communities.geojson').explode(index_parts=False)
+gnis = gnis[gnis.gaz_name.isin(KNOWN_COMMUNITIES)].drop_duplicates('gaz_name').to_crs(PROJ)
+gnis_tree = cKDTree(np.c_[gnis.geometry.x, gnis.geometry.y])
+d_gnis, i_gnis = gnis_tree.query(cen[['x', 'y']].to_numpy())
+near = pd.Series(np.where(d_gnis / MILE <= NEAR_MI, 'Near ' + gnis.gaz_name.to_numpy()[i_gnis], None),
+                 index=cen.index)
+hood = hood.fillna(near)
+tracts['hood'] = tracts.geoid.map(hood).fillna('Unincorporated Harris County')
+tracts['unincorporated'] = tracts.geoid.map(in_city.isna()).fillna(True).astype(int)
+
+# Tracts too small or mostly group quarters (jails, dorms) are not scored.
+scored = (tracts.POP2020.fillna(0) >= 500) & (tracts.GroupQuartersFlag.fillna(0) == 0)
+
+
+def rank(series):
+    return series.where(scored).rank(pct=True) * 100
+
+
+far_share = tracts.far_g / tracts.bpop.replace(0, np.nan)
+tracts['need_far'] = rank(tracts.far_g)
+tracts['need_nocar'] = rank(tracts.TractHUNV.fillna(0) * far_share.fillna(0))
+tracts['need_pov'] = rank(tracts.PovertyRate)
+tracts['need'] = tracts[['need_far', 'need_nocar', 'need_pov']].mean(axis=1)
+tracts['viability'] = rank(tracts.market)
+tracts['leverage'] = np.where(tracts.oz_nominated == 1, 100,
+                              np.where(tracts.oz_eligible == 1, 50, 0)).astype(float)
+tracts.loc[~scored, ['need', 'viability', 'leverage']] = np.nan
+
+# ---------------------------------------------------------------- write tracts
+out = tracts.copy()
+out['geometry'] = out.geometry.simplify(0.00025, preserve_topology=True)
+out = gpd.GeoDataFrame({
+    'geoid': out.geoid,
+    'name': out.name,
+    'hood': out.hood,
+    'unincorporated': out.unincorporated,
+    'pop': out.POP2020.fillna(0).astype(int),
+    'hh': out.OHU2020.fillna(0).astype(int),
+    'mfi': out.MedianFamilyIncome.round(0),
+    'pov': out.PovertyRate.round(1),
+    'nocar': out.TractHUNV.fillna(0).astype(int),
+    'snap': out.TractSNAP.fillna(0).astype(int),
+    'urban': out.Urban.fillna(1).astype(int),
+    'gq': out.GroupQuartersFlag.fillna(0).astype(int),
+    'low_income': li,
+    'far_grocery': out.far_g.round(0).astype(int),
+    'far_any': out.far_a.round(0).astype(int),
+    'dist_grocery': (out.w_dist / out.bpop.replace(0, np.nan)).round(2),
+    'near_stop_share': (out.near_stop / out.bpop.replace(0, np.nan)).round(3),
+    'la_grocery': out.la_grocery,
+    'lila_grocery': out.lila_grocery,
+    'lila_usda': out.lila_usda,
+    'la_usda': out.SD_SRAM_LA1and10.fillna(0).astype(int),
+    'spend': out.spend.round(-3).astype(int),
+    'oz_nominated': out.oz_nominated,
+    'oz_eligible': out.oz_eligible,
+    'market': out.market.round(-3),
+    'need': out.need.round(1),
+    'need_far': out.need_far.round(0),
+    'need_nocar': out.need_nocar.round(0),
+    'need_pov': out.need_pov.round(0),
+    'viability': out.viability.round(1),
+    'leverage': out.leverage,
+    'lon': out.lon.round(5),
+    'lat': out.lat.round(5),
+}, geometry=out.geometry, crs=4326)
+out.to_file(OUT / 'tracts.geojson', driver='GeoJSON', COORDINATE_PRECISION=5)
+
+# ---------------------------------------------------------------- write stores
+s = stores[stores.cat != 'other']
+s_out = gpd.GeoDataFrame(s[['name', 'type', 'addr', 'cat']], geometry=s.geometry, crs=4326)
+s_out.to_file(OUT / 'stores.geojson', driver='GeoJSON', COORDINATE_PRECISION=5)
+
+# ---------------------------------------------------------------- Huff model inputs
+# Each block's pull toward existing grocery stores: the sum of store size over
+# distance squared, for stores within 5 miles. The browser adds new stores to it.
+HUFF_MI = 5
+MIN_MI = 0.25
+SIZE = {'Super Store': 1.5, 'Supermarket': 1.0, 'Large Grocery Store': 0.6}
+groc = stores_m[stores_m.cat == 'grocery']
+gxy = np.c_[groc.geometry.x, groc.geometry.y]
+gsize = groc['type'].map(SIZE).to_numpy()
+gtree = cKDTree(gxy)
+pull = np.zeros(len(blocks))
+for i, idx in enumerate(gtree.query_ball_point(bxy, HUFF_MI * MILE)):
+    if idx:
+        d = np.maximum(np.hypot(*(gxy[idx] - bxy[i]).T) / MILE, MIN_MI)
+        pull[i] = (gsize[idx] / d ** 2).sum()
+blocks['pull'] = pull
+
+# ---------------------------------------------------------------- write blocks (compact)
+tract_index = {g: i for i, g in enumerate(out.geoid)}
+packed = {
+    'fields': ['lon', 'lat', 'pop', 'tract', 'd_grocery', 'near_stop', 'pull', 'spend'],
+    'rows': [[round(x, 5), round(y, 5), int(p), tract_index[t], round(float(d), 2), int(ns <= 0.25),
+              round(float(pl), 3), int(sp)]
+             for x, y, p, t, d, ns, pl, sp in zip(blocks.geometry.x, blocks.geometry.y, blocks.POP100,
+                                                  blocks.tract, blocks.d_grocery, blocks.d_stop,
+                                                  blocks.pull, blocks.spend)],
+}
+(OUT / 'blocks.json').write_text(json.dumps(packed, separators=(',', ':')))
+
+# ---------------------------------------------------------------- write city limits
+city = gpd.read_file(RAW / 'neighborhoods' / 'places-26.geojson')
+city = city[city.BASENAME == 'Houston'][['BASENAME', 'geometry']]
+city['geometry'] = city.geometry.simplify(0.0003, preserve_topology=True)
+city.to_file(OUT / 'houston-city.geojson', driver='GeoJSON', COORDINATE_PRECISION=5)
+
+# ---------------------------------------------------------------- write stops (compact)
+(OUT / 'stops.json').write_text(json.dumps(
+    [[round(float(x), 5), round(float(y), 5)] for x, y in zip(stops.stop_lon, stops.stop_lat)],
+    separators=(',', ':')))
+
+# ---------------------------------------------------------------- summary
+print('tracts', len(out), 'population', int(out['pop'].sum()))
+print('blocks with no grocery store within 5 miles:', int((blocks.pull == 0).sum()))
+print('LILA, USDA official (all SNAP stores):', int(out.lila_usda.sum()))
+print('LILA, our replication with all SNAP stores:', int(tracts.lila_any_ours.sum()))
+print('LILA, grocery stores only:', int(out.lila_grocery.sum()))
+print('low access, grocery only (any income):', int(out.la_grocery.sum()))
+print('people beyond limit from grocery:', int(out.far_grocery.sum()),
+      '| from any SNAP store:', int(out.far_any.sum()))
+print('OZ nominated:', int(out.oz_nominated.sum()), 'eligible:', int(out.oz_eligible.sum()))
+print('county food-at-home spending ($B):', round(out.spend.sum() / 1e9, 2))
+print('scored tracts:', int(out.need.notna().sum()), '| median market ($M):', round(out.market.median() / 1e6, 1), '| max:', round(out.market.max() / 1e6, 1))
+for p in sorted(OUT.iterdir()):
+    print(f'{p.name}: {p.stat().st_size / 1e6:.2f} MB')