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Add solar-power-app — interactive rooftop solar panel planner
Interactive MATLAB app for planning rooftop solar installations. Enter any address to load satellite imagery, draw panels, optimize tilt, and estimate annual energy yield. Includes live scripts for address-based analysis, core function demos, and US solar potential mapping. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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‎Examples/solar-power-app/.gitignore‎

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# MATLAB temporary files
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*.asv
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*.m~
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*.autosave
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# Simulink autosave
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*.slxc
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slprj/
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# Generated outputs
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SolarReport.pdf
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# Tooling
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.claude/
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.mcp.json
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# OS files
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.DS_Store
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Thumbs.db
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desktop.ini

‎Examples/solar-power-app/AddressSolarAnalysis.m‎

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%[text] # Solar Analysis for Any Address
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%[text] Enter a street address and get a complete solar energy analysis for that location. Uses the OpenStreetMap Nominatim geocoder to convert the address to coordinates, then computes sun position and panel output across the year.
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%%
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%[text] ## Enter Your Address
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%[text] Change the address below to analyze any location.
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address = "3 Apple Hill Drive, Natick, MA";
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%%
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%[text] ## Geocode the Address
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[lat, lon, displayName] = geocodeAddress(address);
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fprintf("Location: %s\n", displayName)
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fprintf("Coordinates: %.4f°N, %.4f°E\n", lat, lon)
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%%
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%[text] ## Panel Configuration
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panelEfficiency = 0.20;
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panelArea = 1.6; % m^2
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panelTilt = abs(lat); % rule-of-thumb: tilt = latitude
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panelAzimuth = 180; % south-facing (northern hemisphere)
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%%
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%[text] ## Show Location on Map
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%[text] Display the location on a geographic map with satellite basemap.
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figure('Position', [100 100 700 500])
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geoplot(lat, lon, 'rp', 'MarkerSize', 20, 'MarkerFaceColor', 'r')
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geobasemap satellite
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title(sprintf("Solar Analysis Site: %s", address))
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geolimits([lat-0.01 lat+0.01], [lon-0.01 lon+0.01])
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%%
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%[text] ## Sun Path Diagram
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%[text] Compute sun paths for solstices and equinoxes at this location.
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figure('Position', [100 100 600 600])
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dates = [datetime(2024,3,20), datetime(2024,6,21), ...
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datetime(2024,9,22), datetime(2024,12,21)];
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labels = ["Spring Equinox", "Summer Solstice", "Autumn Equinox", "Winter Solstice"];
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colors = [0.2 0.7 0.3; 0.85 0.33 0.1; 0.6 0.4 0.0; 0.1 0.4 0.8];
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polaraxes;
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hold on
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for k = 1:4
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t = datetime(dates(k), 'TimeZone', 'UTC') + minutes(0:5:1439);
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[az, el] = sunPosition(lat, lon, t);
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daytime = el > 0;
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polarplot(deg2rad(az(daytime)), 90 - el(daytime), ...
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'Color', colors(k,:), 'LineWidth', 2)
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end
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hold off
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ax = gca;
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ax.ThetaZeroLocation = 'top';
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ax.ThetaDir = 'clockwise';
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ax.RLim = [0 90];
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ax.RTickLabel = {'90°','60°','30°','0°'};
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title(sprintf("Sun Path — %s (%.2f°N)", address, lat))
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legend(labels, 'Location', 'southoutside', 'Orientation', 'horizontal')
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%%
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%[text] ## Monthly Energy Yield
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%[text] Compute the expected monthly clear-sky energy production.
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daysPerMonth = [31 29 31 30 31 30 31 31 30 31 30 31];
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monthlyEnergy = zeros(1, 12);
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for m = 1:12
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t = datetime(2024, m, 15, 'TimeZone', 'UTC') + hours(0:23);
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[az, el] = sunPosition(lat, lon, t);
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w = solarPanelPower(panelEfficiency, panelArea, az, el, panelTilt, panelAzimuth);
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dailyKWh = sum(w) / 1000;
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monthlyEnergy(m) = dailyKWh * daysPerMonth(m);
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end
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annualTotal = sum(monthlyEnergy);
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%%
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%[text] Plot the monthly breakdown.
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figure
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bar(1:12, monthlyEnergy, 'FaceColor', [0.9 0.5 0.1], 'EdgeColor', 'none')
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xlabel("Month")
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ylabel("Energy (kWh)")
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title(sprintf("Monthly Solar Energy — %s", address))
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subtitle(sprintf("Annual total: %.0f kWh/panel (clear sky) | Tilt: %.0f° South", ...
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annualTotal, panelTilt))
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xticklabels(["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"])
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grid on
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%%
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%[text] ## Daily Power Curves by Season
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%[text] Show how power output varies through the day for each season.
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figure
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hold on
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dailyYield = zeros(1, 4);
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for k = 1:4
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t = datetime(dates(k), 'TimeZone', 'UTC') + minutes(0:10:1439);
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[az, el] = sunPosition(lat, lon, t);
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w = solarPanelPower(panelEfficiency, panelArea, az, el, panelTilt, panelAzimuth);
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plot(hours(t - t(1)), w, 'Color', colors(k,:), 'LineWidth', 1.5)
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dailyYield(k) = trapz(hours(t - t(1)), w) / 1000;
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end
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hold off
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xlabel("Hour of Day (UTC)")
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ylabel("Power (W)")
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title(sprintf("Daily Power Profiles — %s", address))
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legend(labels + " (" + compose("%.1f", dailyYield) + " kWh)", 'Location', 'northwest')
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grid on
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xlim([0 24])
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%%
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%[text] ## Summary
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%[text] This analysis provides clear-sky estimates. Actual production will be lower due to:
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%[text] - Cloud cover and weather
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%[text] - Shading from buildings and trees
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%[text] - Panel degradation and inverter losses
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%[text] - Temperature effects \
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%[text]
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%[text] A typical derating factor is 0.75–0.80 for real-world conditions. Multiply the annual total by this factor for a more realistic estimate.
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realisticEstimate = annualTotal * 0.77;
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fprintf("Realistic annual estimate (77%% derating): %.0f kWh/panel\n", realisticEstimate)
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%%
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%[text] ---
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%[text] *Functions used: `geocodeAddress`, `sunPosition`, `solarPanelPower`, `geoplot`*
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%[appendix]{"version":"1.0"}
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%---
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%[metadata:view]
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% data: {"layout":"inline"}
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%---

‎Examples/solar-power-app/README.md‎

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# Solar Panel Planner for MATLAB&reg;
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![Solar Panel Planner App](hero.gif)
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An interactive application for planning rooftop solar panel installations using satellite imagery, sun-position modeling, and energy yield estimation in MATLAB&reg;.
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## Overview
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This app lets you enter any street address, view the rooftop on a satellite map, draw solar panel rectangles interactively, and estimate annual energy production. It models:
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- **Sun position** throughout the year (altitude and azimuth for any latitude/longitude)
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- **Clear-sky irradiance** with air mass and atmospheric effects
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- **Temperature derating** using NOCT (Nominal Operating Cell Temperature) model
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- **Clearness index** from NASA POWER monthly averages
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- **Panel tilt optimization** for maximum annual yield
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## Quick Start
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```matlab
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% Launch the interactive app
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SolarPanelApp()
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```
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1. Enter an address and click **Load** to fetch satellite imagery
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2. Click **+ Add Panel** to draw panel rectangles on the roof
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3. Adjust tilt with the slider or click **Optimize** for maximum yield
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4. View daily power curves and monthly energy bar charts in real time
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## Scripts
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| Script | Description |
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|--------|-------------|
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| `AddressSolarAnalysis.m` | Enter any address and get a full year solar analysis |
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| `SolarPanelDemo.m` | Demonstrates core functions: sun position, irradiance, panel power |
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| `SolarPotentialMap.m` | Visualizes solar potential across the United States |
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## Key Functions
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| Function | Description |
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|----------|-------------|
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| `sunPosition` | Solar altitude and azimuth for any location and time |
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| `solarPanelPower` | Instantaneous panel power output (W) given conditions |
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| `clearnessIndex` | Monthly clearness index from latitude/longitude |
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| `ambientTemperature` | Hourly ambient temperature from sinusoidal model |
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| `geocodeAddress` | Convert street address to lat/lon via OpenStreetMap Nominatim |
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| `fetchBuildings` | Fetch building footprints from OpenStreetMap Overpass API |
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| `packPanels` | Fit panel rectangles within a building polygon |
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## Requirements
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- MATLAB&reg; R2023a or later
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- Mapping Toolbox&trade;
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- MATLAB Report Generator&trade; (optional, for PDF export)
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- Internet connection (satellite basemap, geocoding, building footprints)

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