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SolarMap.PH data products

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data/SCHEMA.md ADDED
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+ # SolarMap.PH data product schema
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+
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+ Every file in `site/public/data/` is published under CC-BY-4.0. Cite as:
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+
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+ > SolarMap.PH (YYYY-QN), https://github.com/xmpuspus/solar-map-ph
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+
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+ All geometry is in EPSG:4326 (WGS84). All distances are meters unless noted.
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+
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+ ## Files
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+
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+ | File | Granularity | Used by |
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+ |---|---|---|
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+ | `per_building_solar_ncr.geojson` | Per OSM building (commercial/industrial/public only) | `/map`, `/safety`, `/` roof lookup |
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+ | `residential_solar_aggregate.json` | Counts only, no geometry | `/safety` |
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+ | `rooftop_solar_ncr.geojson` | Per 240m tile center | `/map` |
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+ | `city_solar_saturation.json` | Per 240m cell, summed across NCR | `/safety` saturation index |
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+ | `solar_map_ph_YYYYQN.geojson` | Per city | `/map` choropleth |
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+ | `solar_map_ph_barangay_YYYYQN.geojson` | Per barangay, urban-area drilldown | `/map` |
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+ | `solar_map_ph_summary_YYYYQN.json` | Franchise-wide totals | `/methodology` |
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+ | `manifest.json` | Index of available quarters | site bootstrap |
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+
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+ ## per_building_solar_ncr.geojson
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+
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+ One Feature per OSM building with detected rooftop solar. Residential roofs are intentionally suppressed; see `residential_solar_aggregate.json` for counts.
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+
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+ ```jsonc
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+ {
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+ "type": "Feature",
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+ "geometry": { "type": "Polygon", "coordinates": [[[lon, lat], ...]] },
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+ "properties": {
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+ "building_osm_id": 604560854, // OSM way or relation id
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+ "building_osm_type": "way", // "way" or "relation"
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+ "building_area_m2": 1834.2, // m^2, area of the OSM building footprint
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+ "building_type": "commercial", // OSM `building=*` value, or `amenity` fallback
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+ "is_residential": false, // always false in the published file
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+ "is_commercial": true,
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+ "panel_area_m2": 412.7, // m^2, summed across SAM segments, capped at footprint
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+ "kwp_estimate": 68.78, // panel_area_m2 / 6.0 (CSi rule-of-thumb)
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+ "confidence": 0.9183, // max calibrated segment score
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+ "n_segments_merged": 4, // SAM segments merged onto this building
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+ "tile_ids": ["14.59345_121.10221", ...],
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+ "tile_id": "14.59345_121.10221", // primary (highest-confidence) tile
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+ "tile_score": 0.9871 // CLIP+LR tile-level score for the primary tile
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+ }
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+ }
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+ ```
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+
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+ `_meta` on the FeatureCollection root reports `generated_utc`, `tiles_processed`, `buildings_with_solar_published`, `buildings_residential_suppressed`, `kwp_per_m2`, `scoring`, `polygon_strategy`, `area_strategy`, `privacy_policy`, and `tiles_overpass_failed`.
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+
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+ ### Caveats
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+
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+ - `kwp_estimate` uses the 2015-era 6 m^2 per kWp rule of thumb (~167 W/m^2). Modern PH commercial installs run 5-7 m^2 per kWp. Use a 0.85-1.20 sensitivity band when downstream of this number.
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+ - `panel_area_m2` is capped at the OSM building footprint area as a sanity gate against SAM over-segmenting nearby ground.
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+ - For solar arrays spanning multiple buildings, `kwp_estimate` is a lower bound: each SAM segment is attributed to a single OSM building.
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+
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+ ## residential_solar_aggregate.json
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+
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+ ```jsonc
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+ {
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+ "generated_utc": "2026-05-12T17:55:00Z",
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+ "n_residential_buildings_with_solar": 27,
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+ "kwp_residential_total": 917.18,
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+ "by_building_type": {
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+ "apartments": 4,
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+ "house": 21,
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+ "residential": 2
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+ },
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+ "policy": "Residential rooftops are intentionally not published as individual polygons..."
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+ }
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+ ```
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+
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+ No geometry, no addresses, no per-building entries. This is the only residential-scoped figure SolarMap.PH releases.
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+
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+ ## rooftop_solar_ncr.geojson
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+
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+ One Point feature per 240m tile center that scored above the candidate threshold.
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+
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+ ```jsonc
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+ {
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+ "type": "Feature",
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+ "geometry": { "type": "Point", "coordinates": [lon, lat] },
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+ "properties": {
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+ "tile_id": "14.59345_121.10221",
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+ "score": 0.9871, // calibrated probability of containing rooftop solar
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+ "tier": "high", // "high" (>=0.85) or "candidate" (0.70-0.85)
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+ "anchored_to_building": true,
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+ "osm_status": "confirmed", // "confirmed" if within 50 m of an OSM solar tag
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+ "kwp_estimate": 68.78 // copied from per_building when anchored
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+ }
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+ }
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+ ```
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+
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+ ## city_solar_saturation.json
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+
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+ One row per 240m cell across NCR with a count of high-confidence detections within a 300 m halo. Used by the saturation-tier card on `/safety` and inside the roof-lookup tool.
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+
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+ ```jsonc
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+ [
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+ {
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+ "cell_lat": 14.59345,
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+ "cell_lon": 121.10221,
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+ "n_high_within_300m": 5,
103
+ "n_buildings_solar_within_300m": 4,
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+ "kwp_within_300m": 73.21,
105
+ "saturation_tier": "growing" // "early", "growing", "saturated"
106
+ }
107
+ ]
108
+ ```
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+
110
+ ## solar_map_ph_YYYYQN.geojson (city-level composite)
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+
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+ Earth Engine multi-signal composite, one polygon per franchise city.
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+
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+ ```jsonc
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+ {
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+ "type": "Feature",
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+ "geometry": { "type": "Polygon", "coordinates": [...] },
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+ "properties": {
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+ "city": "Quezon City",
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+ "province": "Metro Manila",
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+ "psgc_code": "1380700000",
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+ "composite": 0.74, // [0,1], higher = stronger multi-signal solar signature
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+ "nir_delta_z": 1.42, // z-scored across cities
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+ "swir_delta_z": 0.93,
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+ "lst_anomaly_z": 0.41,
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+ "nightlight_delta_z": 0.08,
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+ "built_km2": 161.2,
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+ "quarter": "2026Q2",
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+ "baseline_year": 2022
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+ }
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+ }
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+ ```
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+
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+ The composite is correlative, not diagnostic. See `/methodology` on the site for the full algorithm.
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+
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+ ## License and citation
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+
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+ All files: CC-BY-4.0. Cite as `SolarMap.PH (YYYY-QN), https://github.com/xmpuspus/solar-map-ph`. Citing the software itself: see `CITATION.cff` at repo root.
data/case_studies.json ADDED
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+ {
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+ "generated_utc": "2026-05-08T08:52:47Z",
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+ "validation_methodology": "Hand-checked against Esri World Imagery (~1-3 yr vintage in PH). Each location showed a visibly distinct rooftop solar panel array at the centered lat/lon. Six confirmed of 169 reviewable hot-spots in the 2026Q2 v1.0 release. See docs/groundtruth/labels.json for the full validation pass.",
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+ "cases": [
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+ {
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+ "id": "makati",
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+ "city": "Makati",
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+ "province": "Metro Manila",
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+ "lat": 14.5472,
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+ "lon": 121.0398,
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+ "area_m2": 39404,
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+ "kwp_equiv": 5911,
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+ "note": "rooftop panel grid in dense urban Makati; verified against Esri 2022 hi-res",
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+ "v0_hotspot_idx": "007",
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+ "image_path": "/case_studies/makati.jpg",
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+ "image_ok": true
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+ },
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+ {
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+ "id": "valenzuela",
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+ "city": "Valenzuela",
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+ "province": "Metro Manila",
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+ "lat": 14.7194,
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+ "lon": 120.9349,
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+ "area_m2": 74114,
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+ "kwp_equiv": 11117,
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+ "note": "warehouse-scale dark gridded array in northern Valenzuela",
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+ "v0_hotspot_idx": "047",
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+ "image_path": "/case_studies/valenzuela.jpg",
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+ "image_ok": true
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+ },
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+ {
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+ "id": "meycauayan",
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+ "city": "Meycauayan",
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+ "province": "Bulacan",
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+ "lat": 14.7504,
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+ "lon": 120.9549,
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+ "area_m2": 79892,
38
+ "kwp_equiv": 11984,
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+ "note": "Bulacan industrial belt; warehouse rooftop with dark panel grid",
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+ "v0_hotspot_idx": "052",
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+ "image_path": "/case_studies/meycauayan.jpg",
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+ "image_ok": true
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+ },
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+ {
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+ "id": "san_mateo",
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+ "city": "San Mateo",
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+ "province": "Rizal",
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+ "lat": 14.6945,
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+ "lon": 121.1405,
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+ "area_m2": 61382,
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+ "kwp_equiv": 9207,
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+ "note": "industrial warehouse with dark gridded roof on Rizal side",
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+ "v0_hotspot_idx": "077",
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+ "image_path": "/case_studies/san_mateo.jpg",
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+ "image_ok": true
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+ },
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+ {
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+ "id": "dasmarinas",
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+ "city": "Dasmari\u00f1as",
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+ "province": "Cavite",
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+ "lat": 14.3113,
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+ "lon": 120.9532,
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+ "area_m2": 78891,
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+ "kwp_equiv": 11834,
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+ "note": "Cavite industrial roof with dark gridded sections; one of the largest detected",
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+ "v0_hotspot_idx": "116",
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+ "image_path": "/case_studies/dasmarinas.jpg",
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+ "image_ok": true
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+ },
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+ {
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+ "id": "carmona",
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+ "city": "Carmona",
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+ "province": "Cavite",
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+ "lat": 14.2845,
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+ "lon": 121.0177,
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+ "area_m2": 66524,
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+ "kwp_equiv": 9979,
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+ "note": "Carmona industrial complex; visible solar panel array on warehouse roof",
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+ "v0_hotspot_idx": "137",
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+ "image_path": "/case_studies/carmona.jpg",
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+ "image_ok": true
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+ }
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+ ]
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+ }
data/city_detection_counts.json ADDED
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1
+ {
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+ "_meta": {
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+ "n_cities_with_detections": 41,
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+ "n_total_high": 277,
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+ "n_total_candidate": 227,
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+ "n_total_new_high": 242,
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+ "share_new_high": 0.874
8
+ },
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+ "rows": [
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+ {
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+ "name": "Quezon City",
12
+ "province": "Metro Manila",
13
+ "n_high": 36,
14
+ "n_candidate": 33,
15
+ "n_new_high": 27,
16
+ "n_confirmed_high": 9,
17
+ "n_new_candidate": 31,
18
+ "n_confirmed_candidate": 2,
19
+ "sum_kwp_high": 15602.0,
20
+ "sum_kwp_all": 15602.0,
21
+ "area_km2": 160.54,
22
+ "high_per_km2": 0.2242
23
+ },
24
+ {
25
+ "name": "Valenzuela",
26
+ "province": "Metro Manila",
27
+ "n_high": 20,
28
+ "n_candidate": 12,
29
+ "n_new_high": 18,
30
+ "n_confirmed_high": 2,
31
+ "n_new_candidate": 9,
32
+ "n_confirmed_candidate": 3,
33
+ "sum_kwp_high": 4048.1,
34
+ "sum_kwp_all": 4048.1,
35
+ "area_km2": 46.97,
36
+ "high_per_km2": 0.4258
37
+ },
38
+ {
39
+ "name": "Calamba",
40
+ "province": "Laguna",
41
+ "n_high": 17,
42
+ "n_candidate": 8,
43
+ "n_new_high": 17,
44
+ "n_confirmed_high": 0,
45
+ "n_new_candidate": 8,
46
+ "n_confirmed_candidate": 0,
47
+ "sum_kwp_high": 8391.0,
48
+ "sum_kwp_all": 8391.0,
49
+ "area_km2": 167.77,
50
+ "high_per_km2": 0.1013
51
+ },
52
+ {
53
+ "name": "Cabuyao",
54
+ "province": "Laguna",
55
+ "n_high": 15,
56
+ "n_candidate": 8,
57
+ "n_new_high": 15,
58
+ "n_confirmed_high": 0,
59
+ "n_new_candidate": 8,
60
+ "n_confirmed_candidate": 0,
61
+ "sum_kwp_high": 1617.6,
62
+ "sum_kwp_all": 1617.6,
63
+ "area_km2": 80.95,
64
+ "high_per_km2": 0.1853
65
+ },
66
+ {
67
+ "name": "Bulacan",
68
+ "province": "Bulacan",
69
+ "n_high": 15,
70
+ "n_candidate": 8,
71
+ "n_new_high": 15,
72
+ "n_confirmed_high": 0,
73
+ "n_new_candidate": 8,
74
+ "n_confirmed_candidate": 0,
75
+ "sum_kwp_high": 681.2,
76
+ "sum_kwp_all": 681.2,
77
+ "area_km2": 2951.17,
78
+ "high_per_km2": 0.0051
79
+ },
80
+ {
81
+ "name": "Pasay",
82
+ "province": "Metro Manila",
83
+ "n_high": 13,
84
+ "n_candidate": 7,
85
+ "n_new_high": 12,
86
+ "n_confirmed_high": 1,
87
+ "n_new_candidate": 3,
88
+ "n_confirmed_candidate": 4,
89
+ "sum_kwp_high": 2684.2,
90
+ "sum_kwp_all": 2684.2,
91
+ "area_km2": 34.06,
92
+ "high_per_km2": 0.3817
93
+ },
94
+ {
95
+ "name": "Dasmarinas",
96
+ "province": "Cavite",
97
+ "n_high": 12,
98
+ "n_candidate": 15,
99
+ "n_new_high": 8,
100
+ "n_confirmed_high": 4,
101
+ "n_new_candidate": 11,
102
+ "n_confirmed_candidate": 4,
103
+ "sum_kwp_high": 1442.2,
104
+ "sum_kwp_all": 1442.2,
105
+ "area_km2": 90.27,
106
+ "high_per_km2": 0.1329
107
+ },
108
+ {
109
+ "name": "Silang",
110
+ "province": "Cavite",
111
+ "n_high": 11,
112
+ "n_candidate": 5,
113
+ "n_new_high": 9,
114
+ "n_confirmed_high": 2,
115
+ "n_new_candidate": 5,
116
+ "n_confirmed_candidate": 0,
117
+ "sum_kwp_high": 1275.4,
118
+ "sum_kwp_all": 1275.4,
119
+ "area_km2": 138.11,
120
+ "high_per_km2": 0.0796
121
+ },
122
+ {
123
+ "name": "Binan",
124
+ "province": "Laguna",
125
+ "n_high": 11,
126
+ "n_candidate": 14,
127
+ "n_new_high": 11,
128
+ "n_confirmed_high": 0,
129
+ "n_new_candidate": 13,
130
+ "n_confirmed_candidate": 1,
131
+ "sum_kwp_high": 2939.4,
132
+ "sum_kwp_all": 2939.4,
133
+ "area_km2": 63.42,
134
+ "high_per_km2": 0.1734
135
+ },
136
+ {
137
+ "name": "Santa Rosa",
138
+ "province": "Laguna",
139
+ "n_high": 10,
140
+ "n_candidate": 9,
141
+ "n_new_high": 9,
142
+ "n_confirmed_high": 1,
143
+ "n_new_candidate": 9,
144
+ "n_confirmed_candidate": 0,
145
+ "sum_kwp_high": 3350.2,
146
+ "sum_kwp_all": 3350.2,
147
+ "area_km2": 90.02,
148
+ "high_per_km2": 0.1111
149
+ },
150
+ {
151
+ "name": "Taguig",
152
+ "province": "Metro Manila",
153
+ "n_high": 8,
154
+ "n_candidate": 14,
155
+ "n_new_high": 6,
156
+ "n_confirmed_high": 2,
157
+ "n_new_candidate": 12,
158
+ "n_confirmed_candidate": 2,
159
+ "sum_kwp_high": 3231.7,
160
+ "sum_kwp_all": 3231.7,
161
+ "area_km2": 79.7,
162
+ "high_per_km2": 0.1004
163
+ },
164
+ {
165
+ "name": "Pasig",
166
+ "province": "Metro Manila",
167
+ "n_high": 8,
168
+ "n_candidate": 12,
169
+ "n_new_high": 7,
170
+ "n_confirmed_high": 1,
171
+ "n_new_candidate": 11,
172
+ "n_confirmed_candidate": 1,
173
+ "sum_kwp_high": 1394.0,
174
+ "sum_kwp_all": 1394.0,
175
+ "area_km2": 30.83,
176
+ "high_per_km2": 0.2595
177
+ },
178
+ {
179
+ "name": "Manila",
180
+ "province": "Metro Manila",
181
+ "n_high": 8,
182
+ "n_candidate": 5,
183
+ "n_new_high": 8,
184
+ "n_confirmed_high": 0,
185
+ "n_new_candidate": 5,
186
+ "n_confirmed_candidate": 0,
187
+ "sum_kwp_high": 4299.3,
188
+ "sum_kwp_all": 4299.3,
189
+ "area_km2": 179.7,
190
+ "high_per_km2": 0.0445
191
+ },
192
+ {
193
+ "name": "Carmona",
194
+ "province": "Cavite",
195
+ "n_high": 7,
196
+ "n_candidate": 5,
197
+ "n_new_high": 7,
198
+ "n_confirmed_high": 0,
199
+ "n_new_candidate": 5,
200
+ "n_confirmed_candidate": 0,
201
+ "sum_kwp_high": 2993.5,
202
+ "sum_kwp_all": 2993.5,
203
+ "area_km2": 29.8,
204
+ "high_per_km2": 0.2349
205
+ },
206
+ {
207
+ "name": "San Pedro",
208
+ "province": "Laguna",
209
+ "n_high": 7,
210
+ "n_candidate": 1,
211
+ "n_new_high": 4,
212
+ "n_confirmed_high": 3,
213
+ "n_new_candidate": 1,
214
+ "n_confirmed_candidate": 0,
215
+ "sum_kwp_high": 5576.8,
216
+ "sum_kwp_all": 5576.8,
217
+ "area_km2": 50.14,
218
+ "high_per_km2": 0.1396
219
+ },
220
+ {
221
+ "name": "Bacoor",
222
+ "province": "Cavite",
223
+ "n_high": 7,
224
+ "n_candidate": 2,
225
+ "n_new_high": 5,
226
+ "n_confirmed_high": 2,
227
+ "n_new_candidate": 1,
228
+ "n_confirmed_candidate": 1,
229
+ "sum_kwp_high": 3129.6,
230
+ "sum_kwp_all": 3129.6,
231
+ "area_km2": 57.36,
232
+ "high_per_km2": 0.122
233
+ },
234
+ {
235
+ "name": "Paranaque",
236
+ "province": "Metro Manila",
237
+ "n_high": 7,
238
+ "n_candidate": 11,
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583
+ }
584
+ ]
585
+ }
data/city_detection_counts_bacolod.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
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+ ]
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data/city_detection_counts_calabarzon.json ADDED
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1
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111
+ ]
112
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data/city_detection_counts_cdo.json ADDED
@@ -0,0 +1,27 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
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+ ]
27
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data/city_detection_counts_cebu.json ADDED
@@ -0,0 +1,49 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
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+ ]
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+ }
data/city_detection_counts_davao.json ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
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data/city_detection_counts_iloilo.json ADDED
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+ {
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+ ]
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data/city_detection_counts_legazpi.json ADDED
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+ {
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data/city_solar_saturation.json ADDED
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+ "city": "General Mariano Alvarez",
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data/per_building_solar_ncr.geojson ADDED
The diff for this file is too large to render. See raw diff
 
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data/rooftop_solar_calabarzon.geojson ADDED
The diff for this file is too large to render. See raw diff
 
data/rooftop_solar_cdo.geojson ADDED
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data/rooftop_solar_cebu.geojson ADDED
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data/rooftop_solar_davao.geojson ADDED
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data/rooftop_solar_iloilo.geojson ADDED
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data/rooftop_solar_legazpi.geojson ADDED
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data/rooftop_solar_ncr.geojson ADDED
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data/solar_map_ph_2026Q2.geojson ADDED
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data/solar_map_ph_summary_2026Q2.json ADDED
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+ {
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+ "quarter": "2026Q2",
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+ "baseline_year": "2022",
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+ "generated_utc": "2026-05-08T03:54:10.109147+00:00",
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+ "city_count": 61,
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+ "city_count_with_signal": 61,
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+ "composite_score_franchise_mean": -6.768265365286558e-17,
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+ "composite_score_max": 1.2293228816011457,
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+ "composite_score_min": -1.0308550505242573,
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+ "top5_strongest_signal": [
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+ {
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+ "name": "Valenzuela",
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+ "composite": 1.2293228816011457
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+ },
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+ {
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+ "name": "Malabon",
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+ "composite": 0.9129564385983094
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+ },
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+ {
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+ "name": "Baras",
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+ "composite": 0.7151436581083926
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+ },
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+ {
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+ "name": "Antipolo",
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+ "composite": 0.7109068486323796
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+ },
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+ {
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+ "name": "Teresa",
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+ "composite": 0.7057224020381178
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+ }
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+ ],
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+ "weights": {
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+ "nir": 0.4,
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+ "lst": 0.2,
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+ "nightlight": 0.1
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+ },
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+ "meralco_aggregates": {
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+ "registered_installations": 20000,
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+ "registered_capacity_mw_aggregate": 170,
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+ "icsc_unregistered_estimate_fraction": 0.33,
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+ "as_of": "2026-05-03"
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+ }
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+ }
data/solar_saturation_ncr.geojson ADDED
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