Add the solar farm database read by the model scripts

.gitattributes

@@ -207,3 +207,4 @@ results/optimization_2/Optimization_2_Results_R1/flight_results_1.0farm_0.7fligh
 results/optimization_2/Optimization_2_Results_R1/flight_results_1.0farm_0.8flight.csv filter=lfs diff=lfs merge=lfs -text
 results/optimization_2/Optimization_2_Results_R1/flight_results_1.0farm_0.9flight.csv filter=lfs diff=lfs merge=lfs -text
 results/optimization_2/Optimization_2_Results_R1/flight_results_1.0farm_1.0flight.csv filter=lfs diff=lfs merge=lfs -text
+data/solar_farms/uspvdb_v3_0_20250430.geojson filter=lfs diff=lfs merge=lfs -text

README.md

@@ -25,7 +25,7 @@ python download_data.py      # run inside the cloned code repository
 
 `data/`, `results/` and `figures/` then sit next to `code/`, where every script looks for them.
 
-## Contents (2.2 GB)
+## Contents (4.0 GB)
 
 ### `data/` — inputs
 
@@ -37,7 +37,7 @@ python download_data.py      # run inside the cloned code repository
 | `flights/processed/flights_reference_week.parquet` (and `.csv`) | 7–13 April 2025 (Central Time), 149,739 records | `4_reference_week.py` |
 | `flights/processed/flights_reference_week_matched.parquet` | flights whose origin and destination are in the airport file: the 148,814 flights analysed | `5_match_airports.py` |
 | `airports/airport_data.geojson` | USA Airports | Esri, ArcGIS |
-| `farms/uspvdbGeoJSON.zip` | United States Large-Scale Solar Photovoltaic Database | Lawrence Berkeley National Laboratory, U.S. Geological Survey |
+| `solar_farms/uspvdb_v3_0_20250430.geojson` | United States Large-Scale Solar Photovoltaic Database | Lawrence Berkeley National Laboratory, U.S. Geological Survey |
 | `US_boundaries/` | state (1:20M) and county (1:500k) cartographic boundaries, 2023 | U.S. Census Bureau |
 
 ### `results/` — model outputs

data/{farms/uspvdbGeoJSON.zip → solar_farms/uspvdb_v3_0_20250430.geojson}

@@ -1,3 +1,3 @@
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