3.4M Solar Panels
In October, I reviewed the Ground-Mounted Solar Energy in the United States (GM-SEUS) dataset. This dataset attempted to outline the majority of solar farm arrays and panels across the US. Version 1 of this dataset contained 2.9M panels.
On Monday, version 2 of this dataset was released and now contains more than 3.4M panels. In addition to the panels and arrays being refreshed, there is a new rooftop array dataset.
In this post, I'll review v2 of the GM-SEUS dataset.
My Workstation
I'm using a 5.7 GHz AMD Ryzen 9 9950X CPU. It has 16 cores and 32 threads and 1.2 MB of L1, 16 MB of L2 and 64 MB of L3 cache. It has a liquid cooler attached and is housed in a spacious, full-sized Cooler Master HAF 700 computer case.
The system has 96 GB of DDR5 RAM clocked at 4,800 MT/s and a 5th-generation, Crucial T700 4 TB NVMe M.2 SSD which can read at speeds up to 12,400 MB/s. There is a heatsink on the SSD to help keep its temperature down. This is my system's C drive.
The system is powered by a 1,200-watt, fully modular Corsair Power Supply and is sat on an ASRock X870E Nova 90 Motherboard.
I'm running Ubuntu 24 LTS via Microsoft's Ubuntu for Windows on Windows 11 Pro. In case you're wondering why I don't run a Linux-based desktop as my primary work environment, I'm still using an Nvidia GTX 1080 GPU which has better driver support on Windows and ArcGIS Pro only supports Windows natively.
Installing Prerequisites
I'll use GDAL 3.9.3 to help analyse the data in this post.
$sudoadd-apt-repositoryppa:ubuntugis/ubuntugis-unstable
$sudoaptupdate
$sudoaptinstall\
gdal-bin
I'll use DuckDB, along with its H3, JSON, Lindel, Parquet and Spatial extensions in this post.
$cd~
$wget-chttps://github.com/duckdb/duckdb/releases/download/v1.5.1/duckdb_cli-linux-amd64.zip
$unzip-jduckdb_cli-linux-amd64.zip
$chmod+xduckdb
$~/duckdb
INSTALLh3FROMcommunity;
INSTALLlindelFROMcommunity;
INSTALLjson;
INSTALLparquet;
INSTALLspatial;
I'll set up DuckDB to load every installed extension each time it launches.
$vi~/.duckdbrc
.timer on
.width 180
LOAD h3;
LOAD lindel;
LOAD json;
LOAD parquet;
LOAD spatial;
The maps in this post were rendered with QGIS version 4.0.1. QGIS is a desktop application that runs on Windows, macOS and Linux. The application has grown in popularity in recent years and has ~15M application launches from users all around the world each month.
I used QGIS' HCMGIS plugin to add basemaps from Esri to this post.
Analysis-Ready Datasets
The following will download a 3.4 GB ZIP file. I'll extract any GeoPackage (GPKG) file from it.
$wget-OGMSEUS_v2.zip\
'https://zenodo.org/records/19581821/files/GMSEUS.zip?download=1'
$unzip-jGMSEUS_v2.zip"*.gpkg"
The following is the projection used by the GPKG files in this dataset.
$gdalsrsinfo\
-oproj4\
GMSEUS_RooftopArrays_2025_v2_0.gpkg
+proj=aea +lat_0=23 +lon_0=-96 +lat_1=29.5 +lat_2=45.5 +x_0=0 +y_0=0 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs
The following will convert the rooftop arrays into Parquet. I needed to use DuckDB v1.4.4 for the following as v1.5.1 was raising exceptions.
$~/duckdb
COPY(
WITHaAS(
SELECTSource,
grndCvr,
modType,
mount,
nativeID,
roofArrID,
area:IF(area::TEXT='-9999.0',NULL,area::DOUBLE),
azimuth:IF(azimuth::TEXT='-9999.0',NULL,azimuth::DOUBLE),
capMWAC:IF(capMWAC::TEXT='-9999.0',NULL,capMWAC::DOUBLE),
capMWDC:IF(capMWDC::TEXT='-9999.0',NULL,capMWDC::DOUBLE),
tilt:IF(tilt::TEXT='-9999.0',NULL,tilt::DOUBLE),
instYr:CASEWHENinstYr::INT=-9999THENNULLELSEinstYrEND,
ST_FLIPCOORDINATES(
ST_TRANSFORM(
geom,
'+proj=aea +lat_0=23 +lon_0=-96 +lat_1=29.5 +lat_2=45.5 +x_0=0 +y_0=0 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs',
'EPSG:4326'))geometry
FROMST_READ('GMSEUS_RooftopArrays_2025_v2_0.gpkg')
)
SELECT*EXCLUDE(geometry),
{'xmin':ST_XMIN(ST_EXTENT(geometry)),
'ymin':ST_YMIN(ST_EXTENT(geometry)),
'xmax':ST_XMAX(ST_EXTENT(geometry)),
'ymax':ST_YMAX(ST_EXTENT(geometry))}ASbbox,
ST_ASWKB(geometry)geometry
FROMa
ORDERBYHILBERT_ENCODE([ST_Y(ST_CENTROID(geometry)),
ST_X(ST_CENTROID(geometry))]::double[2])
)TO'GMSEUS_RooftopArrays_2025_v2_0.parquet'(
FORMAT'PARQUET',
CODEC'ZSTD',
COMPRESSION_LEVEL22,
ROW_GROUP_SIZE15000);
There are 5,822 records in this dataset.
SELECTCOUNT(*)
FROM'GMSEUS_RooftopArrays_2025_v2_0.parquet';
5,822
Below is a breakdown of unique values and NULL coverage across each column.
SELECTcolumn_name,
column_type,
null_percentage,
approx_unique,
min,
max
FROM(SUMMARIZE
FROMREAD_PARQUET('GMSEUS_RooftopArrays_2025_v2_0.parquet'))
WHEREcolumn_name!='geometry'
ANDcolumn_name!='bbox'
ORDERBYLOWER(column_name);
┌─────────────┬─────────────┬─────────────────┬───────────────┬────────────┬────────────────────┐
│ column_name │ column_type │ null_percentage │ approx_unique │ min │ max │
│ varchar │ varchar │ decimal(9,2) │ int64 │ varchar │ varchar │
├─────────────┼─────────────┼─────────────────┼───────────────┼────────────┼────────────────────┤
│ area │ DOUBLE │ 2.77 │ 5180 │ 15.0 │ 487111.0 │
│ azimuth │ DOUBLE │ 89.63 │ 156 │ 0.0 │ 530.02323408881 │
│ capMWAC │ DOUBLE │ 89.52 │ 60 │ 0.2 │ 74.9 │
│ capMWDC │ DOUBLE │ 87.12 │ 166 │ 0.00448 │ 99.7 │
│ grndCvr │ VARCHAR │ 97.61 │ 2 │ impervious │ vegetation │
│ instYr │ BIGINT │ 72.43 │ 23 │ 2003 │ 2025 │
│ modType │ VARCHAR │ 0.00 │ 2 │ c-si │ thin-film │
│ mount │ VARCHAR │ 87.53 │ 5 │ dual_axis │ unknown │
│ nativeID │ VARCHAR │ 0.00 │ 4540 │ 1 │ Xebec 1 solar farm │
│ roofArrID │ BIGINT │ 0.00 │ 5830 │ 1 │ 5822 │
│ Source │ VARCHAR │ 0.00 │ 15 │ CCVPV │ gspt │
│ tilt │ DOUBLE │ 90.64 │ 31 │ 0.0 │ 52.0 │
├─────────────┴─────────────┴─────────────────┴───────────────┴────────────┴────────────────────┤
│ 12 rows 6 columns │
└───────────────────────────────────────────────────────────────────────────────────────────────┘
The following will convert the panels into Parquet.
COPY(
WITHaAS(
SELECTSource,
arrayID:arrayID::INT,
panelID:panelID::INT,
pnlSource,
rowArea,
rowAzimuth,
rowLength,
rowMount,
rowSpace:IF(rowSpace::TEXT='-9999.0',NULL,rowSpace::DOUBLE),
rowWidth,
ST_FLIPCOORDINATES(
ST_TRANSFORM(
geom,
'+proj=aea +lat_0=23 +lon_0=-96 +lat_1=29.5 +lat_2=45.5 +x_0=0 +y_0=0 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs',
'EPSG:4326'))geometry
FROMST_READ('GMSEUS_Panels_Final_2025_v2_0.gpkg')
)
SELECT*EXCLUDE(geometry),
{'xmin':ST_XMIN(ST_EXTENT(geometry)),
'ymin':ST_YMIN(ST_EXTENT(geometry)),
'xmax':ST_XMAX(ST_EXTENT(geometry)),
'ymax':ST_YMAX(ST_EXTENT(geometry))}ASbbox,
ST_ASWKB(geometry)geometry
FROMa
ORDERBYHILBERT_ENCODE([ST_Y(ST_CENTROID(geometry)),
ST_X(ST_CENTROID(geometry))]::double[2])
)TO'GMSEUS_Panels_Final_2025_v2_0.parquet'(
FORMAT'PARQUET',
CODEC'ZSTD',
COMPRESSION_LEVEL22,
ROW_GROUP_SIZE15000);
There are 3,429,157 records in this dataset.
SELECTCOUNT(*)
FROM'GMSEUS_Panels_Final_2025_v2_0.parquet';
3,429,157
Below is a breakdown of unique values and NULL coverage across each column.
SELECTcolumn_name,
column_type,
null_percentage,
approx_unique,
min,
max
FROM(SUMMARIZE
FROMREAD_PARQUET('GMSEUS_Panels_Final_2025_v2_0.parquet'))
WHEREcolumn_name!='geometry'
ANDcolumn_name!='bbox'
ORDERBYLOWER(column_name);
┌─────────────┬─────────────┬─────────────────┬───────────────┬───────────┬─────────────┐
│ column_name │ column_type │ null_percentage │ approx_unique │ min │ max │
│ varchar │ varchar │ decimal(9,2) │ int64 │ varchar │ varchar │
├─────────────┼─────────────┼─────────────────┼───────────────┼───────────┼─────────────┤
│ arrayID │ INTEGER │ 0.03 │ 12653 │ 1 │ 18980 │
│ panelID │ INTEGER │ 0.00 │ 3323765 │ 1 │ 3429157 │
│ pnlSource │ VARCHAR │ 0.00 │ 5 │ CCVPV │ OSM │
│ rowArea │ DOUBLE │ 0.00 │ 100105 │ 15.01 │ 9982.68 │
│ rowAzimuth │ DOUBLE │ 0.00 │ 22029 │ 90.0 │ 540.0 │
│ rowLength │ DOUBLE │ 0.00 │ 25531 │ 3.96 │ 737.38 │
│ rowMount │ VARCHAR │ 0.00 │ 3 │ dual_axis │ single_axis │
│ rowSpace │ DOUBLE │ 1.27 │ 1836 │ 0.01 │ 20.0 │
│ rowWidth │ DOUBLE │ 0.00 │ 2258 │ 0.45 │ 135.33 │
│ Source │ VARCHAR │ 0.00 │ 12 │ CCVPV │ USPVDB │
├─────────────┴─────────────┴─────────────────┴───────────────┴───────────┴─────────────┤
│ 10 rows 6 columns │
└───────────────────────────────────────────────────────────────────────────────────────┘
The following will convert the arrays and panels datasets into Parquet.
COPY(
WITHaAS(
SELECTCOUNTYFP,
GCR1,
GCR2,
STATEFP,
Source,
arrayID,
avgAzimuth:IF(avgAzimuth::TEXT='-9999.0',NULL,avgAzimuth::DOUBLE),
avgLength:IF(avgLength::TEXT='-9999.0',NULL,avgLength::DOUBLE),
avgSpace:IF(avgSpace::TEXT='-9999.0',NULL,avgSpace::DOUBLE),
avgWidth:IF(avgWidth::TEXT='-9999.0',NULL,avgWidth::DOUBLE),
capMWAC,
capMWACest,
capMWDC,
capMWDCest,
effInit:IF(effInit::TEXT='-9999.0',NULL,effInit::DOUBLE),
grndCvr,
instYr:CASEWHENinstYr::INT=-9999THENNULLELSEinstYrEND,
instYrEst:CASEWHENinstYrEst::INT=-9999THENNULLELSEinstYrEstEND,
modType,
mount,
nativeID:IF(nativeID::TEXT='unknown',NULL,nativeID),
newBound,
numRow,
tilt:IF(tilt::TEXT='-9999.0',NULL,tilt::DOUBLE),
tiltEst:CASEWHENtiltEst::INT=-9999THENNULLELSEtiltEstEND,
totArea,
totRowArea,
ST_FLIPCOORDINATES(
ST_TRANSFORM(
geom,
'+proj=aea +lat_0=23 +lon_0=-96 +lat_1=29.5 +lat_2=45.5 +x_0=0 +y_0=0 +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +units=m +no_defs',
'EPSG:4326'))geometry
FROMST_READ('GMSEUS_Arrays_Final_2025_v2_0.gpkg')
)
SELECT*EXCLUDE(geometry),
{'xmin':ST_XMIN(ST_EXTENT(geometry)),
'ymin':ST_YMIN(ST_EXTENT(geometry)),
'xmax':ST_XMAX(ST_EXTENT(geometry)),
'ymax':ST_YMAX(ST_EXTENT(geometry))}ASbbox,
ST_ASWKB(geometry)geometry
FROMa
ORDERBYHILBERT_ENCODE([ST_Y(ST_CENTROID(geometry)),
ST_X(ST_CENTROID(geometry))]::double[2])
)TO'GMSEUS_Arrays_Final_2025_v2_0.parquet'(
FORMAT'PARQUET',
CODEC'ZSTD',
COMPRESSION_LEVEL22,
ROW_GROUP_SIZE15000);
There are 18,980 records in this dataset.
SELECTCOUNT(*)
FROM'GMSEUS_Arrays_Final_2025_v2_0.parquet';
18,980
Below is a breakdown of unique values and NULL coverage across each column.
SELECTcolumn_name,
column_type,
null_percentage,
approx_unique,
min,
max
FROM(SUMMARIZE
FROMREAD_PARQUET('GMSEUS_Arrays_Final_2025_v2_0.parquet'))
WHEREcolumn_name!='geometry'
ANDcolumn_name!='bbox'
ORDERBYLOWER(column_name);
┌─────────────┬─────────────┬─────────────────┬───────────────┬────────────┬────────────┐
│ column_name │ column_type │ null_percentage │ approx_unique │ min │ max │
│ varchar │ varchar │ decimal(9,2) │ int64 │ varchar │ varchar │
├─────────────┼─────────────┼─────────────────┼───────────────┼────────────┼────────────┤
│ arrayID │ BIGINT │ 0.00 │ 16914 │ 1 │ 18980 │
│ avgAzimuth │ DOUBLE │ 32.88 │ 5865 │ 90.22 │ 540.0 │
│ avgLength │ DOUBLE │ 32.88 │ 12674 │ 4.02 │ 360.128 │
│ avgSpace │ DOUBLE │ 32.88 │ 7965 │ 0.024 │ 20.0 │
│ avgWidth │ DOUBLE │ 32.88 │ 6528 │ 0.863 │ 83.13 │
│ capMWAC │ DOUBLE │ 0.00 │ 4182 │ 0.003 │ 1128.931 │
│ capMWACest │ DOUBLE │ 0.00 │ 6620 │ 0.003 │ 1352.693 │
│ capMWDC │ DOUBLE │ 0.00 │ 7203 │ 0.003 │ 1467.61 │
│ capMWDCest │ DOUBLE │ 0.00 │ 8883 │ 0.004 │ 1758.501 │
│ COUNTYFP │ VARCHAR │ 0.00 │ 237 │ 001 │ 840 │
│ effInit │ DOUBLE │ 0.07 │ 12 │ 0.09 │ 0.21 │
│ GCR1 │ DOUBLE │ 0.00 │ 5096 │ 0.1 │ 1.0 │
│ GCR2 │ DOUBLE │ 0.00 │ 5913 │ 0.0943 │ 0.9883 │
│ grndCvr │ VARCHAR │ 0.00 │ 3 │ impervious │ vegetation │
│ instYr │ BIGINT │ 0.00 │ 26 │ 1985 │ 2025 │
│ instYrEst │ BIGINT │ 0.32 │ 23 │ 2003 │ 2025 │
│ modType │ VARCHAR │ 0.00 │ 3 │ c-si │ thin-film │
│ mount │ VARCHAR │ 0.00 │ 9 │ dual_axis │ unknown │
│ nativeID │ VARCHAR │ 0.23 │ 14342 │ 1 │ York Solar │
│ newBound │ BIGINT │ 0.00 │ 2 │ 0 │ 1 │
│ numRow │ INTEGER │ 0.00 │ 1177 │ 0 │ 90145 │
│ Source │ VARCHAR │ 0.00 │ 10 │ CCVPV │ USPVDB │
│ STATEFP │ VARCHAR │ 0.00 │ 49 │ 01 │ 56 │
│ tilt │ DOUBLE │ 46.39 │ 63 │ 0.0 │ 90.0 │
│ tiltEst │ BIGINT │ 46.39 │ 30 │ 10 │ 43 │
│ totArea │ INTEGER │ 0.00 │ 14669 │ 30 │ 19603313 │
│ totRowArea │ INTEGER │ 0.00 │ 13415 │ 30 │ 8537538 │
├─────────────┴─────────────┴─────────────────┴───────────────┴────────────┴────────────┤
│ 27 rows 6 columns │
└───────────────────────────────────────────────────────────────────────────────────────┘
Rooftop Solar Arrays
Below is a heatmap of the rooftop solar arrays dataset.
CREATEORREPLACETABLEh3_4_statsAS
SELECTh3_4:H3_LATLNG_TO_CELL(
bbox.ymin,
bbox.xmin,
4),
COUNT(*)num_recs
FROM'GMSEUS_RooftopArrays_2025_v2_0.parquet'
GROUPBY1;
COPY(
SELECTgeometry:ST_ASWKB(H3_CELL_TO_BOUNDARY_WKT(h3_4)::geometry),
num_recs
FROMh3_4_stats
)TO'GMSEUS_RooftopArrays_2025_v2_0.h3_4.parquet'(
FORMAT'PARQUET',
CODEC'ZSTD',
COMPRESSION_LEVEL22,
ROW_GROUP_SIZE15000);
These are the source counts for this dataset.
SELECTCOUNT(*),
Source
FROM'GMSEUS_RooftopArrays_2025_v2_0.parquet'
GROUPBY2
ORDERBY1DESC;
┌──────────────┬────────────────────────────┐
│ count_star() │ Source │
│ int64 │ varchar │
├──────────────┼────────────────────────────┤
│ 2175 │ OSM │
│ 1835 │ CECSFC │
│ 1024 │ TZSAM │
│ 485 │ USPVDB │
│ 93 │ GRW │
│ 54 │ GMSEUSdigArraysPanels_v2_0 │
│ 46 │ gspt │
│ 43 │ SAM │
│ 24 │ GMSEUSgeoref_v2_0 │
│ 16 │ CCVPV │
│ 15 │ GPPDB │
│ 10 │ CWSD │
│ 2 │ InSPIRE │
├──────────────┴────────────────────────────┤
│ 13 rows 2 columns │
└───────────────────────────────────────────┘
Below are the most-represented source per hexagon.
CREATEORREPLACETABLEh3_3sAS
WITHbAS(
WITHaAS(
SELECTh3_3:H3_LATLNG_TO_CELL(
bbox.ymin,
bbox.xmin,
3),
Source,
num_recs:COUNT(*)
FROM'GMSEUS_RooftopArrays_2025_v2_0.parquet'
GROUPBY1,2
)
SELECT*,
ROW_NUMBER()OVER(PARTITIONBYh3_3
ORDERBYnum_recsDESC)ASrn
FROMa
)
FROMb
WHERErn=1
ORDERBYnum_recsDESC;
COPY(
SELECTgeom:H3_CELL_TO_BOUNDARY_WKT(h3_3)::GEOMETRY,
Source
FROMh3_3s
)TO'GMSEUS_RooftopArrays_2025_v2_0.Source.h3_3.parquet'(
FORMAT'PARQUET',
CODEC'ZSTD',
COMPRESSION_LEVEL22,
ROW_GROUP_SIZE15000);
This is the breakdown of mount and mod types.
WITHaAS(
SELECTmodType,
mount,
cnt:COUNT(*)
FROM'GMSEUS_RooftopArrays_2025_v2_0.parquet'
GROUPBY1,2
)
PIVOTa
ONmodType
USINGSUM(cnt)
GROUPBYmount
ORDERBYmount;
┌─────────────┬────────┬───────────┐
│ mount │ c-si │ thin-film │
│ varchar │ int128 │ int128 │
├─────────────┼────────┼───────────┤
│ dual_axis │ 33 │ NULL │
│ fixed_axis │ 381 │ 2 │
│ mixed │ 2 │ NULL │
│ single_axis │ 210 │ NULL │
│ unknown │ 98 │ NULL │
│ NULL │ 5096 │ NULL │
└─────────────┴────────┴───────────┘
These are the area stats broken down by year of installation.
SELECTinstYr,
count:COUNT(*),
avg:AVG(area)::INT,
mean:MEAN(area)::INT,
max:MAX(area)::INT
FROM'GMSEUS_RooftopArrays_2025_v2_0.parquet'
WHEREinstYrISNOTNULL
GROUPBY1
ORDERBY1;
┌────────┬───────┬───────┬───────┬────────┐
│ instYr │ count │ avg │ mean │ max │
│ int64 │ int64 │ int32 │ int32 │ int32 │
├────────┼───────┼───────┼───────┼────────┤
│ 2003 │ 23 │ 2630 │ 2630 │ 18124 │
│ 2005 │ 1 │ 20342 │ 20342 │ 20342 │
│ 2006 │ 1 │ 37587 │ 37587 │ 37587 │
│ 2007 │ 6 │ 16848 │ 16848 │ 27067 │
│ 2008 │ 4 │ 24989 │ 24989 │ 30107 │
│ 2009 │ 11 │ 7877 │ 7877 │ 30229 │
│ 2010 │ 24 │ 15834 │ 15834 │ 43854 │
│ 2011 │ 46 │ 41511 │ 41511 │ 487111 │
│ 2012 │ 54 │ 13371 │ 13371 │ 38923 │
│ 2013 │ 47 │ 14476 │ 14476 │ 151620 │
│ 2014 │ 24 │ 29289 │ 29289 │ 65995 │
│ 2015 │ 37 │ 34130 │ 34130 │ 218080 │
│ 2016 │ 47 │ 21094 │ 21094 │ 46138 │
│ 2017 │ 105 │ 20882 │ 20882 │ 315564 │
│ 2018 │ 225 │ 13584 │ 13584 │ 152636 │
│ 2019 │ 102 │ 21613 │ 21613 │ 111497 │
│ 2020 │ 143 │ 16052 │ 16052 │ 70018 │
│ 2021 │ 120 │ 16169 │ 16169 │ 101955 │
│ 2022 │ 141 │ 17343 │ 17343 │ 185698 │
│ 2023 │ 164 │ 18865 │ 18865 │ 137787 │
│ 2024 │ 132 │ 14743 │ 14743 │ 63190 │
│ 2025 │ 148 │ 12363 │ 12363 │ 135270 │
├────────┴───────┴───────┴───────┴────────┤
│ 22 rows 5 columns │
└─────────────────────────────────────────┘
Rooftop Arrays Footprints
The map below shows Los Angeles to Long Beach. The detections are coloured by their source.
Some sources conservatively outline the building footprint.
Other sources have more organic shapes.
The "gspt" source uses vague circles for its detections. Below, there are four warehouses with roof panels but only two large circles are shown for their detections.
There are plenty of rooftop arrays that weren't detected all over LA. Given that this dataset only contains ~5K records, its coverage leaves a fair amount of room for improvement.
Arrays & Panels
Below is a heatmap of the arrays dataset.
CREATEORREPLACETABLEh3_4_statsAS
SELECTh3_4:H3_LATLNG_TO_CELL(
bbox.ymin,
bbox.xmin,
4),
COUNT(*)num_recs
FROM'GMSEUS_Arrays_Final_2025_v2_0.parquet'
GROUPBY1;
COPY(
SELECTgeometry:ST_ASWKB(H3_CELL_TO_BOUNDARY_WKT(h3_4)::geometry),
num_recs
FROMh3_4_stats
)TO'GMSEUS_Arrays_Final_2025_v2_0.h3_4.parquet'(
FORMAT'PARQUET',
CODEC'ZSTD',
COMPRESSION_LEVEL22,
ROW_GROUP_SIZE15000);
These are the record counts for each source.
SELECTCOUNT(*),
Source
FROM'GMSEUS_Arrays_Final_2025_v2_0.parquet'
GROUPBY2
ORDERBY1DESC;
┌──────────────┬────────────────────────────┐
│ count_star() │ Source │
│ int64 │ varchar │
├──────────────┼────────────────────────────┤
│ 5222 │ OSM │
│ 4024 │ USPVDB │
│ 3278 │ TZSAM │
│ 2288 │ CECSFC │
│ 1697 │ GMSEUSgeoref_v2_0 │
│ 1291 │ GMSEUSdigArraysPanels_v2_0 │
│ 957 │ GRW │
│ 155 │ CCVPV │
│ 68 │ CWSD │
└──────────────┴────────────────────────────┘
Below are the most-represented source per hexagon.
CREATEORREPLACETABLEh3_3sAS
WITHbAS(
WITHaAS(
SELECTh3_3:H3_LATLNG_TO_CELL(
bbox.ymin,
bbox.xmin,
3),
Source,
num_recs:COUNT(*)
FROM'GMSEUS_Arrays_Final_2025_v2_0.parquet'
GROUPBY1,2
)
SELECT*,
ROW_NUMBER()OVER(PARTITIONBYh3_3
ORDERBYnum_recsDESC)ASrn
FROMa
)
FROMb
WHERErn=1
ORDERBYnum_recsDESC;
COPY(
SELECTgeom:H3_CELL_TO_BOUNDARY_WKT(h3_3)::GEOMETRY,
Source
FROMh3_3s
)TO'GMSEUS_Arrays_Final_2025_v2_0.Source.h3_3.parquet'(
FORMAT'PARQUET',
CODEC'ZSTD',
COMPRESSION_LEVEL22,
ROW_GROUP_SIZE15000);
Solar Farms in close proximity can have different sources attributed to their detection.
Not all solar farms are picked up within the arrays dataset. There are also array datasets that haven't marked out the panels themselves. The following is an example from 34.837N, -118.355E. The panels are coloured purple.
These are the array capacity stats broken down by year of installation.
SELECTinstYr,
count:COUNT(*),
ACavg:AVG(capMWAC)::INT,
DCavg:AVG(capMWDC)::INT,
ACmean:MEAN(capMWAC)::INT,
DCmean:MEAN(capMWDC)::INT,
ACmax:MAX(capMWAC)::INT,
DCmax:MAX(capMWDC)::INT
FROM'GMSEUS_Arrays_Final_2025_v2_0.parquet'
WHEREinstYrISNOTNULL
GROUPBY1
ORDERBY1;
┌────────┬───────┬───────┬───────┬────────┬────────┬───────┬───────┐
│ instYr │ count │ ACavg │ DCavg │ ACmean │ DCmean │ ACmax │ DCmax │
│ int64 │ int64 │ int32 │ int32 │ int32 │ int32 │ int32 │ int32 │
├────────┼───────┼───────┼───────┼────────┼────────┼───────┼───────┤
│ 1985 │ 1 │ 14 │ 17 │ 14 │ 17 │ 14 │ 17 │
│ 1990 │ 2 │ 88 │ 90 │ 88 │ 90 │ 92 │ 92 │
│ 2002 │ 1 │ 3 │ 3 │ 3 │ 3 │ 3 │ 3 │
│ 2003 │ 7 │ 2 │ 2 │ 2 │ 2 │ 2 │ 3 │
│ 2005 │ 4 │ 0 │ 0 │ 0 │ 0 │ 0 │ 1 │
│ 2006 │ 64 │ 3 │ 4 │ 3 │ 4 │ 100 │ 125 │
│ 2007 │ 101 │ 2 │ 3 │ 2 │ 3 │ 68 │ 68 │
│ 2008 │ 195 │ 2 │ 3 │ 2 │ 3 │ 226 │ 294 │
│ 2009 │ 268 │ 2 │ 2 │ 2 │ 2 │ 150 │ 195 │
│ 2010 │ 401 │ 2 │ 2 │ 2 │ 2 │ 150 │ 195 │
│ 2011 │ 544 │ 3 │ 3 │ 3 │ 3 │ 175 │ 225 │
│ 2012 │ 777 │ 3 │ 3 │ 3 │ 3 │ 331 │ 430 │
│ 2013 │ 793 │ 4 │ 5 │ 4 │ 5 │ 280 │ 313 │
│ 2014 │ 913 │ 6 │ 7 │ 6 │ 7 │ 586 │ 752 │
│ 2015 │ 910 │ 5 │ 7 │ 5 │ 7 │ 314 │ 398 │
│ 2016 │ 1096 │ 9 │ 12 │ 9 │ 12 │ 300 │ 350 │
│ 2017 │ 1765 │ 5 │ 6 │ 5 │ 6 │ 350 │ 455 │
│ 2018 │ 1941 │ 5 │ 6 │ 5 │ 6 │ 352 │ 458 │
│ 2019 │ 1531 │ 6 │ 8 │ 6 │ 8 │ 300 │ 390 │
│ 2020 │ 1673 │ 11 │ 15 │ 11 │ 15 │ 638 │ 829 │
│ 2021 │ 1705 │ 19 │ 24 │ 19 │ 24 │ 504 │ 656 │
│ 2022 │ 1389 │ 16 │ 21 │ 16 │ 21 │ 868 │ 1128 │
│ 2023 │ 2017 │ 34 │ 44 │ 34 │ 44 │ 1095 │ 1423 │
│ 2024 │ 730 │ 37 │ 44 │ 37 │ 44 │ 868 │ 1128 │
│ 2025 │ 152 │ 18 │ 23 │ 18 │ 23 │ 1129 │ 1468 │
├────────┴───────┴───────┴───────┴────────┴────────┴───────┴───────┤
│ 25 rows 8 columns │
└──────────────────────────────────────────────────────────────────┘
Source: hackernews