PV Rooftop Database
Overview
The National Renewable Energy Laboratory’s (NREL) PV Rooftop Database (PVRDB) is a lidar-derived, geospatially-resolved dataset of suitable roof surfaces and their PV technical potential for 128 metropolitan regions in the United States. The source lidar data and building footprints were obtained by the U.S. Department of Homeland Security Homeland Security Infrastructure Program for 2006-2014. Using GIS methods, NREL identified suitable roof surfaces based on their size, orientation, and shading parameters Gagnon et al. (2016). Standard 2015 technical potential was then estimated for each plane using NREL’s System Advisory Model.
The PVRDB is down-loadable by city and year of lidar collection. Four geospatial layers are available for each city and year: 1) the raster extent of the lidar collection, 2) buildings identified from the lidar data, 3) suitable developable planes for each building, and 4) aspect values of the developable planes.
Storage Resources
The pv-rooftop Dataset is made available in Parquet format in the following container:
https://nrel.blob.core.windows.net/oedi
Data
The data are located in the pv-rooftops/ directory. The four main datasets are stored in the following subdirectories:
Main datasets
/aspects/buildings/developable_planes/rasd
Each partition is stored in an individual folder within each subdirectory.
Partitions
/city_year=<city>_<state>_<year>
e.g. /city_year=dover_de_09
Data Format
The PV Rooftops dataset is provided in geoparquet format partitioned by city_year. There are 4 core datasets:
oedi/pv-rooftop/aspects
field | data_type | description
– | – | –
gid | bigint |
city | string | city of source lidar dataset
state | string | state of source lidar dataset
year | bigint | year of source lidar dataset
bldg_fid | bigint | building id
aspect | bigint | aspect value
the_geom_96703 | string | projected geometry (US Contiguous Albers Equal Area Conic - SRID 6703)
the_geom_4326 | string | geometry (WGS 1984 - SRID 4326)
region_id | bigint |
oedi/pv-rooftop/buildings
| field | data_type | description |
|---|---|---|
gid |
bigint | |
bldg_fid |
bigint | the building fid |
the_geom_96703 |
string | projected geometry (US Contiguous Albers Equal Area Conic - SRID 6703) |
the_geom_4326 |
string | geometry (WGS 1984 - SRID 4326) |
city |
string | the city of the source lidar data |
state |
string | the state of the source lidar data |
year |
bigint | the year of the source lidar data |
region_id |
bigint |
oedi/pv-rooftop/developable_planes
| field | data_type | description |
|---|---|---|
bldg_fid |
bigint | building ID associated with the developable plane |
footprint_m2 |
double | developable plane footprint area (m2) |
slope |
bigint | slope value |
flatarea_m2 |
double | flat area of the developable plane (m2) |
slopeconversion |
double | the slope conversion factor used to convert the flat area into the sloped area |
slopearea_m2 |
double | sloped area of the developable plane (m2) |
zip |
string | zipcode |
zip_perc |
double | |
aspect |
bigint | the aspect value of the developable plane |
gid |
bigint | unique developable plane ID |
city |
string | the city of the source lidar data |
state |
string | the state of the source lidar data |
year |
bigint | the year of the source lidar data |
region_id |
bigint | |
the_geom_96703 |
string | projected geometry (US Contiguous Albers Equal Area Conic - SRID 6703) |
the_geom_4326 |
string | geometry (WGS 1984 - SRID 4326) |
oedi/pv-rooftop/rasd
| field | data_type | description |
|---|---|---|
gid |
bigint | the unique geographic ID of the raster domain |
the_geom_96703 |
string | projected geometry (US Contiguous Albers Equal Area Conic - SRID 6703) |
the_geom_4326 |
string | geometry (WGS 1984 - SRID 4326) |
city |
string | the city of the source lidar data |
state |
string | the state of the source lidar data |
year |
bigint | the year of the source lidar data |
region_id |
bigint | |
serial_id |
bigint | |
__index_level_0__ |
bigint |
Within each core dataset there are paritions by city_state_year(YY) that can be queried using Apache pyarrow tools or dask, or downloaded as individual geoparquet format data files.
Aspects Lookup:
1 337.5 - 22.5 north
2 22.5 - 67.5 northeast
3 67.5 - 112.5 east
4 112.5 - 157.5 southeast
5 157.5 - 202.5 south
6 202.5 - 247.5 southwest
7 247.5 - 292.5 west
8 292.5 - 337.5 northwest
0 flat flat
Regions Lookup:
1 Albany NY 2006-01-01
2 Albany NY 2013-01-01
3 Albuquerque NM 2006-01-01
4 Albuquerque NM 2012-01-01
5 Allentown PA 2006-01-01
6 Amarillo TX 2008-01-01
7 Anaheim CA 2010-01-01
8 Arnold MO 2006-01-01
9 Atlanta GA 2008-01-01
10 Atlanta GA 2013-01-01
11 Augusta GA 2010-01-01
12 Augusta ME 2008-01-01
13 Austin TX 2006-01-01
14 Austin TX 2012-01-01
15 Bakersfield CA 2010-01-01
16 Baltimore MD 2008-01-01
17 Baltimore MD 2013-01-01
18 Baton Rouge LA 2006-01-01
19 Baton Rouge LA 2012-01-01
20 Birmingham AL 2008-01-01
21 Bismarck ND 2008-01-01
22 Boise ID 2007-01-01
23 Boise ID 2013-01-01
24 Boulder CO 2014-01-01
25 Bridgeport CT 2006-01-01
26 Bridgeport CT 2013-01-01
27 Buffalo NY 2008-01-01
28 Carson City NV 2009-01-01
29 Charleston SC 2010-01-01
30 Charleston WV 2009-01-01
31 Charlotte NC 2006-01-01
32 Charlotte NC 2012-01-01
33 Cheyenne WY 2008-01-01
34 Chicago IL 2008-01-01
35 Chicago IL 2012-01-01
36 Cincinnati OH 2010-01-01
37 Cleveland OH 2012-01-01
38 Colorado Springs CO 2006-01-01
39 Colorado Springs CO 2013-01-01
40 Columbia SC 2009-01-01
41 Columbus GA 2009-01-01
42 Columbus OH 2006-01-01
43 Columbus OH 2012-01-01
44 Concord NH 2009-01-01
45 Corpus Christi TX 2012-01-01
46 Dayton OH 2006-01-01
47 Dayton OH 2012-01-01
48 Denver CO 2012-01-01
49 Des Moines IA 2010-01-01
50 Detroit MI 2012-01-01
51 Dover DE 2009-01-01
52 El Paso TX 2007-01-01
53 Flint MI 2009-01-01
54 Fort Wayne IN 2008-01-01
55 Frankfort KY 2012-01-01
56 Fresno CA 2006-01-01
57 Fresno CA 2013-01-01
58 Ft Belvoir DC 2012-01-01
59 Grand Rapids MI 2013-01-01
60 Greensboro NC 2009-01-01
61 Harrisburg PA 2009-01-01
62 Hartford CT 2006-01-01
63 Hartford CT 2013-01-01
64 Helena MT 2007-01-01
65 Helena MT 2013-01-01
66 Houston TX 2010-01-01
67 Huntsville AL 2009-01-01
68 Indianapolis IN 2006-01-01
69 Indianapolis IN 2012-01-01
70 Jackson MS 2007-01-01
71 Jacksonville FL 2010-01-01
72 Jefferson City MO 2008-01-01
73 Kansas City MO 2010-01-01
74 Kansas City MO 2012-01-01
75 LaGuardia JFK NY 2012-01-01
76 Lancaster PA 2010-01-01
77 Lansing MI 2007-01-01
78 Lansing MI 2013-01-01
79 Las Vegas NV 2009-01-01
80 Lexington KY 2012-01-01
81 Lincoln NE 2008-01-01
82 Little Rock AR 2008-01-01
83 Los Angeles CA 2007-01-01
84 Louisville KY 2006-01-01
85 Louisville KY 2012-01-01
86 Lubbock TX 2008-01-01
87 Madison WI 2010-01-01
88 Manhattan NY 2007-01-01
89 McAllen TX 2008-01-01
90 Miami FL 2009-01-01
91 Milwaukee WI 2007-01-01
92 Milwaukee WI 2013-01-01
93 Minneapolis MN 2007-01-01
94 Minneapolis MN 2012-01-01
95 Mission Viejo CA 2013-01-01
96 Mobile AL 2010-01-01
97 Modesto CA 2010-01-01
98 Montgomery AL 2007-01-01
99 Montpelier VT 2009-01-01
100 Newark NJ 2007-01-01
101 New Haven CT 2007-01-01
102 New Haven CT 2013-01-01
103 New Orleans LA 2008-01-01
104 New Orleans LA 2012-01-01
105 New York NY 2005-01-01
106 New York NY 2013-01-01
107 Norfolk VA 2007-01-01
108 Oklahoma City OK 2007-01-01
109 Oklahoma City OK 2013-01-01
110 Olympia WA 2010-01-01
111 Omaha NE 2007-01-01
112 Omaha NE 2013-01-01
113 Orlando FL 2009-01-01
114 Oxnard CA 2010-01-01
115 Palm Bay FL 2010-01-01
116 Pensacola FL 2009-01-01
117 Philadelphia PA 2007-01-01
118 Pierre SD 2008-01-01
119 Pittsburgh PA 2004-01-01
120 Pittsburgh PA 2012-01-01
121 Portland OR 2012-01-01
122 Poughkeepsie NY 2012-01-01
123 Providence RI 2004-01-01
124 Providence RI 2012-01-01
125 Raleigh-Durham NC 2010-01-01
126 Reno NV 2007-01-01
127 Richmond VA 2008-01-01
128 Richmond VA 2013-01-01
129 Rochester NY 2008-01-01
130 Rochester NY 2014-01-01
131 Sacramento CA 2012-01-01
132 Salem OR 2008-01-01
133 Salt Lake City UT 2012-01-01
134 San Antonio TX 2008-01-01
135 San Antonio TX 2013-01-01
137 San Diego CA 2008-01-01
138 San Diego CA 2013-01-01
139 San Francisco CA 2013-01-01
140 Santa Fe NM 2009-01-01
141 Sarasota FL 2009-01-01
142 Scranton PA 2008-01-01
143 Seattle WA 2011-01-01
144 Shreveport LA 2008-01-01
145 Spokane WA 2008-01-01
146 Springfield IL 2009-01-01
147 Springfield MA 2007-01-01
148 Springfield MA 2013-01-01
149 St Louis MO 2008-01-01
150 St Louis MO 2013-01-01
151 Stockton CA 2010-01-01
152 Syracuse NY 2008-01-01
153 Tallahassee FL 2009-01-01
154 Tampa FL 2008-01-01
155 Toledo OH 2006-01-01
156 Toledo OH 2012-01-01
157 Topeka KS 2008-01-01
158 Trenton NJ 2008-01-01
159 Tucson AZ 2007-01-01
160 Tulsa OK 2008-01-01
161 Washington DC 2009-01-01
162 Washington DC 2012-01-01
163 Wichita KS 2012-01-01
164 Winston-Salem NC 2009-01-01
165 Worcester MA 2009-01-01
166 Youngstown OH 2008-01-01
167 Andrews AFB DC 2012-01-01
136 San Bernardino-Riverside CA 2012-01-01
168 Tampa FL 2013-01-01
Sample code
A complete Python example of accessing and visualizing some of these data is available in the accompanying sample notebook.
Mounting the container
We also provide an API to get read-only SAS (shared access signature) tokens to allow access via, e.g., BlobFuse, which allows you to mount blob containers as drives:
https://planetarycomputer.microsoft.com/api/sas/v1/token/nrel/oedi
API documentation is at https://planetarycomputer.microsoft.com/api/sas/v1/docs.
Mounting instructions for Linux are here.
References
Main References:
-
Rooftop Solar Photovoltaic Technical Potential in the United States: A Detailed Assessment
-
Using GIS-based methods and lidar data to estimate rooftop solar technical potential in US cities
-
Rooftop Photovoltaic Technical Potential in the United States
Related Reference:
-
Rooftop Solar Technical Potential for Low-to-Moderate Income Households in the United States
-
Rooftop Energy Potential of Low Income Communities in America REPLICA
-
Puerto Rico Solar-for-All: LMI PV Rooftop Technical Potential and Solar Savings Potential
Disclaimer and Attribution
Copyright (c) 2020, Alliance for Sustainable Energy LLC, All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
-
Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
-
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
-
Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Contact
For questions about this dataset, contact aiforearthdatasets@microsoft.com.
Notices
Microsoft provides this dataset on an “as is” basis. Microsoft makes no warranties (express or implied), guarantees, or conditions with respect to your use of the dataset. To the extent permitted under your local law, Microsoft disclaims all liability for any damages or losses * including direct, consequential, special, indirect, incidental, or punitive * resulting from your use of this dataset. This dataset is provided under the original terms that Microsoft received source data.