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This dataset demonstrates an optimal size of PV system to be installed on a rooftop area. It is an analysis of residential rooftops (excluding apartment complexes) to estimate a potential capacity of a PV installation. The analysis uses LiDAR data taken in 2018 to estimate solar irradiance and roof shape to estimate the number of 1m x 2m solar panels. This data is then used with PVWatts API created by NREL to estimate the annual AC generated per panel. Each address has one or more entries each representing a continuous area where panels could be installed.

These 3D building shapes are derived from full surface LiDAR by creating roof surface outlines. Exterior walls are projected from the outer edges of the roof outlines to just below the ground surface. The open dataset is not strictly 3D. To download 3D buildings data in Multipatch GDB format (0.35 GB), click zipped geodatabase attachment file, or for 3D buildings in CAD file format (1.17 GB), click zipped Autocad file.
The projection is NAD83 Alberta 3TM 114W (EPSG:3776).

This dataset identifies selected building footprints located on lands under Calgary Parks Stewardship.

“This dataset contains building energy and greenhouse gas emission performance information for a subset of properties owned and operated by the City of Calgary. All energy and greenhouse gas emission metrics are calculated by ENERGY STAR Portfolio Manager using monthly, whole-building energy consumption data billed between January 1st and December 31st.

All blank cells in the dataset correspond to data points that are "not available" because they do not exist or cannot be calculated.”

The DAS Building Roof Outline layer contains polygon features as a graphical representation for individual building roof edge lines. The layer shows the spatial locations of building roof outlines located throughout the City of Calgary.

“This dataset contains building energy and greenhouse gas emission performance information for a subset of properties owned and operated by the City of Calgary. All energy and greenhouse gas emission metrics are calculated by ENERGY STAR Portfolio Manager using monthly, whole-building energy consumption data billed between January 1st and December 31st.

All blank cells in the dataset correspond to data points that are "not available" because they do not exist or cannot be calculated.”

Using data collected in 2012 and 2013, The City has created this solar potential dataset of all buildings within city limits. The data shows varying degrees of a roof’s solar exposure, on an annual basis, in generalized optimal conditions. The data model used to generate the map takes into account the shape of the terrain and the relative position of building rooftops and structures, existing infrastructure, and tree canopies. It doesn’t take into account weather conditions, such as cloudy days and precipitation that limit a roof’s direct solar exposure. It also does not reflect any new adjacent structures built after 2012 that may obstruct another building’s solar exposure.

The Yield levels are measured as kWh\m2\day. Yield values are interpreted as: Low Yield (0 - 0.87); Low Moderate Yield (0.87 - 1.74); High Moderate Yield (1.74 - 2.61); High Yield (2.61 - 3.48)

The compressed file for download is 3 GB. The uncompressed files are 3.35 GB. Data is arranged in Townships, with 16 GeoTiff image files in total.

The Solar map data is intended for information purposes only and as a preliminary solar opportunity assessment tool. It is not intended to be used as a decision making source of information for solar panel installations.

Using data collected between 2012 and 2017, The City has created this solar potential dataset of all buildings within city limits. The data shows varying degrees of a roof’s solar exposure, on an annual basis, in generalized optimal conditions. The data model used to generate the map takes into account the shape of the terrain and the relative position of building rooftops and structures, existing infrastructure, and tree canopies. It doesn’t take into account weather conditions, such as cloudy days and precipitation that limit a roof’s direct solar exposure. It also does not reflect any new adjacent structures built after 2012 that may obstruct another building’s solar exposure.

The Yield levels are measured as kWh\m2\day. Yield values are interpreted as: Low Yield (0 - 0.87); Low Moderate Yield (0.87 - 1.74); High Moderate Yield (1.74 - 2.61); High Yield (2.61 - 3.48)

The compressed file for download is 4.25 GB. The uncompressed files are 4.5 GB. Data is arranged in Townships, with 18 GeoTiff image files in total.

The Solar map data is intended for information purposes only and as a preliminary solar opportunity assessment tool. It is not intended to be used as a decision making source of information for solar panel installations.

Using data collected in 2018, The City has created this solar potential dataset of all buildings within city limits. The data shows varying degrees of a roof’s solar exposure, on an annual basis, in generalized optimal conditions. The data model used to generate the map takes into account the shape of the terrain and the relative position of building rooftops and structures, existing infrastructure, and tree canopies. It doesn’t take into account weather conditions, such as cloudy days and precipitation that limit a roof’s direct solar exposure. It also does not reflect any new adjacent structures built after 2018 that may obstruct another building’s solar exposure.

The Yield levels are measured as kWh\m2\day. Yield values are interpreted as: Low Yield (0 - 0.87); Low Moderate Yield (0.87 - 1.74); High Moderate Yield (1.74 - 2.61); High Yield (2.61 - 3.48)

The compressed file for download is 326 MB. The uncompressed files are 3.95 GB. Data is arranged in Townships, with 21 GeoTiff image files in total.

The Solar map data is intended for information purposes only and as a preliminary solar opportunity assessment tool. It is not intended to be used as a decision making source of information for solar panel installations.