Introduction#
This repo contains the scripts for automated metadata extraction of solar PV installations, using satellite imagery coupled with computer vision techniques. In this package, the user can perform the following actions:
Automatically generate a satellite image using a set of lat-long coordinates, and a Google Maps API key. Users would need to set up a Google Cloud account and get a Maps Static API key. Please refer to Setting Up Google Maps Static API Key section for this process.
Perform image segmentation on the satellite image, to locate the solar array(s) in the image on a pixel-by-pixel basis, using an image segmentation model (panel_detection_model.pth). Get classification of the installation (rooftop, ground mounted fixed-tilt or tracking, carport, etc).
Perform azimuth estimation on each solar array cluster in the masked image.
Detect solar panels and get its latitude, longitude, and address within a geographic bounding box through the SOL-Searcher Pipeline.
Detect and calculate hurricane damage on solar installations given pre-hurricane and post-hurricane satellite imagery through the Hurricane Detection Pipeline.
Detect and calculate hail damage on solar installations given satellite imagery through the Hail Detection pipeline.
Convert NOAA MESH (Maximum Estimated Size of Hail) grib2 files into kml or geojson files.
Estimate tilt and azimuth of a solar array by processing USGS LiDAR data for the array’s location.