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https://github.com/djdhairya/rooftop-solar-detection
https://github.com/djdhairya/rooftop-solar-detection
data-processing data-science deep-learning eda machine-learning pandas scikit-learn tif
Last synced: 27 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/djdhairya/rooftop-solar-detection
- Owner: djdhairya
- Created: 2024-08-18T17:51:18.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-08-18T17:59:12.000Z (3 months ago)
- Last Synced: 2024-10-10T08:01:40.663Z (27 days ago)
- Topics: data-processing, data-science, deep-learning, eda, machine-learning, pandas, scikit-learn, tif
- Language: Jupyter Notebook
- Homepage: https://youtu.be/pK8fs3JcQ6U?si=1qXcQMuF8sRADsMV
- Size: 50.6 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Rooftop-Solar-Detection
Granular data on distributed rooftop solar PV is becoming increasingly important as solar photovoltaic (PV) becomes a significant segment of the energy industry. An imagery-based solar panel recognition algorithm that can be used to create detailed databases of installations and their power capacity would be extremely helpful to solar power suppliers and consumers, urban planners, grid system operators, and energy policy makers. The fact that solar panel installers typically keep installation details to themselves is another factor in solar panel detection. A well-known solar panel detecting technique or algorithm is therefore urgently needed. However, there hasn't been much effort done to identify solar panels in aerial or satellite photographs.
