P12: Monitoring Solar Panel Installations | |
Maturity score | |
Mean: 2.00 | STD: 0.82 |
Constraints and limitations · Cloud presence. · Panels integrated into complex rooftop configurations can be harder to identify due to varying angles and orientations. | |
Relevant user needs UN37: Projection of risk to portfolio assets into the future. | |
R&D gaps · The availability and size of solar panels dataset to train the deep learning model. · Higher costs as balancing higher spatial resolution (to detect small panels) with broader coverage (to monitor larger installations) can be challenging due to cost constraints. · The resolution of thermal sensors is insufficient at the solar panel level. · Price models for commercial EO data. | |
Potential improvements drivers · Provide more training datasets. · Higher-resolution thermal sensors. | |
Utilisation level review | |
Utilisation score | |
Mean: 3.00 | STD: 0.89 |
No utilisation Unawareness of the existence of this EO product. Low utilisation Medium utilisation Unawareness of the existence of the best available commercial EO product with better specifications. High utilisation | |
Critical gaps related to relevant user needs | |
| |
Overview
Community Forums
Content Tools
This page has no comments.