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Satellite Sunroof: High-res Digital Surface Models and Roof Segmentation for Global Solar Mapping

Autor: Batchu, Vishal, Wilson, Alex, Peng, Betty, Elkin, Carl, Jain, Umangi, Van Arsdale, Christopher, Goroshin, Ross, Gulshan, Varun

The transition to renewable energy, particularly solar, is key to mitigating climate change. Google's Solar API aids this transition by estimating solar potential from aerial imagery, but its impact is constrained by geographical coverage. This paper

Externí odkaz: http://arxiv.org/abs/2408.14400

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A scalable system to measure contrail formation on a per-flight basis

Autor: Geraedts, Scott, Brand, Erica, Dean, Thomas R., Eastham, Sebastian, Elkin, Carl, Engberg, Zebediah, Hager, Ulrike, Langmore, Ian, McCloskey, Kevin, Ng, Joe Yue-Hei, Platt, John C., Sankar, Tharun, Sarna, Aaron, Shapiro, Marc, Goyal, Nita

Persistent contrails make up a large fraction of aviation's contribution to global warming. We describe a scalable, automated detection and matching (ADM) system to determine from satellite data whether a flight has made a persistent contrail. The AD

Externí odkaz: http://arxiv.org/abs/2308.02707

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Estimating Residential Solar Potential Using Aerial Data

Autor: Goroshin, Ross, Wilson, Alex, Lamb, Andrew, Peng, Betty, Ewonus, Brandon, Ratsch, Cornelius, Raisher, Jordan, Leung, Marisa, Burq, Max, Colthurst, Thomas, Rucklidge, William, Elkin, Carl

Publikováno v: ICLR 2023 - Tackling Climate Change with Machine Learning Workshop

Project Sunroof estimates the solar potential of residential buildings using high quality aerial data. That is, it estimates the potential solar energy (and associated financial savings) that can be captured by buildings if solar panels were to be in

Externí odkaz: http://arxiv.org/abs/2306.13564

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