arXiv Computer Vision
OpenPVMapper: A Multi-source, Nationwide Database of Rooftop Photovoltaic Systems in France
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arXiv Machine Learning
Sep 16
Nationally Consistent, Locally Incomplete: A Bayesian Remote-Sensing Audit of Rooftop Photovoltaic Registries
The paper presents a Bayesian framework that uses remote sensing to estimate the true rooftop photovoltaic (PV) capacity, correcting for detector imperfections and providing uncertainty estimates. Applied to France, the method yields a 4.03 GWp estimate for rooftop PV below 36 kWp, aligning with transmission operator data within 3.3% nationally but revealing local under‑reports up to 61%. It also identifies a significant truncation bias in French open PV data, highlighting the need for more reliable capacity estimates worldwide.
arXiv Machine Learning
Sep 10
SolarBench: A global solar energy nowcasting benchmark
SolarBench is an open global benchmark for image-based solar nowcasting that consolidates over six million sky and satellite images from 11 sites across a decade, paired with irradiance, PV output, and atmospheric data. The benchmark includes a toolbox for reproducible data access, processing, model development, and evaluation. Using SolarBench, the authors benchmark representative models, uncover a gap between average forecasting accuracy and the capture of rapid solar fluctuations, quantify predictability across cloud regimes, and demonstrate data‑efficient adaptation to new PV systems.
arXiv Computer Vision
Aug 27
OpenCVL: An Open, Diverse, and Large-Scale Dataset for Fine-Grained Cross-View Localization
OpenCVL is a large, open dataset for fine-grained cross-view localization, comprising 617,388 ground‑aerial image pairs from 41 European cities. It blends high‑end sensor data with diverse in‑the‑wild images and includes a curation framework to correct pose annotations, enabling reliable evaluation. The dataset also offers cross‑area and snowy test sets to probe generalization, and experiments show that adding noisy in‑the‑wild data improves model performance on clean tests.
arXiv Machine Learning
Jul 27
Beyond Binary Rooftop Mapping: A Four-Class Deep Learning Framework for Green Roof Potential Assessment from Open Swiss Geospatial Data
arXiv:2607. 22342v1 Announce Type: new Abstract: The development of effective urban climate adaptation strategies requires comprehensive spatial information on rooftops and buildings, since such information underpins the assessment of ecosystem services provided by green infrastructure, particularly for urban heat island (UHI) mitigation.
arXiv Machine Learning
Sep 23
Label-Efficient Learning for Ground-Based Sky-Image Classification: A Benchmark of Transfer Learning, Active Learning, and Pseudo-Labeling on GCD
arXiv:2609.26631v1 Announce Type: new Abstract: Accurate ground-based cloud classification is important for atmospheric monitoring, solar-energy forecasting, aviation weather assessment, and climate...
arXiv Machine Learning
Jun 5
Step-adaptive multimodal fusion network with multi-scale cloud feature learning for ultra-short-term solar irradiance forecasting
arXiv:2606. 06102v1 Announce Type: cross Abstract: Ultra-short-term solar irradiance prediction is critical for photovoltaic system dispatch and power grid stability.