The DOI matches its Crossref record; 80 of the 80 references it cites were found in a registry or an index.
Automatic detection of solar photovoltaic arrays in high resolution aerial imagery
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“Since the locations and sizes of rooftop solar panels are often unknown to electricity system operators, previous work has used computer vision techniques on satellite imagery to generate size and location data for rooftop solar panels [165,514,868].”
From Tackling climate change with machine learning (2023) · cites this paper as [514]
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Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
A Threshold Selection Method from Gray-Level Histograms
Otsu, N. (1979) · IEEE Transactions on Systems, Man and Cybernetics · doi:10.1109/tsmc.1979.4310076 · Cited by 44,708 · cited 2×
“Regions are grown around each remaining maxima location using Otsu’s method [70], which automatically segments pixels into foreground (high confidence) and background (low confidence) regions.”
Method(2014) · Climate Change 2013 – The Physical Science Basis · doi:10.1017/cbo9781107415324.004 · Cited by 23,880
Book Review: Pattern Recognition and Machine Learning
Nasrabadi, N. M. (2007) · Journal of Electronic Imaging · doi:10.1117/1.2819119 · Cited by 22,066 · cited 1×
“This is a common approach for supervised machine learning algorithms [49].”
MethodClassification and Regression Trees.
Ryzin, J. V., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1986) · Journal of the American Statistical Association · doi:10.2307/2288003 · Cited by 21,030
Seel, N. M. (2012) · Springer eBooks · doi:10.1007/978-1-4419-1428-6_5195 · Cited by 19,482
Robust Real-Time Face Detection
Viola, P., & Jones, M. J. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000013087.49260.fb · Cited by 14,097
Classification and regression trees
Praagman, J. (1985) · European Journal of Operational Research · doi:10.1016/0377-2217(85)90321-2 · Cited by 10,053
Pattern Recognition and Machine Learning
(2007) · Kybernetes · doi:10.1108/03684920710743466 · Cited by 8,545
Russell, E. L., Chiang, L. H., & Braatz, R. D. (2000) · Advances in industrial control · doi:10.1007/978-1-4471-0409-4_3 · Cited by 7,938
Research works printed but not linked: 3
- Mokhtarzade, 2007, Road detection from high-resolution satellite images using artificial neural networks, Int J Appl Earth Obs Geoinf, 9, 32
- Bishop, 2006, vol. 1
- Theodoridis, 1999, Pattern Recogn
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A global inventory of photovoltaic solar energy generating units
Kruitwagen, L., Story, K. T., Friedrich, J., Byers, L., Skillman, S. W., & Hepburn, C. J. (2021) · Nature · doi:10.1038/s41586-021-03957-7 · Cited by 502
Yu, J., Wang, Z., Majumdar, A., & Rajagopal, R. (2018) · Joule · doi:10.1016/j.joule.2018.11.021 · Cited by 362
Li, K., Wang, F., Mi, Z., Fotuhi‐Firuzabad, M., Duić, N., & Wang, T. (2019) · Applied Energy · doi:10.1016/j.apenergy.2019.113595 · Cited by 224
Tackling climate change with machine learning
Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys · doi:10.1145/3485128 · Cited by 336
“[90] Jordan M Malof, Kyle Bradbury, Leslie M Collins, and Richard G Newell.”
BackgroundPersello, C., Wegner, J. D., Hänsch, R., Tuia, D., Ghamisi, P., Koeva, M., & Camps‐Valls, G. (2022) · IEEE Geoscience and Remote Sensing Magazine · doi:10.1109/mgrs.2021.3136100 · Cited by 222
Metadata
- Authors
- Malof, J. M., Bradbury, K., Collins, L. M., & Newell, R. G.
- Affiliations
- Duke University (US)
- Corresponding author
- Malof, Jordan M.
- Venue
- Applied Energy
- Publisher
- Elsevier BV
- Published
- 2016-12
- Volume
- 183
- Pages
- 229-240
- ISSN
- 0306-2619 (ISSN-L)
- OpenAlex
- W2494424066
- Cited by
- 196
- References
- 76
- Citations by year
- 2026: 17 · 2025: 29 · 2024: 23 · 2023: 32 · 2022: 28 · 2021: 23 · 2020: 19 · 2019: 8 · 2018: 8 · 2017: 7 · 2016: 2
- FWCI
- 6.86
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Applied Energy (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- arXiv (Cornell University)
- Funders
- Wells Fargo
- Alfred P. Sloan Foundation
- Topics
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Solar Radiation and Photovoltaics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Remote-Sensing Image Classification
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Photovoltaic Systems and Sustainability
- Keywords
- solar photovoltaic array, very high resolution satellite imagery, aerial imagery, automated detection algorithm, solar energy mapping, solar resource assessment
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