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David B. Lobell

2000–2026 年に発表

134
論文数
58,175
被引用数
90
h 指数
122
i10 指数

被引用数

David B. Lobell の年別被引用数1998 年: 被引用 1 件2001 年: 被引用 3 件2002 年: 被引用 7 件2003 年: 被引用 19 件2004 年: 被引用 25 件2005 年: 被引用 29 件2006 年: 被引用 18 件2007 年: 被引用 42 件2008 年: 被引用 96 件2009 年: 被引用 114 件2010 年: 被引用 173 件2011 年: 被引用 245 件2012 年: 被引用 241 件2013 年: 被引用 243 件2014 年: 被引用 332 件2015 年: 被引用 348 件2016 年: 被引用 372 件2017 年: 被引用 439 件2018 年: 被引用 495 件2019 年: 被引用 787 件2020 年: 被引用 1,053 件2021 年: 被引用 1,191 件2022 年: 被引用 1,074 件2023 年: 被引用 791 件2024 年: 被引用 1,059 件2025 年: 被引用 761 件2026 年: 被引用 150 件1999〜2000 年は被引用が無いため表示していません

引用元

国・地域

この著者を引用した国・地域の世界地図アメリカ合衆国: 引用元論文 2,454 件、この内訳の 19.3%中国: 引用元論文 2,079 件、この内訳の 16.4%イギリス: 引用元論文 717 件、この内訳の 5.6%ドイツ: 引用元論文 688 件、この内訳の 5.4%オーストラリア: 引用元論文 592 件、この内訳の 4.7%インド: 引用元論文 507 件、この内訳の 4%フランス: 引用元論文 401 件、この内訳の 3.2%イタリア: 引用元論文 323 件、この内訳の 2.5%カナダ: 引用元論文 320 件、この内訳の 2.5%オランダ: 引用元論文 277 件、この内訳の 2.2%スペイン: 引用元論文 264 件、この内訳の 2.1%スイス: 引用元論文 202 件、この内訳の 1.6%
0%19.3%その他 30.5%

機関

分野

  • Environmental Science34.8%
  • Agricultural and Biological Sciences27.2%
  • Engineering8.2%
  • Biochemistry, Genetics and Molecular Biology7.7%
  • Computer Science7.5%
  • Social Sciences5%
  • その他9.6%

トピック

  • Remote Sensing in Agriculture7.9%
  • Climate change impacts on agriculture3.8%
  • Land Use and Ecosystem Services3.2%
  • Remote-Sensing Image Classification3.2%
  • Smart Agriculture and AI2.5%
  • Plant Water Relations and Carbon Dynamics2.2%
  • その他77.2%

共著者

全論文

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  1. Transfer learning in environmental remote sensing

    著者: Yuchi Ma, Shuo Chen, Stefano Ermon, David B. Lobell - Remote Sensing of Environment 2023 被引用: 372

  2. Temperature increase reduces global yields of major crops in four independent estimates

    著者: Chuang Zhao, Bing Liu, Shilong Piao, Xuhui Wang, David B. Lobell, Yao Huang, Mengtian Huang, Yitong Yao, Simona Bassu, Philippe Ciais, J. L. Durand, Joshua Elliott, Frank Ewert, Ivan A. Janssens, Tao Li, Erda Lin, Qiang Liu, Pierre Martre, Christoph Müller, Shushi Peng, Josep Peñuelas, Alex C. Ruane, Daniel Wallach, Tao Wang, Donghai Wu, Zhuo Liu, Yan Zhu, Zaichun Zhu, Senthold Asseng - National Academy of Sciences, Proceedings of the National Academy of Sciences 2017 被引用: 3,159

  3. Combining satellite imagery and machine learning to predict poverty

    著者: Neal Jean, Marshall Burke, Sang Michael Xie, W. Matthew Davis, David B. Lobell, Stefano Ermon - Science 2016 被引用: 1,676

  4. SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery

    著者: Yezhen Cong, Samar Khanna, Chenlin Meng, Patrick Liu, Erik Rozi, Yutong He, Marshall Burke, David B. Lobell, Stefano Ermon - Advances in Neural Information Processing Systems 35, NeurIPS 2022 被引用: 602

  5. Using satellite imagery to understand and promote sustainable development

    著者: Marshall Burke, Anne Driscoll, David B. Lobell, Stefano Ermon - Science 2020 被引用: 424

  6. GeoLLM: Extracting Geospatial Knowledge from Large Language Models

    著者: Rohin Manvi, Samar Khanna, Gengchen Mai, Marshall Burke, David B. Lobell, Stefano Ermon - ICLR 2024 被引用: 109

  7. Climate Trends and Global Crop Production Since 1980

    著者: David B. Lobell, Wolfram Schlenker, Justin Costa-Roberts - Science 2011 被引用: 4,514

  8. DiffusionSat: A Generative Foundation Model for Satellite Imagery

    著者: Samar Khanna, Patrick Liu, Linqi Zhou, Chenlin Meng, Robin Rombach, Marshall Burke, David B. Lobell, Stefano Ermon - ICLR 2024 被引用: 190

  9. Large Language Models are Geographically Biased

    著者: Rohin Manvi, Samar Khanna, Marshall Burke, David B. Lobell, Stefano Ermon - ICML 2024 被引用: 126

  10. Using publicly available satellite imagery and deep learning to understand economic well-being in Africa

    著者: Christopher Yeh, Anthony Perez, Anne Driscoll, George Azzari, Zhongyi Tang, David B. Lobell, Stefano Ermon, Marshall Burke - Nature Communications 2020 被引用: 409

  11. Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches

    著者: Yaping Cai, Kaiyu Guan, David B. Lobell, Andries Potgieter, Shaowen Wang, Jian Peng, Tianfang Xu, Senthold Asseng, Yongguang Zhang, Liangzhi You, Bin Peng - Agricultural and Forest Meteorology 2019 被引用: 571

  12. Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data

    著者: Jiaxuan You, Xiaocheng Li, Melvin Low, David B. Lobell, Stefano Ermon - AAAI Conference on Artificial Intelligence 2017 被引用: 564

  13. Rising temperatures reduce global wheat production

    著者: Senthold Asseng, Frank Ewert, Pierre Martre, Reimund P. Rötter, David B. Lobell, Davide Cammarano, Bruce A. Kimball, Michael J. Ottman, Gerard W. Wall, Jeffrey W. White, Matthew Reynolds, Phillip D. Alderman, P. V. Vara Prasad, Pramod Aggarwal, Jakarat Anothai, Bruno Basso, Christian Biernath, Andrew J. Challinor, Giacomo De Sanctis, Jordi Doltra, Elías Fereres, Margarita García‐Vila, Sebastian Gayler, Gerrit Hoogenboom, L. A. Hunt, R. C. Izaurralde, Mohamed Jabloun, Curtis D. Jones, Kurt Christian Kersebaum, A-K. Koehler, Christoph Müller, Soora Naresh Kumar, Claas Nendel, Garry J. O’Leary, Jørgen E. Olesen, Taru Palosuo, Eckart Priesack, Ehsan Eyshi Rezaei, A. C. Ruane, Mikhail A. Semenov, Iurii Shcherbak, Claudio Stöckle, Pierre Stratonovitch, Thilo Streck, Iwan Supit, Fulu Tao, Peter J. Thorburn, Katharina Waha, Enli Wang, Daniel Wallach, J. Wolf, Zhigan Zhao, Yan Zhu - Nature Climate Change 2014 被引用: 2,401

  14. Crop type mapping without field-level labels: Random forest transfer and unsupervised clustering techniques

    著者: Sherrie Wang, George Azzari, David B. Lobell - Remote Sensing of Environment 2019 被引用: 417

  15. Weakly Supervised Deep Learning for Segmentation of Remote Sensing Imagery

    著者: Sherrie Wang, William Chen, Sang Michael Xie, George Azzari, David B. Lobell - Remote Sensing, Remote. Sens. 2020 被引用: 259

  16. Early- and in-season crop type mapping without current-year ground truth: generating labels from historical information via a topology-based approach

    著者: Chenxi Lin, Liheng Zhong, Xiao-Peng Song, Jinwei Dong, David B. Lobell, Zhenong Jin - Remote Sensing of Environment 2022 被引用: 148

  17. A meta-analysis of crop yield under climate change and adaptation

    著者: Andrew J. Challinor, James Watson, David B. Lobell, Mark Howden, Daniel R. Smith, Netra Chhetri - Nature Climate Change 2014 被引用: 2,273

  18. A scalable satellite-based crop yield mapper

    著者: David B. Lobell, David Thau, Christopher Seifert, Eric Engle, Bertis B. Little - Remote Sensing of Environment 2015 被引用: 580

  19. The Influence of Climate Change on Global Crop Productivity

    著者: David B. Lobell, Sharon Gourdji - PLANT PHYSIOLOGY 2012 被引用: 1,289

  20. Deep Transfer Learning for Crop Yield Prediction with Remote Sensing Data

    著者: Anna X. Wang, Caelin Tran, Nikhil Desai, David B. Lobell, Stefano Ermon - SIGCAS Conference on Computing and Sustainable Societies, COMPASS 2018 被引用: 253

  21. Unlocking Large-Scale Crop Field Delineation in Smallholder Farming Systems with Transfer Learning and Weak Supervision

    著者: Sherrie Wang, François Waldner, David B. Lobell - Remote Sensing, Remote. Sens. 2022 被引用: 59

  22. Greater Sensitivity to Drought Accompanies Maize Yield Increase in the U.S. Midwest

    著者: David B. Lobell, Michael J. Roberts, Wolfram Schlenker, Noah Braun, Bertis B. Little, Roderick M. Rejesus, Graeme Hammer - Science 2014 被引用: 1,129

  23. Smallholder maize area and yield mapping at national scales with Google Earth Engine

    著者: Zhenong Jin, George Azzari, Calum You, Stefania Di Tommaso, Stephen Aston, Marshall Burke, David B. Lobell - Remote Sensing of Environment 2019 被引用: 369

  24. On the use of statistical models to predict crop yield responses to climate change

    著者: David B. Lobell, Marshall Burke - Agricultural and Forest Meteorology 2010 被引用: 982