IDEAS home Printed from https://ideas.repec.org/r/nat/nature/v566y2019i7743d10.1038_s41586-019-0912-1.html
   My bibliography  Save this item

Deep learning and process understanding for data-driven Earth system science

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Wen-Ping Tsai & Dapeng Feng & Ming Pan & Hylke Beck & Kathryn Lawson & Yuan Yang & Jiangtao Liu & Chaopeng Shen, 2021. "From calibration to parameter learning: Harnessing the scaling effects of big data in geoscientific modeling," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
  2. Mario Guevara & Rodrigo Vargas, 2019. "Downscaling satellite soil moisture using geomorphometry and machine learning," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-20, September.
  3. Li, Ziyue & Zhang, Zhao & Zhang, Lingyan, 2021. "Improving regional wheat drought risk assessment for insurance application by integrating scenario-driven crop model, machine learning, and satellite data," Agricultural Systems, Elsevier, vol. 191(C).
  4. Chao, Xiangrui & Ran, Qin & Chen, Jia & Li, Tie & Qian, Qian & Ergu, Daji, 2022. "Regulatory technology (Reg-Tech) in financial stability supervision: Taxonomy, key methods, applications and future directions," International Review of Financial Analysis, Elsevier, vol. 80(C).
  5. Florian Reiner & Martin Brandt & Xiaoye Tong & David Skole & Ankit Kariryaa & Philippe Ciais & Andrew Davies & Pierre Hiernaux & Jérôme Chave & Maurice Mugabowindekwe & Christian Igel & Stefan Oehmcke, 2023. "More than one quarter of Africa’s tree cover is found outside areas previously classified as forest," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
  6. Zhang, Yi & Cheng, Chuntian & Cai, Huaxiang & Jin, Xiaoyu & Jia, Zebin & Wu, Xinyu & Su, Huaying & Yang, Tiantian, 2022. "Long-term stochastic model predictive control and efficiency assessment for hydro-wind-solar renewable energy supply system," Applied Energy, Elsevier, vol. 316(C).
  7. Licheng Liu & Wang Zhou & Kaiyu Guan & Bin Peng & Shaoming Xu & Jinyun Tang & Qing Zhu & Jessica Till & Xiaowei Jia & Chongya Jiang & Sheng Wang & Ziqi Qin & Hui Kong & Robert Grant & Symon Mezbahuddi, 2024. "Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
  8. Xuehui Pi & Qiuqi Luo & Lian Feng & Yang Xu & Jing Tang & Xiuyu Liang & Enze Ma & Ran Cheng & Rasmus Fensholt & Martin Brandt & Xiaobin Cai & Luke Gibson & Junguo Liu & Chunmiao Zheng & Weifeng Li & B, 2022. "Mapping global lake dynamics reveals the emerging roles of small lakes," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
  9. Rozenstein, Offer & Fine, Lior & Malachy, Nitzan & Richard, Antoine & Pradalier, Cedric & Tanny, Josef, 2023. "Data-driven estimation of actual evapotranspiration to support irrigation management: Testing two novel methods based on an unoccupied aerial vehicle and an artificial neural network," Agricultural Water Management, Elsevier, vol. 283(C).
  10. Ming Zhong & Hongrui Zhang & Tao Jiang & Jun Guo & Jinxin Zhu & Dagang Wang & Xiaohong Chen, 2023. "A Hybrid Model Combining the Cama-Flood Model and Deep Learning Methods for Streamflow Prediction," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(12), pages 4841-4859, September.
  11. Qin, Jun & Jiang, Hou & Lu, Ning & Yao, Ling & Zhou, Chenghu, 2022. "Enhancing solar PV output forecast by integrating ground and satellite observations with deep learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
  12. Jiang, Hou & Lu, Ning & Qin, Jun & Tang, Wenjun & Yao, Ling, 2019. "A deep learning algorithm to estimate hourly global solar radiation from geostationary satellite data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
  13. Pan Xia & Lu Zhang & Min Min & Jun Li & Yun Wang & Yu Yu & Shengjie Jia, 2024. "Accurate nowcasting of cloud cover at solar photovoltaic plants using geostationary satellite images," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
  14. Jiang, Hou & Lu, Ning & Huang, Guanghui & Yao, Ling & Qin, Jun & Liu, Hengzi, 2020. "Spatial scale effects on retrieval accuracy of surface solar radiation using satellite data," Applied Energy, Elsevier, vol. 270(C).
  15. Stephanie R. Clark & Dan Pagendam & Louise Ryan, 2022. "Forecasting Multiple Groundwater Time Series with Local and Global Deep Learning Networks," IJERPH, MDPI, vol. 19(9), pages 1-31, April.
  16. Galaz, Victor & Centeno, Miguel A. & Callahan, Peter W. & Causevic, Amar & Patterson, Thayer & Brass, Irina & Baum, Seth & Farber, Darryl & Fischer, Joern & Garcia, David & McPhearson, Timon & Jimenez, 2021. "Artificial intelligence, systemic risks, and sustainability," Technology in Society, Elsevier, vol. 67(C).
  17. Feng, Jiaojiao & Wang, Weizhen & Che, Tao & Xu, Feinan, 2023. "Performance of the improved two-source energy balance model for estimating evapotranspiration over the heterogeneous surface," Agricultural Water Management, Elsevier, vol. 278(C).
  18. Wan, Zijing & Wei, Fulong & Peng, Jiale & Deng, Chao & Ding, Siqi & Xu, Dongwei & Luo, Xiaobing, 2023. "Application of physical model-based machine learning to the temperature prediction of electronic device in oil-gas exploration logging," Energy, Elsevier, vol. 282(C).
  19. Xu Lian & Wenli Zhao & Pierre Gentine, 2022. "Recent global decline in rainfall interception loss due to altered rainfall regimes," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
  20. Hood, Raleigh R. & Shenk, Gary W. & Dixon, Rachel L. & Smith, Sean M.C. & Ball, William P. & Bash, Jesse O. & Batiuk, Rich & Boomer, Kathy & Brady, Damian C. & Cerco, Carl & Claggett, Peter & de Mutse, 2021. "The Chesapeake Bay program modeling system: Overview and recommendations for future development," Ecological Modelling, Elsevier, vol. 456(C).
  21. Wen Zhang & Jing Li & Yunhao Chen & Yang Li, 2019. "A Surrogate-Based Optimization Design and Uncertainty Analysis for Urban Flood Mitigation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(12), pages 4201-4214, September.
  22. Wang, Yukuan & Liu, Jingxian & Liu, Ryan Wen & Wu, Weihuang & Liu, Yang, 2023. "Interval prediction of vessel trajectory based on lower and upper bound estimation and attention-modified LSTM with bayesian optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
  23. Gürtürk, Mert & Ucar, Ferhat & Erdem, Murat, 2022. "A novel approach to investigate the effects of global warming and exchange rate on the solar power plants," Energy, Elsevier, vol. 239(PD).
  24. Li, Zhuo-Lin & Yu, Jie & Zhang, Xiao-Lin & Xu, Ling-Yu & Jin, Bao-Gang, 2022. "A Multi-Hierarchical attention-based prediction method on Time Series with spatio-temporal context among variables," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 602(C).
  25. Alysha van Duynhoven & Suzana Dragićević, 2021. "Exploring the Sensitivity of Recurrent Neural Network Models for Forecasting Land Cover Change," Land, MDPI, vol. 10(3), pages 1-29, March.
  26. Christopher K. Wikle, 2019. "Comparison of Deep Neural Networks and Deep Hierarchical Models for Spatio-Temporal Data," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(2), pages 175-203, June.
  27. Devis Tuia & Benjamin Kellenberger & Sara Beery & Blair R. Costelloe & Silvia Zuffi & Benjamin Risse & Alexander Mathis & Mackenzie W. Mathis & Frank Langevelde & Tilo Burghardt & Roland Kays & Holger, 2022. "Perspectives in machine learning for wildlife conservation," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
  28. Akash Koppa & Dominik Rains & Petra Hulsman & Rafael Poyatos & Diego G. Miralles, 2022. "A deep learning-based hybrid model of global terrestrial evaporation," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
  29. Jennie Molinder & Sebastian Scher & Erik Nilsson & Heiner Körnich & Hans Bergström & Anna Sjöblom, 2020. "Probabilistic Forecasting of Wind Turbine Icing Related Production Losses Using Quantile Regression Forests," Energies, MDPI, vol. 14(1), pages 1-19, December.
  30. Alberto Ardid & David Dempsey & Corentin Caudron & Shane Cronin, 2022. "Seismic precursors to the Whakaari 2019 phreatic eruption are transferable to other eruptions and volcanoes," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
  31. Xigui Li & Pengnan Xiao & Yong Zhou & Jie Xu & Qing Wu, 2022. "The Spatiotemporal Evolution Characteristics of Cultivated Land Multifunction and Its Trade-Off/Synergy Relationship in the Two Lake Plains," IJERPH, MDPI, vol. 19(22), pages 1-34, November.
  32. J. C. Ryan & L. C. Smith & S. W. Cooley & B. Pearson & N. Wever & E. Keenan & J. T. M. Lenaerts, 2022. "Decreasing surface albedo signifies a growing importance of clouds for Greenland Ice Sheet meltwater production," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
  33. Quansheng Ge & Mengmeng Hao & Fangyu Ding & Dong Jiang & Jürgen Scheffran & David Helman & Tobias Ide, 2022. "Modelling armed conflict risk under climate change with machine learning and time-series data," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
  34. Christopher K. Wikle & Abhirup Datta & Bhava Vyasa Hari & Edward L. Boone & Indranil Sahoo & Indulekha Kavila & Stefano Castruccio & Susan J. Simmons & Wesley S. Burr & Won Chang, 2023. "An illustration of model agnostic explainability methods applied to environmental data," Environmetrics, John Wiley & Sons, Ltd., vol. 34(1), February.
  35. Yuxin Guo & Zhanya Xu & Shuang Zhu & Xiangang Luo & Yinli Xiao, 2023. "Using distributed root soil moisture data to enhance the performance of rainfall thresholds for landslide warning," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(2), pages 1167-1192, January.
  36. Guoxiong Chen & Qiuming Cheng & Timothy W. Lyons & Jun Shen & Frits Agterberg & Ning Huang & Molei Zhao, 2022. "Reconstructing Earth’s atmospheric oxygenation history using machine learning," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
  37. Zhang, Liwenbo & Wilson, Robin & Sumner, Mark & Wu, Yupeng, 2023. "Advanced multimodal fusion method for very short-term solar irradiance forecasting using sky images and meteorological data: A gate and transformer mechanism approach," Renewable Energy, Elsevier, vol. 216(C).
  38. He, Xinlei & Liu, Shaomin & Xu, Tongren & Yu, Kailiang & Gentine, Pierre & Zhang, Zhe & Xu, Ziwei & Jiao, Dandan & Wu, Dongxing, 2022. "Improving predictions of evapotranspiration by integrating multi-source observations and land surface model," Agricultural Water Management, Elsevier, vol. 272(C).
  39. Suraj Pawar & Shady E. Ahmed & Omer San & Adil Rasheed, 2020. "An Evolve-Then-Correct Reduced Order Model for Hidden Fluid Dynamics," Mathematics, MDPI, vol. 8(4), pages 1-25, April.
  40. Zhang, Xinru & Hou, Lei & Liu, Jiaquan & Yang, Kai & Chai, Chong & Li, Yanhao & He, Sichen, 2022. "Energy consumption prediction for crude oil pipelines based on integrating mechanism analysis and data mining," Energy, Elsevier, vol. 254(PB).
  41. Guanyin Shuai & Yan Zhou & Jingli Shao & Yali Cui & Qiulan Zhang & Chaowei Jin & Shuyuan Xu, 2024. "Comparison of Multiple Machine Learning Methods for Correcting Groundwater Levels Predicted by Physics-Based Models," Sustainability, MDPI, vol. 16(2), pages 1-18, January.
  42. Mohanad A. Deif & Ahmed A. A. Solyman & Mohammed H. Alsharif & Seungwon Jung & Eenjun Hwang, 2021. "A Hybrid Multi-Objective Optimizer-Based SVM Model for Enhancing Numerical Weather Prediction: A Study for the Seoul Metropolitan Area," Sustainability, MDPI, vol. 14(1), pages 1-17, December.
  43. Zhang, Shuangyi & Li, Xichen, 2021. "Future projections of offshore wind energy resources in China using CMIP6 simulations and a deep learning-based downscaling method," Energy, Elsevier, vol. 217(C).
  44. Julie Jebeile & Vincent Lam & Mason Majszak & Tim Räz, 2023. "Machine learning and the quest for objectivity in climate model parameterization," Climatic Change, Springer, vol. 176(8), pages 1-19, August.
  45. Zhou, Huanyu & Qiu, Yingning & Feng, Yanhui & Liu, Jing, 2022. "Power prediction of wind turbine in the wake using hybrid physical process and machine learning models," Renewable Energy, Elsevier, vol. 198(C), pages 568-586.
  46. Sanghyeon Choi & Jaeho Shin & Gwanyeong Park & Jung Sun Eo & Jingon Jang & J. Joshua Yang & Gunuk Wang, 2024. "3D-integrated multilayered physical reservoir array for learning and forecasting time-series information," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
  47. Wang, Yangjun & Liu, Kefeng & Zhang, Ren & Qian, Longxia & Shan, Yulong, 2021. "Feasibility of the Northeast Passage: The role of vessel speed, route planning, and icebreaking assistance determined by sea-ice conditions for the container shipping market during 2020–2030," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
  48. Richards, Daniel Rex & Lavorel, Sandra, 2022. "Integrating social media data and machine learning to analyse scenarios of landscape appreciation," Ecosystem Services, Elsevier, vol. 55(C).
  49. Shasha Song & Isaac R. Santos & Huaming Yu & Faming Wang & William C. Burnett & Thomas S. Bianchi & Junyu Dong & Ergang Lian & Bin Zhao & Lawrence Mayer & Qingzhen Yao & Zhigang Yu & Bochao Xu, 2022. "A global assessment of the mixed layer in coastal sediments and implications for carbon storage," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
  50. Feini Huang & Yongkun Zhang & Ye Zhang & Wei Shangguan & Qingliang Li & Lu Li & Shijie Jiang, 2023. "Interpreting Conv-LSTM for Spatio-Temporal Soil Moisture Prediction in China," Agriculture, MDPI, vol. 13(5), pages 1-16, April.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.