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Comparative assessment of environmental variables and machine learning algorithms for maize yield prediction in the US Midwest 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2020, 15 (6)
作者:  Kang, Yanghui;  Ozdogan, Mutlu;  Zhu, Xiaojin;  Ye, Zhiwei;  Hain, Christopher;  Anderson, Martha
收藏  |  浏览/下载：15/0  |  提交时间：2020/07/02
crop yields  climate impact  machine learning  deep learning  data-driven  
Sentinel-1 observation frequency significantly increases burnt area detectability in tropical SE Asia 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2020, 15 (5)
作者:  Carreiras, Joao M. B.;  Quegan, Shaun;  Tansey, Kevin;  Page, Susan
收藏  |  浏览/下载：8/0  |  提交时间：2020/07/02
burnt area  tropics  Sentinel-1  radar  machine learning  Indonesia  
Predicting spatial and temporal variability in crop yields: an inter-comparison of machine learning, regression and process-based models 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2020, 15 (4)
作者:  Leng, Guoyong;  Hall, Jim W.
收藏  |  浏览/下载：11/0  |  提交时间：2020/07/02
climate change  crop yield  machine learning  statistical model  crop model  
Food flows between counties in the United States 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2019, 14 (8)
作者:  Lin, Xiaowen;  Ruess, Paul J.;  Marston, Landon;  Konar, Megan
收藏  |  浏览/下载：10/0  |  提交时间：2019/11/27
food flows  networks  algorithm development  
The effects of climate extremes on global agricultural yields 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2019, 14 (5)
作者:  Vogel, Elisabeth;  Donat, Markus G.;  Alexander, Lisa, V;  Meinshausen, Malte;  Ray, Deepak K.;  Karoly, David;  Meinshausen, Nicolai;  Frieler, Katja
收藏  |  浏览/下载：11/0  |  提交时间：2019/11/26
agriculture  crop yields  extreme weather events  random forest  machine learning  
Using machine learning to build temperature-based ozone parameterizations for climate sensitivity simulations 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2018, 13 (10)
作者:  Nowack, Peer;  Braesicke, Peter;  Haigh, Joanna;  Abraham, Nathan Luke;  Pyle, John;  Voulgarakis, Apostolos
收藏  |  浏览/下载：5/0  |  提交时间：2019/04/09
climate change  climate sensitivity  ozone  parameterization  machine learning  big data  climate modeling