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A review of flexibility of residential electricity demand as climate solution in four EU countries 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2020, 15 (7)
作者:  Mata, Erika;  Ottosson, Jonas;  Nilsson, Johanna
收藏  |  浏览/下载：19/0  |  提交时间：2020/08/18
demand side management  flexibility  grid edge  residential buildings  mitigation potentials  electricity demand  
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  
Estimation of water volume in ungauged, dynamic floodplain lakes 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2020, 15 (5)
作者:  Tan, Z.;  Melack, J.;  Li, Y.;  Liu, X.;  Chen, B.;  Zhang, Q.
收藏  |  浏览/下载：12/0  |  提交时间：2020/07/02
floodplain lakes  water volume  remote sensing  hydrological connectivity  
Monitoring hydropower reliability in Malawi with satellite data and machine learning 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2020, 15 (1)
作者:  Falchetta, Giacomo;  Kasamba, Chisomo;  Parkinson, Simon C.
收藏  |  浏览/下载：8/0  |  提交时间：2020/07/02
hydroelectricity  vulnerability  extreme hydroclimatic events  energy-climate-water nexus  random forests  remote sensing  
Machine learning and artificial intelligence to aid climate change research and preparedness 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2019, 14 (12)
作者:  Huntingford, Chris;  Jeffers, Elizabeth S.;  Bonsall, Michael B.;  Christensen, Hannah M.;  Lees, Thomas;  Yang, Hui
收藏  |  浏览/下载：16/0  |  提交时间：2020/02/17
climate change  global warming  extreme weather  drought  artificial intelligence  machine learning  climate simulations  
High-resolution mapping of aboveground biomass for forest carbon monitoring system in the Tri-State region of Maryland, Pennsylvania and Delaware, USA 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2019, 14 (9)
作者:  Huang, Wenli;  39;Neil-Dunne, Jarlath
收藏  |  浏览/下载：9/0  |  提交时间：2019/11/27
forest aboveground biomass  carbon monitoring system  lidar  forest inventory analysis  Maryland  Delaware  Pennsylvania  
How can Big Data and machine learning benefit environment and water management: a survey of methods, applications, and future directions 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2019, 14 (7)
作者:  Sun, Alexander Y.;  Scanlon, Bridget R.
收藏  |  浏览/下载：9/0  |  提交时间：2019/11/27
machine learning  deep learning  predictive analytics  artificial intelligence  environmental management  big Data  remote sensing  
Modeling spatial climate change landuse adaptation with multi-objective genetic algorithms to improve resilience for rice yield and species richness and to mitigate disaster risk 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2019, 14 (2)
作者:  Yoon, Eun Joo;  Thorne, James H.;  Park, Chan;  Lee, Dong Kun;  Kim, Kwang Soo;  Yoon, Heeyeun;  Seo, Changwan;  Lim, Chul-Hee;  Kim, Haeryung;  Song, Young-Il
收藏  |  浏览/下载：8/0  |  提交时间：2019/04/09
scenario planning  landslides  economic value  landuse conversion  trade-offs  South Korea  
Machine learning to analyze the social-ecological impacts of natural resource policy: insights from community forest management in the Indian Himalaya 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2019, 14 (2)
作者:  Rana, Pushpendra;  Miller, Daniel C.
收藏  |  浏览/下载：5/0  |  提交时间：2019/04/09
forest policy  community forest management  forest livelihoods  deforestation  machine learning  impact evaluation  
Integrating snow science and wildlife ecology in Arctic-boreal North America 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2019, 14 (1)
作者:  Boelman, Natalie T.;  Liston, Glen E.;  Gurarie, Eliezer;  Meddens, Arjan J. H.;  Mahoney, Peter J.;  Kirchner, Peter B.;  Bohrer, Gil;  Brinkman, Todd J.;  Cosgrove, Chris L.;  Eitel, Jan U. H.;  Hebblewhite, Mark;  Kimball, John S.;  LaPoint, Scott;  Nolin, Anne W.;  Pedersen, Stine Hojlund;  Prugh, Laura R.;  Reinking, Adele K.;  Vierling, Lee A.
收藏  |  浏览/下载：11/0  |  提交时间：2019/11/26
ABoVE  Arctic boreal vulnerability experiment  caribou  Dall sheep  polar bear  remote sensing  snow