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Gap-filling approaches for eddy covariance methane fluxes: A comparison of three machine learning algorithms and a traditional method with principal component analysis 期刊论文
GLOBAL CHANGE BIOLOGY, 2019
作者:  Kim, Yeonuk;  Johnson, Mark S.;  Knox, Sara H.;  Black, T. Andrew;  Dalmagro, Higo J.;  Kang, Minseok;  Kim, Joon;  Baldocchi, Dennis
收藏  |  浏览/下载：16/0  |  提交时间：2019/11/27
artificial neural network  comparison of gap-filling techniques  eddy covariance  machine learning  marginal distribution sampling  methane flux  random forest  support vector machine  
Improving Atmospheric River Forecasts With Machine Learning 期刊论文
GEOPHYSICAL RESEARCH LETTERS, 2019
作者:  Chapman, W. E.;  Subramanian, A. C.;  Delle Monache, L.;  Xie, S. P.;  Ralph, F. M.
收藏  |  浏览/下载：4/0  |  提交时间：2019/11/27
atmospheric river  machine learning  convolutional neural network  postprocess  forecasting  
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  
First Effort at Constructing a High-Density Photosynthetically Active Radiation Dataset during 1961-2014 in China 期刊论文
JOURNAL OF CLIMATE, 2019, 32 (10) : 2761-2780
作者:  Qin, Wenmin;  Wang, Lunche;  Zhang, Ming;  Niu, Zigeng;  Luo, Ming;  Lin, Aiwen;  Hu, Bo
收藏  |  浏览/下载：7/0  |  提交时间：2019/11/26
Atmosphere  Asia  Radiative forcing  Shortwave radiation  Data processing  Databases  
High-resolution mapping of daily climate variables by aggregating multiple spatial data sets with the random forest algorithm over the conterminous United States 期刊论文
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2019, 39 (6) : 2964-2983
作者:  Hashimoto, Hirofumi;  Wang, Weile;  Melton, Forrest S.;  Moreno, Adam L.;  Ganguly, Sangram;  Michaelis, Andrew R.;  Nemani, Ramakrishna R.
收藏  |  浏览/下载：10/0  |  提交时间：2019/11/26
daily surface climate  machine learning  NEX-GDM  precipitation  random forest  solar radiation and wind speed  temperature  
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  
Cluster-Based Evaluation of Model Compensating Errors: A Case Study of Cloud Radiative Effect in the Southern Ocean 期刊论文
GEOPHYSICAL RESEARCH LETTERS, 2019, 46 (6) : 3446-3453
作者:  Schuddeboom, Alex;  Varma, Vidya;  McDonald, Adrian J.;  Morgenstern, Olaf;  Harvey, Mike;  Parsons, Simon;  Field, Paul;  Furtado, Kalli
收藏  |  浏览/下载：11/0  |  提交时间：2019/11/26
model evaluation  cloud simulation  Southern Ocean  compensating errors  
Comparison of machine learning algorithms for forest parameter estimations and application for forest quality assessments 期刊论文
FOREST ECOLOGY AND MANAGEMENT, 2019, 434: 224-234
作者:  Zhao, Qingxia;  Yu, Shichuan;  Zhao, Fei;  Tian, Linghong;  Zhao, Zhong
收藏  |  浏览/下载：4/0  |  提交时间：2019/04/09
Machine learning algorithms (MLAs)  Forest parameter estimations  Forest quality (FQ)  Black locust (Robinia pseudoacacia)  
Environmental drivers of fire severity in extreme fire events that affect Mediterranean pine forest ecosystems 期刊论文
FOREST ECOLOGY AND MANAGEMENT, 2019, 433: 24-32
作者:  Garcia-Llamas, Paula;  Suarez-Seoane, Susana;  Taboada, Angela;  Fernandez-Manso, Alfonso;  Quintano, Carmen;  Fernandez-Garcia, Victor;  Manuel Fernandez-Guisuraga, Jose;  Marcos, Elena;  Calvo, Leonor
收藏  |  浏览/下载：4/0  |  提交时间：2019/04/09
LiDAR  Vegetation structure  Physical properties  Fire history  Weather conditions  Landsat  CBI  
A revised above-ground maximum biomass layer for the Australian continent 期刊论文
FOREST ECOLOGY AND MANAGEMENT, 2019, 432: 264-275
作者:  Roxburgh, Stephen H.;  Karunaratne, Senani B.;  Paul, Keryn I.;  Lucas, Richard M.;  Armston, John D.;  Sun, Jingyi
收藏  |  浏览/下载：8/0  |  提交时间：2019/04/09
Forest biomass  Random forest  Carbon accounting  National greenhouse gas inventory