Xiaoliang Lu

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a r t i c l e i n f o In this study, we used the remotely-sensed data from the Moderate Resolution Imaging Spectrometer (MODIS), meteorological and eddy flux data and an artificial neural networks (ANNs) technique to develop a daily evapotranspiration (ET) product for the period of 2004–2005 for the conterminous U.S. We then estimated and analyzed the(More)
Development of regional policies to reduce net emissions of carbon dioxide (CO2) would benefit from the quantification of the major components of the region's carbon balance--fossil fuel CO2 emissions and net fluxes between land ecosystems and the atmosphere. Through spatially detailed inventories of fossil fuel CO2 emissions and a terrestrial(More)
Multivariate alteration detection (MAD) and Bayesian inference (BI) methods are used to analyze land cover changes with Landsat images for the Alaskan Yukon River Basin from 1984 to 2008. The US Geological Survey National Land Cover Database 2001 (NLCD 2001) is treated as reference information to detect the changes. It is found that the regional land cover(More)
  • Jerry M Melillo, Xiaoliang Lu, David W Kicklighter, John M Reilly, Yongxia Cai, Andrei P Sokolov +1 other
  • 2015
The MIT Joint Program on the Science and Policy of Global Change combines cutting-edge scientific research with independent policy analysis to provide a solid foundation for the public and private decisions needed to mitigate and adapt to unavoidable global environmental changes. Being data-driven, the Program uses extensive Earth system and economic data(More)
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