Xiaoliang Lu

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[1] Much progress has been made in methane modeling for the Arctic. However, there is still large uncertainty in emissions estimates due to the spatial variability in water table depth resulting from complex topographic gradients, and due to variations in methane production and oxidation due to complex freezing and thawing processes. Here we extended an(More)
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)
Effects of various spatial scales of water table dynamics on land–atmospheric methane (CH 4) exchanges have not yet been assessed for large regions. Here we used a coupled hydrology–biogeochemistry model to quantify daily CH 4 exchanges over the pan-Arctic from 1993 to 2004 at two spatial scales of 100 km and 5 km. The effects of sub-grid spatial(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)
Climate change will alter ecosystem metabolism and may lead to a redistribution of vegetation and changes in fire regimes in Northern Eurasia over the 21st century. Land management decisions will interact with these climate-driven changes to reshape the region's landscape. Here we present an assessment of the potential consequences of climate change on land(More)
The MIT Joint Program on the Science and Policy of Global Change made extensive use of the GTAP data set for research and analysis conducted in the program over the past year (see the following publication list). GTAP data serves as the principal economic data for the Program's Emissions Prediction and Policy Analysis (EPPA) Model, a global CGE model of the(More)
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)