Organization
NASA Ames Research Center
Co-Authored Publications
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Kumar, U., et al. (2017), Exploring Subpixel Learning Algorithms for Estimating Global Land Cover Fractions from Satellite Data Using High Performance Computing, Remote Sens., 9, 1105, doi:10.3390/rs9111105.
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Schleeweis, K., et al. (2016), Selection and quality assessment of Landsat data for the North American forest dynamics forest history maps of the US, (Online) Journal homepage, 1753-8955, doi:10.1080/17538947.2016.1158876.
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Basu, S., et al. (2015), A Semiautomated Probabilistic Framework for Tree-Cover Delineation from 1-m NAIP Imagery Using a High-Performance Computing Architecture, IEEE Trans. Geosci. Remote Sens., 53, 5690-5708, doi:10.1109/TGRS.2015.2428197.
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Ichii, K., et al. (2015), Refinement of rooting depths using satellite-based evapotranspiration seasonality for ecosystem modeling in California, 149, 1907-1918 (manuscript in preparation).
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Ganguly, S., et al. (2012), Generating global Leaf Area Index from Landsat: Algorithm formulation and demonstration, Remote Sens. Environ., 122, 185-202.
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Melton, F., et al. (2012), Satellite Irrigation Management Support with the Terrestrial Observation and Prediction System: A Framework for Integration of Satellite and Surface Observations to Support Improvements in Agricultural Water Resource Management, IEEE J. Selected Topics in Applied Earth Observations & Remote Sensing, 5, 1709-1721, doi:10.1109/JSTARS.2012.2214474.
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Nemani, R., et al. (2011), Collaborative Supercomputing for Global Change Science., Eos Trans., 92 (13), 109-110, doi:10.1029/2011EO130001.
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Wang, W., et al. (2010), Diagnosing and assessing uncertainties of terrestiral ecosystem models in a multi-model ensemble experiment: 1, primary production. Global Change Biology, doi:10.111/j.1365-2486.2010.02309.x.
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Hashimoto, H., et al. (2008), Satellite-based estimation of surface vapor pressure deficits using MODIS land surface temperature data, Remote Sensing of Environment, 112, 142-155.
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Ichii, K., et al. (2008), Evaluation of snow models in terrestrial biosphere models using ground observation and satellite data, Impact on terrestrial ecosystem processes. Hydrological Processes, 22, 347-355.
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Yang, F., et al. (2007), Developing a continental-scale measure of gross primary production by combining MODIS and AmeriFlux data through Support Vector Machine approach, Remote Sensing of Environment, 110, 109-122.
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Jolly, ., et al. (2005), A flexible, integrated system for generating meteorological surfaces derived from point sources across multiple geographic scales, Environmental Modeling & Software, 20, 873-882.
Note: Only publications that have been uploaded to the ESD Publications database are listed here.
