Cristina Milesi
Organization:
NASA Ames Research Center
Email:
Business Phone:
Work:
(650) 604-6431
First Author Publications:
- Milesi, C., et al. (2010), Decadal Variations in NDVI and Food Production in India, Remote Sensing, 2, 758-776.
- Milesi, C., et al. (2005), Climate variability, vegetation productivity, and people at risk. Global and Planetary Change, 47, 221-231.
- Milesi, C., et al. (2005), Mapping and modeling the biogeochemical cycling of turf grasses in the United States, Environmental Management, 36, 426-438.
Co-Authored Publications:
- 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.
- 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.
- Ganguly, S., et al. (2014), Green Leaf Area and Fraction of Photosynthetically Active Radiation Absorbed by Vegetation, Biophysical Applications Satellite Remote Sensing. Berlin/Heidelberg: Springer Verlag, 43-61, doi:10.1007/978-3-642-25047-7_2.
- Rosenzweig, C., et al. (2014), Enhancing climate resilience at NASA centers: A collaboration between science and sewardship, Bull. Am. Meteorol. Soc., doi:/abs/10.1175/BAMS-D-12-00169.1 (submitted).
- Wang, W., et al. (2014), Variations in atmospheric CO2 growth rates coupled with tropical temperature, Proc. Natl. Acad. Sci., 13061-13066, doi:10.1073/pnas.1219683110.
- Zhang, G., et al. (2014), Estimation of forest aboveground biomass in California using canopy height and leaf area index estimated from satellite data, Remote Sensing of Environment, doi:10.1016/j.rse.2014.01.025.
- Hashimoto, H., et al. (2013), Structural Uncertainty in Model-Simulated Trends of Global Gross Primary Production. Remote Sensing, Remote Sensing, 5, 1258-1273, doi:10.3390/rs5031258.
- Laurent, O., et al. (2013), Green spaces and pregnancy outcomes in Southern California, Health & Place, 24, 190-195.
- Small, C., and C. Milesi (2013), Multi-scale standardized spectral mixture models, Remote Sensing of Environment, 136, 442-454, doi:10.1016/j.rse.2013.05.024.
- Ganguly, S., et al. (2012), Generating global Leaf Area Index from Landsat: Algorithm formulation and demonstration, Remote Sens. Environ., 122, 185-202.
- Hashimoto, H., et al. (2012), Exploring Simple Algorithms for Estimating Gross Primary Production in Forested Areas from Satellite Data, Remote Sensing, 4, 303-326.
- Thenkabail, P. S., et al. (2012), Assessing future risks to agricultural productivity, water resources and food security: how can remote sensing help?, Photogrammetric Engineering and Remote Sensing, 78, 773-782.
- Nemani, R., et al. (2011), Collaborative Supercomputing for Global Change Science., Eos Trans., 92 (13), 109-110, doi:10.1029/2011EO130001.
- Hashimoto, H., et al. (2010), Evaluating the impacts of climate and elevated CO2 on tropical rainforests of the western Amazon basin using ecosystem models and satellite data, Global Change Biology, 16, 255-271.
- 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.
- Elvidge, C. D., et al. (2004), U.S. constructed area approaches the size of Ohio, U.S. constructed area approaches the size of Ohio. EOS Transactions, 85, 233-240.