天美传媒

Dr. Bassil El Masri

Contact

Dr. Bassil El Masri

Dr. Bassil El Masri

Professor, Graduate Program Coordinator
Earth and Environmental Sciences

415 Blackburn Science Building, Murray, KY 42071

Research

My research interests are on the use of remote sensing data and land surface models to study ecosystem dynamics, which includes:

  1. the use of multi-sensor remotely sensed data for estimating ecosystem carbon and water fluxes
  2. modeling ecosystem carbon fluxes at large scale using land surface models, and
  3. investigating the influence of climatic variables on ecosystem functions.

My current research at 天美传媒 is focused on investigating the relationships between environmental controls and deciduous trees phenology to better understand climate change impacts on ecosystem functions. To answer such questions, I have started collecting leaf area index data and continuous soil temperature and moisture data at 天美传媒's Hancock biological station (HBS). Also, students are measuring phenological development for several tree species in 天美传媒 campus as part of a partnership with USA National Phenology Network (NPN)

Research Interests

  • Terrestrial carbon, water and nitrogen cycle
  • LiDAR remote sensing
  • Vegetation phenology
  • Land surface and atmosphere interactions
  • Climate change

Education

  • PhD., Indiana University, 2011
  • MS., Texas Tech University, 2006
  • BS., Lebanese University, 2001

Current Projects

  • Evaluating links between eastern deciduous tree phenology and climate
  • Influence of environmental variables on the seasonal development of LAI in Western Kentucky
  • Investigating the soil-vegetation interactions
  • Methane dynamics described through vegetation-soil interactions in bald cypress and other bottomland hardwood forests
  • Assessing the impacts of Physiological and Environmental controls on the Accuracy of WUE: Linking Field Observations, Satellite Imagery, and Land Surface Model

Teaching

  • EES 110: World Geography
  • EES 199: Earth Sciences
  • EES2 202: Introduction to Geographical Information Science
  • EES 522/622: Digital Cartography
  • EES 555/655: Big Data Analysis in Environmental Sciences
  • EES 578/678: Terrestial Ecosystem Modeling
  • EES 579/679: Remote Sensing of Vegetation
  • EES 619: Seminar in Research Techniques

Grants and Research Awards

  • 2021-23, PI, funding from DOE ($299,846). Title: "Methane dynamics described through vegetation-soil interactions in bald cypress and other bottomland hardwood forests".
  • 2020-21, PI, funding from NASA EPSCoR ($41,000). Title: "Assessing the Impacts of Physiological and Environmental controls on the Accuracy of WUE: Linking Field Observations, Satellite Imagery, and Land Surface Model".
  • 2018-20, co-PI, funding from U.S. Fish and Wildlife Service ($15,000). Title: "Determining the drivers of native hardwood regeneration in an alluvial floodplain to inform the restoration of post oak flatwoods".
  • 2017-18, PI, funding from NASA EPSCoR ($50,000). Title: " A long-term Monitoring network in Kentucky: Linking climate change to carbon and water use efficiences, and soil properties".
  • 2017-18, PI, funding from 天美传媒 Provost office CISR grant ($3000). Title: " Quantifying soil influences on forest ecohydrology in western Kentucky".
  • 2017-20, co-PI, funding from U.S. Fish and Wildlife Service ($15000). Title: "Determining the drivers of native hardwood regeneration in an alluvial floodplain to inform the restoration of post oak flatwoods".
  • 2016-17, PI, funding from 天美传媒 Provost office CISR grant ($3100). Title: " Evaluating links between eastern deciduous tree phenology and climate".
  • 2015-16, PI, funding from 天美传媒 Provost office CISR grant ($3000). Title:  鈥淚nfluence of Environmental Variables on the Seasonal Development of LAI鈥.
  • 2014-15, PI, funding from Kentucky View mini grant ($3000). Title: 鈥淓xamining the Spatial and Temporal Variability of Soil Moisture in Kentucky Using a Land Surface Model, Remote Sensing and Observational Data鈥.
  • 2006 鈥 07, PI, funding from USGS through Texas Water Resources Institute (TWRI) $4500; Title: 鈥淓stimation of Water Quality Parameters for Lake Kemp Texas Derived From Remotely Sensed Data.鈥.

Awards and Recognitions

  • Ameriflux workshop travel award - 2018
  • NASA KY EPSCoR travel award - 2018
  • Workshop travel award: Advanced Study Program colloquium carbon-climate connections in the Earth systems 鈥 2013.

Journal Publications

  • El Masri, B., G.E. Stinchcomb, H. Cetin, B. Ferguson, S.L. Kim, J. Xiao, J.B. Fisher (2021), Linking Remotely Sensed Carbon and Water Use Efficiencies with In Situ Soil Properties. Remote Sensing, 13, 2593. .
  • Yang, Y., B. Tao, L. Liang, Y. Huang, C. Matocha, C.D. Lee, M. Sama, B. El Masri, W. Ren (2021). Detecting Recent Crop Phenology Dynamics in Corn and Soybean Cropping Systems of Kentucky. Remote Sensing, 13, 1615. .
  • Ferguson, B., W.E. Lukens, B. El Masri, G.E. Stinchcomb (2020). Alluvial landform and the occurrence of paleosols in a humid-subtropical climate have an effect on long-term soil organic carbon storage. Geoderma, 371, 114388.
  • El Masri, B., C. Schwalm, D.N. Huntzinger, J. Mao, X. Shi, C. Peng, J. Fisher, A. Jain, H. Tian, B. Poulter, A.M. Michalak (2019). Carbon and Water Use Efficiencies: A comparative analysis of ten terrestrial ecosystem models under changing climate. Scientific Reports, 9, 14680.
  • Yang, Y., B. Tao, W. Ren, D. Zourarakis, B. El Masri, Z. Sun, and Q. Tian (2019). A Novel Approach Considering Intraclass Variability for Mapping Winter Wheat Using Multi-temporal MODIS EVI Images. Remote Sensing, 11, 1191: doi: 10.3390/rs11101191.
  • El Masri, B., A.F. Rahman, and D.D. Dragoni (2019). Evaluating a New Algorithm for Satellite based Evapotranspiration for North American Ecosystems: Model development and Validation. Agricultural and Forest Meteorology, 268, 243-248.
  • El Masri, B. (2017). Examining the spatial and temporal variability of soil moisture in Kentucky using remote sensing data. Biomed. Sci. & Tech. Res.
  • El Masri, B., S. Shu, A.K. Jain (2015). Implementation of dynamic root depth and phenology into a land surface model: Evaluations of carbon, water, and energy fluxes in the high latitude ecosystems. Agricultural and Forest Meteorology, 211, 85-99.
  • Schwalm, C., D. Huntzinger, J. Fisher, A. Michalak, K. Bowman, P. Ciais, R. Cook, B. El-Masri, et al. (2015). Toward 鈥渙ptimal鈥 integration of terrestrial biosphere models. Geophysical Research Letters, 42(11), 4418-4428.
  • Miller, P., M. Robson. B. El-Masri, R. Barman, G. Zheng, A. Jain, L. Kale (2014). Scaling the ISAM Land Surface Model through parallelization of Inter-Component data transfer. Parallel Processing (ICPP), 2014 43rd International Conference on , vol., no., pp.422,431, 9-12 Sept., doi: 10.1109/ICPP.2014.51
  • Fisher, J.B, M. Sikka, W.C. Oechel, D.N. Huntzinger, J.R. Melton, C.D. Koven, A. Ahlstr枚m, A.M. Arain, I. Baker, J.M. Chen, P. Ciais, C. Davidson, M. Dietze, B. El-Masri, et al. (2014). Carbon cycle uncertainty in Alaskan Arctic. Biogeosciences, 11, 4271-4288
  • Zscheischler, J., A.M. Michalak, C. Schwalm, M.D. Mahecha, D.N. Huntzinger, M. Reichstein, G. Bertheir, P. Ciais, B. El-Masri, et al. (2014). Impact of Large-Scale Climate Extremes on Biospheric Carbon Fluxes: An Intercomparison Based on MsTMIP Data. Global Biogeochemical Cycles, DOI: 10.1002/2014GB004826
  • De Kauwe, M.G., B.E. Medlyn, A.P. Wakler, S. Asao, M.C. Dietze, B. El-Masri, et al. (2014). Where does the carbon go? A model-data intercomparison of carbon allocation at two temperate forest free-air CO2 enrichment sites. New Phytologist, 203(3), 883-899.
  • Zaehle, S., B.E. Medlyn, M.G. De Kauwe, A.P.Walker, M.C. Dietze, T. Hickler, Y. Luo, Y.P.Wang, B. El-Masri, et al. (2014). Evaluation of eleven terrestrial carbon-nitrogen cycle models against observations from two temperate Free-Air CO2 Enrichment Studies. New Phytologist. DOI: 10.1111/nph.12697.
  • El-Masri, B., R. Barman, P. Meiyappan, Y. Song, M. Liang. A. K. Jain (2013). Carbon Dynamics in the Amazonian Basin: Integration of eddy covariance and ecophysiological data with a land surface model. Agricultural and Forest Meteorology. 182-183, 156-167.
  • Rahman, A.F., D. Dragoni., B. El-Masri (2011). Response of the Sundarbans coastline to sea level rise and decreased sediment flow: A remote sensing assessment. Remote Sensing of Environment. 115: 3121-3128.
  • Sim, D. A., A. F. Rahman, C. D. Cordova, B. Z. El-Masri, D. D. Baldocchi, P. V. Bolstad, L.B. Flanagan, A. H. Goldstein, D. Y. Hollinger, L. Mission, R. K. Monson, W. C. Oechel, H. P. Schmid, S. C. Wofsy, L. Xu. (2008). A new model of gross primary productivity for North American ecosystems based solely on the enhanced vegetation index and land surface temperature from MODIS . Remote sensing of Environment. 112: 1633-1646.
  • Sim, D. A., A. F. Rahman, C. D. Cordova, B. Z. El-Masri, D. D. Baldocchi, L. B. Flanagan, A.H. Goldstein, D. Y. Hollinger, L. Mission, R. K. Monson, W. C. Oechel, H.P. Schmid, S. C. Wofsy, L. Xu (2006). On the use of MODIS EVI to assess gross primary productivity of North American ecosystems. Journal of Geophysical Research, 111, G4, G04015, 10.1029/2006JG000162.
  • Rahman .A. F., D. A. Sims, V. D. Cordova, B. Z. El-Masri (2005). Potential of MODIS EVI and Surface Temperature for Directly Estimating Per-Pixel Ecosystem C Fluxes. Geophysical Research Letters, 32, 19, L19404, doi:10.1029/2005GL024127.

Data

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