Dr. Bassil El Masri


Research Interests:

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


  • PhD., Indiana University, 2011
  • MS., Texas Tech University, 2006
  • BS., Lebanese University, 2001
Assistant Professor
Department of Geosciences
Office: 413 Blackburn
Phone: 270.809.3110
Email: belmasri@murraystate.edu
El Masri CV

Environmental Modeling and Monitoring Lab


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 Murray State 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 Murray State's Hancock biological station (HBS). Also, students are measuring phenological development for several tree species in Murray State campus as part of a partnership with USA National Phenology Network (NPN)


  • 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.


  • GSC 110: World Geography
  • GSC 199: Earth Sciences
  • GSC2 202: Introduction to Geographical Information Science
  • GSC 522/622: Digital Cartography
  • GSC 579/679: Remote Sensing of Vegetation
  • GSC 619: Seminar in Research Techniques


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 Murray State University 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 Murray State University Provost office CISR grant ($3100). Title: " Evaluating links between eastern deciduous tree phenology and climate".

2015-16   PI, funding from Murray State University Provost office CISR grant ($3000). Title:  “Influence of Environmental Variables on the Seasonal Development of LAI”.

2014-15    PI, funding from Kentucky View mini grant ($3000). Title: “Examining the Spatial and Temporal Variability of Soil Moisture in Kentucky Using a Land Surface Model, Remote Sensing and Observational Data”.

2006 – 07    PI, funding from USGS through Texas Water Resources Institute (TWRI) $4500; Title: “Estimation of Water Quality Parameters for Lake Kemp Texas Derived From Remotely Sensed Data.”.


Workshop travel award: Advanced Study Program colloquium carbon-climate connections in the Earth systems – 2013.


El-Masri, B., A.F. Rahman, and D.D. Dragoni (2016). Evaluating a New Algorithm for Satellite based Evapotranspiration for North American Ecosystems: Model development and Validation. In Review.

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 “optimal” 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. Ahlström, 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.