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  • Ackerman, S. A., K. I. Strabala, W. P. Menzel, R. A. Frey, C. C. Moeller, and L. E. Gumley (1998), Discriminating clear sky from clouds with MODIS, J. Geophys. Res., 103(D24), 32,14132,157, doi:10.1029/1998JD200032.
  • Allen, R. G., L. S. Pereira, D. Raes, and M. Smith (1998), Crop evapotranspiration. Guideline for computing crop water requirements, FAO Irrig. Drain. Pap. 56, 326 pp., Food and Agric. Organ., Rome.
  • Allen, R. G., M. Tasumi, and R. Trezza (2007a), Satellite-based energy balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)-model, J. Irrig. Drain. Eng., 133(4), 380394.
  • Allen, R. G., M. Tasumi, and R. Trezza (2007b), Satellite-based Energy balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)-applications, J. Irrig. Drain. Eng., 133(4), 395406.
  • Allen, R. G., K. Irmak, R. Trezza, J. M. H. Hendrickx, W. G. M. Bastiaanssen, and J. Kjaersgaard (2011a), Satellite-based ET estimation in agriculture using SEBAL and METRIC, Hydrol. Processes, 25, 40114027.
  • Allen, R. G., L. S. Pereira, T. A. Howell, and M. E. Jensen (2011b), Evapotranspiration information reporting: I. Factors governing measurement accuracy, Agric. Water Manage., 98(6), 899920.
  • Anderson, M. C., J. M. Norman, G. R. Diak, W. P. Kustas, and J. R. Mecikalski (1997), A two-source time-integrated model for estimating surface fluxes using thermal infrared remote sensing, Remote Sens. Environ., 60, 195216.
  • Anderson, M. C., C. M. U. Neale, F. Li, J. M. Norman, W. P. Kustas, H. Jayanthi, and J. L. Chavez (2004a), Upscaling ground observations of vegetation water content, canopy height, and leaf area index during SMEX02 using aircraft and Landsat imagery, Remote Sens. Environ., 92, 447464.
  • Anderson, M. C., J. M. Norman, J. R. Mecikalski, R. D. Torn, W. P. Kustas, and J. B. Basara (2004b), A multi-scale remote sensing model for disaggregating regional fluxes to micrometeorological scales, J. Hydrometeorol., 5, 343363.
  • Anderson, M. C., J. M. Norman, W. P. Kustas, F. Li, J. H. Prueger, and J. R. Mecikalski (2005), Effects of vegetation clumping on two-source model estimates of surface energy fluxes from an agricultural landscape during SMACEX, J. Hydrometeorol., 6, 892909.
  • Anderson, M. C., W. P. Kustas, and J. M. Norman (2007a), Upscaling flux observations from local to continental scales using thermal remote sensing, Agron. J., 99, 240254.
  • Anderson, M. C., J. M. Norman, J. R. Mecikalski, J. A. Otkin, and W. P. Kustas (2007b), A climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing: 1. Model formulation, J. Geophys. Res., 112, D11117, doi:10.1029/2006JD007506.
  • Anderson, M. C., J. M. Norman, J. R. Mecikalski, J. A. Otkin, and W. P. Kustas (2007c), A climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing: 2. Surface moisture climatology, J. Geophys. Res., 112, D11112, doi:10.1029/2006JD007507.
  • Anderson, M. C., C. R. Hain, B. Wardlow, J. R. Mecikalski, and W. P. Kustas (2011), Evaluation of a drought index based on thermal remote sensing of evapotranspiration over the continental U.S., J. Clim., 24, 20252044.
  • Anderson, M. C., R. G. Allen, A. Morse, and W. P. Kustas (2012a), Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources, Remote Sens. Environ., 122, 5065.
  • Anderson, M. C., W. P. Kustas, J. G. Alfieri, C. R. Hain, J. H. Prueger, S. R. Evett, P. D. Colaizzi, T. A. Howell, and J. L. Chavez (2012b), Mapping daily evapotranspiration at Landsat spatial scales during the BEAREX'08 field campaign, Adv. Water Resour., 50, 162177.
  • Anderson, M. C., C. R. Hain, J. A. Otkin, X. Zhan, K. C. Mo, M. Svoboda, B. Wardlow, and A. Pimstein (2013), An intercomparison of drought indicators based on thermal remote sensing and NLDAS-2 simulations with U.S. Drought Monitor classifications, J. Hydrometeorol., doi:10.1175/JHM-D-12-0140.1.
  • Bastiaanssen, W. G. M., M. Menenti R. A. Feddes, and A. A. M. Holtslag (1998), The Surface Energy Balance Algorithm for Land (SEBAL): Part 1 formulation, J. Hydrol., 212, 198212.
  • Bastiaanssen, W. G. M., M. D. Ahmad, and Y. Chemin (2002), Satellite surveillance of water use across the Indus Basin, Water Resour. Res., 38(12), 1273, doi:10.1029/2001WR000386.
  • Berk, A., L. S. Bernstein, and D. C. Robertson (1989), MODTRAN: A moderate resolution model for LOWTRAN 7, GL-TR-89–0122, 38 pp., Air Force Geophys. Lab., Bedford, Mass.
  • Bhandari, S., S. Phinn, and T. Gill (2012), Preparing Landsat Image Time Series (LITS) for monitoring changes in vegetation phenology in Queensland, Australia, Remote Sens., 4, 18561886.
  • Brutsaert, W. (1982), Evaporation Into the Atmosphere: Theory, History and Applications, 299 pp., D. Reidel, Boston, Mass.
  • Brutsaert, W., and M. Sugita (1992), Application of self-preservation in the diurnal evolution of the surface energy budget to determine daily evaporation, J. Geophys. Res., 97(D17), 18,37718,382, doi:10.1029/92JD00255.
  • Cammalleri, C., M. C. Anderson, G. Ciraolo, G. D'Urso, W. P. Kustas, G. La Loggia, and M. Minacapilli (2012), Applications of a remote sensing-based two-source energy balance algorithm for mapping surface fluxes without in-situ air temperature observations, Remote Sens. Environ., 124, 502515.
  • Chehbouni, A., Y. Nouvellon, J.-P. Lhomme, C. Watts, G. Boulet, Y. H. Kerr, M. S. Moran, and D. C. Goodrich (2001), Estimation of surface sensible heat flux using dual angle observations of radiative surface temperature, Agric. For. Meteorol., 108, 5565.
  • Chemin, Y., and T. Alexandridis (2004), Improving spatial resolution of ET seasonal for irrigated rice in Zhanghe, China, Asian J. Geoinf., 5(1), 311.
  • Choi, M., W. P. Kustas, M. C. Anderson, R. G. Allen, F. Li, and J. H. Kjaersgaard (2009), An intercomparison of three remote sensing-based surface energy balance algorithms over a corn and soybean production region (Iowa, U.S.) during SMACEX, Agric. For. Meteorol., 149(12), 20822097.
  • Crago, R. D. (1996), Conservation and variability of the evaporative fraction during the daytime, J. Hydrol., 180, 173194.
  • Diak, G. R., and C. Gautier (1983), Improvements to a simple physical model for estimating insolation from GOES data, J. Clim. Appl. Meteorol., 22, 505508.
  • Doraiswamy, P. C., J. L. Hatfield, T. J. Jackson, B. Akhmedoc, J. Prueger, and A. Stern (2004), Crop condition and yield simulations using Landsat and MODIS, Remote Sens. Environ., 92, 548559.
  • Dudhia, J. (1993), A nonhydrostatic version of the Penn State/NCAR mesoscale model: Validation tests and simulation of an Atlantic cyclone and cloud front, Mon. Weather Rev., 121, 14931513.
  • French, A. N., J. M. Norman M. C. Anderson (2003), Simplified correction of GOES thermal infrared observations, Remote Sens. Environ., 87, 326333.
  • French, A. N., et al. (2005), Surface energy fluxes with the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) at the Iowa 2002 SMACEX site (USA), Remote Sens. Environ., 99(1–2), 5565.
  • Gao, F., J. Masek, M. Schwaller, F. Hall (2006), On the blending of the Landsat and MODIS surface reflectance: Predicting daily Landsat surface reflectance, IEEE Trans. Geosci. Remote Sens., 44(8), 22072218.
  • Gao, F., M. C. Anderson, W. P. Kustas, and Y. Wang (2012), Simple method for retrieving leaf area index from Landsat using MODIS leaf area index products as reference, J. Appl. Remote Sens., 6, 063554, doi:10.1117/1.JRS.6.063554.
  • Hall, N. D., B. B. Stuntz, and R. H. Abrams (2008), Climate change and freshwater resources, Nat. Resour. Environ., 22(3), 3035.
  • Hatfield, J. L., D. B. Jaynes, M. R. Burkart, C. A. Cambardella, T. B. Moorman, J. H. Prueger, and M. A. Smith (1999), Water quality in Walnut Creek watershed: Setting and farming practices, J. Environ. Qual., 28, 1124.
  • Hatfield, J. L., J. H. Prueger, and W. P. Kustas (2007), Spatial and temporal variation of energy and carbon fluxes in central Iowa, Agron. J., 99, 285296.
  • Hilker, T., M. A. Wulder, N. C. Coops, J. Linke, G. McDermid, J. F. Masek, F. Gao, and J. C. White (2009), A new data fusion model for high spatial- and temporal-resolution mapping of forest disturbance based on Landsat and MODIS, Remote Sens. Environ., 113(8), 16131627.
  • Homer, C., J. Dewitz, J. Fry, M. Coan, N. Hossain, C. Larson, N. Herold, A. McKerrow, J. N. VanDriel, and J. Wickham (2007), Completion of the 2001 National Land Cover Database for the Conterminous United States, Photogramm. Eng. Remote Sens., 73(4), 337341.
  • Ju, J., and D. P. Roy (2008), The availability of cloud-free Landsat ETM+ data over the conterminous United States and globally, Remote Sens. Environ., 112, 11961211.
  • Kalma, J. D., T. R. McVicar, M. F. McCabe (2008), Estimating land surface evaporation: A review of methods using remotely sensed surface temperature data, Surv. Geophys., 29(4–5), 421469.
  • Kormann, R., and F. X. Meixner (2000), An analytical footprint model for non-neutral stratification, Boundary-Layer Meteorol., 99, 207224.
  • Kustas, W. P., and J. M. Norman (1999), Evaluation of soil and vegetation heat flux predictions using a simple two-source model with radiometric temperatures for partial canopy cover, Agric. For. Meteorol., 99, 1329.
  • Kustas, W. P., J. M. Norman, M. C. Anderson, and A. N. French (2003a), Estimating subpixel surface temperatures and energy fluxes from the vegetation index–radiometric temperature relationship, Remote Sens. Environ., 85, 429440.
  • Kustas, W. P., J. H. Prueger, J. L. Hatfield, J. I. Macpherson, M. Wolde, C. M. U. Neale, W. E. Eichinger, D. I. Cooper, J. M. Norman, and M. C. Anderson (2003b), An overview of the Soil-Moisture Atmospheric-Coupling-Experiment (SMACEX) in central Iowa, paper presented at 17th Conference on Hydrology, Am. Meteorol. Soc., Long Beach, Calif., 9–13 Feb.
  • Kustas, W. P., J. L. Hatfield, and J. H. Prueger (2005), The Soil Moisture Atmosphere Coupling Experiment (SMACEX): Background, hydrometeorological conditions and preliminary findings, J. Hydrometeorol., 6, 791804.
  • Li, F., T. J. Jackson, W. P. Kustas, T. J. Schmugge, A. N. French, M. H. Cosh, and R. Bindlish (2004), Deriving land surface temperature from Landsat 5 and 7 during SMEX02/SMACEX, Remote Sens. Environ., 92, 521534.
  • Li, F., W. P. Kustas, J. H. Prueger, C. M. U. Neale, and T. J. Jackson (2005), Utility of remote sensing-based two-source energy balance model under low- and high-vegetation cover conditions, J. Hydrometeorol., 6, 878891.
  • McNaughton, K. G., and T. W. Spriggs (1986), A mixed-layer model for regional evaporation, Boundary-Layer Meteorol., 34, 243262.
  • Mu, Q., M. Zhao, J. S. Kimball, N. G. McDowell, and S. W. Running (2013), A remotely sensed global terrestrial drought severity index, Bull. Am. Meteorol. Soc., 94(1), 8398, doi:10.1175/bams-d-11–00213.1.
  • Myneni, R. B., et al. (2002), Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data, Remote Sens. Environ., 83(1–2), 214231.
  • Norman, J. M., W. P. Kustas, and K. S. Humes (1995), Source approach for estimating soil and vegetation energy fluxes in observations directional radiometric surface temperature, Agric. For. Meteorol., 77, 263293.
  • Norman, J. M., M. C. Anderson, W. P. Kustas, A. N. French, J. Mecikalski, R. Torn, G. R. Diak, T. J. Schmugge, and B. C. W. Tanner (2003), Remote sensing of surface energy fluxes at 101-m pixel resolution, Water Resour. Res., 39(8), 1221, doi:10.1029/2002WR001775.
  • Otkin, J. A., M. C. Anderson, J. R. Mecikalski, and G. R. Diak (2005), Validation of GOES-based insolation estimates using data from the U.S. climate reference network, J. Hydrometeorol., 6, 460475.
  • Priestley, C. H. B., and R. J. Taylor (1972), On the assessment of surface heat flux and evaporation using large-scale parameters, Mon. Weather Rev., 100, 8192.
  • Roerink, G. J., Z. Su, and M. Menenti (2000), S-SEBI: A simple remote sensing algorithm to estimate the surface energy balance, Phys. Chem. Earth, 25(2), 147157.
  • Santanello, J. A., Jr., and M. A. Friedl (2003), Diurnal covariation in soil heat flux and net radiation, J. Appl. Meteorol., 42, 851862.
  • Schmugge, T. J., W. P. Kustas, J. C. Ritchie T. J. Jackson, and A. Rango (2002), Remote sensing in hydrology, Adv. Water Resour., 25, 13671385.
  • Shuttleworth, W. J., and J. S. Wallace (1985), Evaporation from sparse crops—An energy combination theory, Q. J. R. Meteorol. Soc., 111, 839855.
  • Singh, R. K., S. Liu, L. L. Tieszen, A. E. Suyker, and S. B. Verma (2011), Estimating seasonal evapotranspiration from temporal satellite images, Irrig. Sci., 30(4), 303313, doi:10.1007/s00271-011-0287-z.
  • Tan, B., J. Hu, P. Zhang, D. Huang, N. Shabanov, M. Weiss, Y. Knyazikhin, and R. B. Myneni (2005), Validation of Moderate Resolution Imaging Spectroradiometer leaf area index product in croplands of Alpilles, France, J. Geophys. Res., 110, D01107. doi:10.1029/2004JD004860.
  • Timmermans, W., W. P. Kustas, M. C. Anderson, and A. N. French (2007), An intercomparison of the surface energy balance algorithm for land (SEBAL) and the two-source energy balance (TSEB) modeling schemes, Remote Sens. Environ., 108, 369384.
  • Twine, T. E., W. P. Kustas, J. M. Norman, D. R. Cook, P. R. Houser, T. P. Meyer, J. H. Prueger, P. J. Starks, and M. L. Wesely (2000), Correcting eddy covariance flux underestimates over a grassland, Agric. For. Meteorol., 103(3), 279300.
  • Wan, Z., and Z.-L. Li (1997), A physics-based algorithm for retrieving land-surface emissivity and temperature from EOS/MODIS data, IEEE Trans. Geosci. Remote Sens., 35(4), 980996.
  • Wang, Y., et al. (2004), Evaluation of the MODIS LAI algorithm at a coniferous forest site in Finland, Remote Sens. Environ., 91(1), 114127.
  • Zurita-Milla, R., J. G. P. W. Clevers, and M. E. Schaepman (2008), Unmixing-based Landsat TM and MERIS FR data fusion, IEEE Trans. Geosci. Remote Sens., 5(3), 453457.