136
Multiscale Hydrologic Remote Sensing: Perspectives and Applications
Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., and Ferreira, L.G. (2002). Overview
of the radiometric and biophysical performance of the MODIS vegetation indices.
Remote Sensing of Environment, 83, 195–213.
Huete, A., Justice, C., and van Leeuwen, W. (1999). MODIS Vegetation Index (MOD 13):
Algorithm Theoretical Basis Document (Version 3), http://modis.gsfc.nasa.gov/data/
atbd/atbd_mod13.pdf.
Jackson, T. J. (2002). Remote sensing of soil moisture: Implications for groundwater recharge.
Hydrogeology Journal, 10(1), 40–51.
Jacobs, J., Mecikalski, J., and Paech, S. (2008). Satellite-based solar radiation, net radiation, and
potential and reference evapotranspiration estimates over Florida. Technical Report, Florida
Integrated Water Science Center, the United States Geological Survey (USGS), Orlando,
FL, USA.
Kite, G. W. and Droogers, P. (2000). Comparison evapotranspiration estimates from satellites,
hydrological models and field data. Journal of Hydrology, 229, 3–18.
Kogan, F. N. (1998). Global drought and flood watch from NOAA polar-orbiting satellites.
Advances in Space Research, 21(3), 411–414.
Koza, J. R. (1992). Genetic Programming: On the Programming of Computers by Means of
Natural Selection. MIT Press, Cambridge, MA, USA.
Kustas, W. P., Zhan, X., and Schmugge, T. J. (1998). Combining optical and microwave
remote sensing for mapping energy fluxes in a semiarid watershed. Remote Sensing of
Environment, 64(2), 116–131.
Makkeasorn, A., Chang, N. B., Beaman, M., Wyatt, C., and Slater, C. (2006). Soil moisture
prediction in a semi-arid reservoir watershed using RADARSAT satellite images and
genetic programming. Water Resources Research, 42, 1–15.
Merlin, O., Al Bitar, A., Walker, J. P., and Kerr, Y. (2010). An improved algorithm for disaggregating microwave-derived soil moisture based on red, near-infrared and thermalinfrared data. Remote Sensing of Environment, 114(10), 2305–2316.
Moran, M. S., Vidal, A., Troufleau, D., Qi, J., Clarke, T. R., Pinter, P. J., Mitchell, T. A., Inoue,
Y., and Neale, C. M. U. (1997). Combining multifrequency microwave and optical data
for crop management. Remote Sensing of Environment, 61(1), 96–109.
Nagler, P. L., Cleverly, J., and Glenn, E. (2005a). Predicting riparian evapotranspiration from
MODIS vegetation indices and meteorological data. Remote Sensing of Environment,
94(1), 17–30.
Nagler, P. L., Scott, R. L., and Westenburg, C. (2005b). Evapotranspiration on western US
rivers estimated using the enhanced vegetation index from MODIS and data from
eddy covariance and Bowen ratio flux towers. Remote Sensing of Environment, 97(3),
337–351.
Njoku, E. G. and Entekhabi, D. (1996). Passive microwave remote sensing of soil moisture.
Journal of Hydrology (Amsterdam), 184(1–2), 101–129.
O’Neill, P., Chauhan, N. S., and Jackson, T. J. (1996). Use of active and passive microwave
remote sensing for soil moisture estimation through corn. International Journal of
Remote Sensing, 17(10), 1851–1865.
Population Reference Bureau (PRB). (2007). World population highlights. Population Bulletin,
62(3), 1. ISSN 0032-468X, p1.
Roth, C. H., Malicki, M. A., and Plagge, R. (1992). Empirical evaluation of the relationship
between soil dielectric constant and volumetric water content as the basis for calibrating
soil moisture measurements by TDR. Journal of Soil Science, 43, 1–13.
Schuurmans, J. M., Troch, P. A., Veldhuizen, A. A., Bastiaanssen, W. G. M., and Bierkens,
M. F. P. (2003). Assimilation of remotely sensed latent heat fl ux in a distributed hydroAssimilation of remotely sensed latent heat flux in a distributed hydrological model. Advances in Water Resources, 26, 151–159.
Spectrum Technologies, Inc. (2004). Field Scout™ TDR 300 Soil Moisture Meter, User’s
Manual: catalog # 6430FS.
Multiscale Hydrologic Remote Sensing: Perspectives and Applications
Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., and Ferreira, L.G. (2002). Overview
of the radiometric and biophysical performance of the MODIS vegetation indices.
Remote Sensing of Environment, 83, 195–213.
Huete, A., Justice, C., and van Leeuwen, W. (1999). MODIS Vegetation Index (MOD 13):
Algorithm Theoretical Basis Document (Version 3), http://modis.gsfc.nasa.gov/data/
atbd/atbd_mod13.pdf.
Jackson, T. J. (2002). Remote sensing of soil moisture: Implications for groundwater recharge.
Hydrogeology Journal, 10(1), 40–51.
Jacobs, J., Mecikalski, J., and Paech, S. (2008). Satellite-based solar radiation, net radiation, and
potential and reference evapotranspiration estimates over Florida. Technical Report, Florida
Integrated Water Science Center, the United States Geological Survey (USGS), Orlando,
FL, USA.
Kite, G. W. and Droogers, P. (2000). Comparison evapotranspiration estimates from satellites,
hydrological models and field data. Journal of Hydrology, 229, 3–18.
Kogan, F. N. (1998). Global drought and flood watch from NOAA polar-orbiting satellites.
Advances in Space Research, 21(3), 411–414.
Koza, J. R. (1992). Genetic Programming: On the Programming of Computers by Means of
Natural Selection. MIT Press, Cambridge, MA, USA.
Kustas, W. P., Zhan, X., and Schmugge, T. J. (1998). Combining optical and microwave
remote sensing for mapping energy fluxes in a semiarid watershed. Remote Sensing of
Environment, 64(2), 116–131.
Makkeasorn, A., Chang, N. B., Beaman, M., Wyatt, C., and Slater, C. (2006). Soil moisture
prediction in a semi-arid reservoir watershed using RADARSAT satellite images and
genetic programming. Water Resources Research, 42, 1–15.
Merlin, O., Al Bitar, A., Walker, J. P., and Kerr, Y. (2010). An improved algorithm for disaggregating microwave-derived soil moisture based on red, near-infrared and thermalinfrared data. Remote Sensing of Environment, 114(10), 2305–2316.
Moran, M. S., Vidal, A., Troufleau, D., Qi, J., Clarke, T. R., Pinter, P. J., Mitchell, T. A., Inoue,
Y., and Neale, C. M. U. (1997). Combining multifrequency microwave and optical data
for crop management. Remote Sensing of Environment, 61(1), 96–109.
Nagler, P. L., Cleverly, J., and Glenn, E. (2005a). Predicting riparian evapotranspiration from
MODIS vegetation indices and meteorological data. Remote Sensing of Environment,
94(1), 17–30.
Nagler, P. L., Scott, R. L., and Westenburg, C. (2005b). Evapotranspiration on western US
rivers estimated using the enhanced vegetation index from MODIS and data from
eddy covariance and Bowen ratio flux towers. Remote Sensing of Environment, 97(3),
337–351.
Njoku, E. G. and Entekhabi, D. (1996). Passive microwave remote sensing of soil moisture.
Journal of Hydrology (Amsterdam), 184(1–2), 101–129.
O’Neill, P., Chauhan, N. S., and Jackson, T. J. (1996). Use of active and passive microwave
remote sensing for soil moisture estimation through corn. International Journal of
Remote Sensing, 17(10), 1851–1865.
Population Reference Bureau (PRB). (2007). World population highlights. Population Bulletin,
62(3), 1. ISSN 0032-468X, p1.
Roth, C. H., Malicki, M. A., and Plagge, R. (1992). Empirical evaluation of the relationship
between soil dielectric constant and volumetric water content as the basis for calibrating
soil moisture measurements by TDR. Journal of Soil Science, 43, 1–13.
Schuurmans, J. M., Troch, P. A., Veldhuizen, A. A., Bastiaanssen, W. G. M., and Bierkens,
M. F. P. (2003). Assimilation of remotely sensed latent heat fl ux in a distributed hydroAssimilation of remotely sensed latent heat flux in a distributed hydrological model. Advances in Water Resources, 26, 151–159.
Spectrum Technologies, Inc. (2004). Field Scout™ TDR 300 Soil Moisture Meter, User’s
Manual: catalog # 6430FS.