Utility of thermal sharpening over Texas high plains irrigated agricultural fields

Journal of Geophysical Research Atmospheres

Volumn 112, Issue 19, 2007, Pages

  Agam, Nurit ^a   Kustas, William P ^a   Anderson, Martha C ^a   Li, Fuqin ^a   Colaizzi, Paul D ^b  

^a AGRICULTURAL RESEARCH SERVICE   (United States)

^b Agriculture Research Service   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGING TECHNIQUES; IRRIGATION; TEMPERATURE DISTRIBUTION; VEGETATION; WATER MANAGEMENT;

ACCURACY ASSESSMENT; ALGORITHM; BOUNDARY CONDITION; CROP PRODUCTION; ESTIMATION METHOD; IMAGE RESOLUTION; IRRIGATION; LANDSAT; MODIS; SATELLITE IMAGERY; SPATIOTEMPORAL ANALYSIS; VEGETATION COVER; WATER MANAGEMENT; WATER USE;

EID: 36849035024     PISSN: 01480227     EISSN: None     Source Type: Journal    
DOI: 10.1029/2007JD008407     Document Type: Article

References (20)

1. Abrams, M. (2000), The Advanced Spacebome Thermal Emission and Reflection Radiometer (ASTER): Data products for the high spatial resolution imager on NASA's Terra platform, Int. J. Remote Sens., 21, 847-859.
2. Agam, N., W. P. Kustas, M. C. Anderson, F. Li, and C. M. U. Neale (2007), A vegetation index based technique for spatial sharpening of thermal imagery, Remote Sens. Environ., 107, 545-558.
3. 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, 195-216.
4. Anderson, M. C., C. M. U. Neale, F. Li, J. M. Norman, W. P. Kustas, H. Jayanthi, and J. 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, 447-464.
5. Anderson, M. C., J. M. Norman, J. R. Mecikalski, R. D. Tom, W. P. Kustas, and J. B. Basara (2004b), A multi-scale remote sensing model for disaggregating regional fluxes to micrometeorological scales, J. Hydrometeorol., 5, 343-363.
6. Anderson, M. C., J. M. Norman, J. R. Mecikalski, J. A. Otkin, and W. P. Kustas (2007), A climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing: I. Model formulation, J. Geophys. Res., 112, D10117, doi:10.1029/2006JD007506.
7. Becker, F., and Z.-L. Li (1990), Temperature-independent spectral indices in thermal infrared bands, Remote Sens. Environ., 32, 17-33.
8. Berk, A., L. S. Bernstein, G. P. Anderson, P. K. Acharya, D. C. Robertson, J. H. Chetwynd, and S. M. Adler-Golden (1998), MODTRAN cloud and multiple scattering upgrades with application to AVIRIS, Remote Sens. Environ., 65, 367-375.
9. Choudhury, B. J., N. U. Ahmed, S. B. Idso, R. J. Reginato, and C. S. T. Daughtry (1994), Relations between evaporation coefficients and vegetation indices studied by model simulations, Remote Sens. Environ., 50, 1-17.
10. Colaizzi, P. D., P. H. Gowda, T. H. Marek, and D. O. Polter (2006), Reducing Ogallala withdrawals by changing cropping and irrigation practices in the Texas High Plains, paper presented at Ground Water and Surface Water Under Stress: Competition, Interaction, Solutions, Boise, Id., U. S. Comm. on Irrigation and Drainage, Denver, Colo.
11. De Cola, L. (1997), Multiresolution covariation among Landsat and AVHRR vegetation indices, in Scale in Remote Sensing and GIS, edited by D. A. Quattrochi and M. F. Goodchild, pp. 73-91, CRC Press, Boca Raton, Fla.
12. Friedl, M. A., and F. W. Davis (1994), Sources of validation in radiometric surface temperature over a tallgrass prairie, Remote Sens. Environ., 48, 1-17.
13. Friedl, M. A., F. W. Davis, J. Michaelsen, and M. A. Moritz (1995), Scaling and uncertainty in the relationship between NDVI and land surface biophysical variables: An analysis using a scene simulation model and data from FIFE, Remote Sens. Environ., 54, 233-246.
14. Hall, F. G., K. F. Huemmrich, S. J. Goetz, P. J. Sellers, and J. E. Nickerson (1992), Satellite remote sensing of surface energy balance: Success, failures and unresolved issues in FIFE, J. Geophys. Res., 97, 19,061-19,089.
15. Kustas, W. P., J. M. Norman, M. C. Anderson, and A. N. French (2003), Estimating subpixel surface temperatures and energy fluxes from the vegetation index-radiometric temperature relationship, Remote Sens. Environ., 85, 429-440.
16. Li, F., T. J. Jackson, W. P. Kustas, T. J. Schimugge, A. N. French, M. Cosh, and R. Bindlish (2004), Deriving land surface temperature from Landsat 5 and 7 during SMEX02/SMACEX, Remote Sens. Envviron., 92, 521-534.
17. Norman, J. M., and F. Becker (1995), Terminology in thermal infrared remote sensing of natural surfaces, Agric. For Meteorol, 77, 153-166.
18. 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 resolutions, Water Resour Res., 39(8), 1221, doi:10.1029/ 2002WR001775.
19. Sobrino, J. A., N. Raissouni, and Z.-L. Li (2001), A comparative study of land surface emissivity retrieval from NOAA data, Remote Sens. Environ., 75, 256-266.
20. Willmoft, C. J., and K. Matsuura (2005), Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance, Clim. Res., 30, 79-82.