Evaluating a thermal image sharpening model over a mixed agricultural landscape in India

@article{Jeganathan2011EvaluatingAT,
  title={Evaluating a thermal image sharpening model over a mixed agricultural landscape in India},
  author={C. Jeganathan and N. A. S. Hamm and S. Mukherjee and Peter M. Atkinson and P. L. N. Raju and Vinay K. Dadhwal},
  journal={Int. J. Applied Earth Observation and Geoinformation},
  year={2011},
  volume={13},
  pages={178-191}
}
Fine spatial resolution (e.g., <300 m) thermal data are needed regularly to characterise the temporal pattern of surface moisture status, water stress, and to forecast agriculture drought and famine. However, current optical sensors do not provide frequent thermal data at a fine spatial resolution. The TsHARP model provides a possibility to generate fine spatial resolution thermal data from coarse spatial resolution (≥1 km) data on the basis of an anticipated inverse linear relationship between… CONTINUE READING
Highly Cited
This paper has 42 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 26 extracted citations

Regression-Kriging Technique to Downscale Satellite-Derived Land Surface Temperature in Heterogeneous Agricultural Landscape

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing • 2015
View 7 Excerpts
Highly Influenced

References

Publications referenced by this paper.
Showing 1-10 of 55 references

A simple interpretation of the surface temperature / vegetation index space for assessment of surface moisture status

Inge Sandholta, Kjeld Rasmussena, Jens Andersenb
2001
View 5 Excerpts
Highly Influenced

Disaggregation of GOES land surface temperatures using surface emissivity

A. K. namdar, A. French
Geophysical Research Letters • 2009

Handling uncertainties in image mining for remote sensing studies

A. Stein, N.A.S. Hamm, Q. H. Ye
International Journal of Remote Sensing • 2009
View 2 Excerpts

Similar Papers

Loading similar papers…