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

作者: C. Jeganathan , N.A.S. Hamm , S. Mukherjee , P.M. Atkinson , P.L.N. Raju

DOI: 10.1016/J.JAG.2010.11.001

关键词:

摘要: Fine spatial resolution (e.g., <300 m) thermal data are needed regularly to characterise the temporal pattern of surface moisture status, water stress, and forecast agriculture drought famine. However, current optical sensors do not provide frequent at a fine resolution. The TsHARP model provides possibility generate from coarse (≥1 km) on basis an anticipated inverse linear relationship between normalised difference vegetation index (NDVI) land temperature study utilised over mixed agricultural landscape in northern part India. Five variants were analysed, including original model, for their efficiency. Those five global (original); resolution-adjusted model; piecewise regression stratified local model. models first evaluated using Advanced Space-borne Thermal Emission Reflection Radiometer (ASTER) (90 aggregated following resolutions: 180 m, 270 450 630 810 m 990 m. Although sharpening was undertaken resolutions 90 root mean square error (RMSE) <2 K could, average, be achieved only 990–270 ASTER data. RMSE sharpened images data, global, regression, stratification 1.91, 1.89, 1.96, 1.70 K, respectively. yielded higher accuracy, applied sharpen MODIS (1 target resolutions. Aggregated considered as reference respective assess prediction results predicted image 250 3.08, 2.92 1.98 consistently led more accurate predictions by comparison other variants.

参考文章(58)
Paul J. Curran, Peter M. Atkinson, Issues of scale and optimal pixel size Springer Netherlands. pp. 115- 133 ,(1999) , 10.1007/0-306-47647-9_7
Geoffrey H. Ball, David J. Hall, ISODATA, A NOVEL METHOD OF DATA ANALYSIS AND PATTERN CLASSIFICATION Stanford Research Institute. ,(1965)
Michael F. Goodchild Dale A. Quattrochi, None, Scale in remote sensing and GIS CRC Lewis. ,(1997)
W. J. Carper, The use of intensity-hue-saturation transformations for merging SPOT panchromatic and multispectral image data Photogrammetric Engineering and Remote Sensing. ,vol. 56, pp. 457- 467 ,(1990)
Anand K. Inamdar, Andrew French, Disaggregation of GOES land surface temperatures using surface emissivity Geophysical Research Letters. ,vol. 36, ,(2009) , 10.1029/2008GL036544
M ANDERSON, J NORMAN, W KUSTAS, R HOUBORG, P STARKS, N AGAM, A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales Remote Sensing of Environment. ,vol. 112, pp. 4227- 4241 ,(2008) , 10.1016/J.RSE.2008.07.009
R. S. Defries, A. S. Belward, Global and regional land cover characterization from satellite data: an introduction to the Special Issue International Journal of Remote Sensing. ,vol. 21, pp. 1083- 1092 ,(2000) , 10.1080/014311600210083
A. Stein, N. A. S. Hamm, Qinghua Ye, Handling uncertainties in image mining for remote sensing studies International Journal of Remote Sensing. ,vol. 30, pp. 5365- 5382 ,(2009) , 10.1080/01431160903130895
Umamaheshwaran Rajasekar, Qihao Weng, Urban heat island monitoring and analysis using a non-parametric model: A case study of Indianapolis Isprs Journal of Photogrammetry and Remote Sensing. ,vol. 64, pp. 86- 96 ,(2009) , 10.1016/J.ISPRSJPRS.2008.05.002