The use of results of ground-based test site spectrometric measurements for the calibration of satellite observations to estimate hydrological and hydrogeological security

1Kostyuchenko, Yu.V, 2Solovyov, DM, 3Yushchenko, MV, 4Dugin, SS, 4Kopachevsky, IM, 4Bilous, Yu.H, 4Artemenko, IG
1State institution «Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine», Kyiv, Ukraine
2State institution «Scientific Centre for Aerospace Research of the Earth Institute of Geological Science National Academy of Sciences of Ukraine», Kyiv; Marine Hydrophysical Institute Ukrainian National Academy of Sciences, Sevastopol
3State institution «Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Science of the National Academy of Sciences of Ukraine», Kyiv, Ukraine
4State institution «Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Science of the National Academy of Sciences of Ukraine», Kyiv, Ukraine
Kosm. nauka tehnol. 2012, 18 ;(6):14–21
https://doi.org/10.15407/knit2012.06.014
Section: Study of the Earth from Space
Publication Language: Ukrainian
Abstract: 
We propose some theoretical and methodological principles for intercalibration of satellite data and in-field spectrometric measurements in the framework of water balance and hydrological and hydro-geological security assessment. On the basis of the analysis of ground test sites spectrometric data of FieldSpec ® 3 FR, the statistical regularities of spatial-temporal distribution of spectral reflectance characteristics are determined for the spectral indices used in this study. An algorithm is proposed to calculate spectral indices using the correlation analysis. The general form of calibration patterns for further verification of satellite observations is given
Keywords: calibration of satellite data, spectral indices, water balance
References: 
1.  Acarreta J. R., Stammes P. Calibration comparison between SCIAMACHY and MERIS onboard ENVISAT.  IEEE Geosci. Remote Sens. Lett., 2, 31—35 (2005).
https://doi.org/10.1109/LGRS.2004.838348
2.  ASD FieldSpec®3 FR User Manual,  96 p. (ASD Document, Boulder, 2007).
3.  Castelli F., Entekhabi D., Caporali E. Estimation of surface heat flux and an index of soil moisture using adjointstate surface energy balance.  Water Resour. Res., 35, 3115—3125 (1999).
https://doi.org/10.1029/1999WR900140 
4.  Choudhury B. J., Ahmed N. U., Idso S. B., et al. Relations between evaporation coefficients and vegetation indices studied by model simulations. Remote Sens. Environ., 50, 1—17 (1994).
https://doi.org/10.1016/0034-4257(94)90090-6
5. Cowpertwait P. S. P. A generalized spatial-temporal model of rainfall based on a clustered point process.  Proc. Roy. Soc. London A., 450, 163—175 (1995).
https://doi.org/10.1098/rspa.1995.0077
6. Cox D. R., Hinkley D. V. Theoretical Statistics, 285 p. (Chapman & Hall, NY, 1974).
https://doi.org/10.1007/978-1-4899-2887-0
7. Fowler H. J., Kilsby C. G., O’Connell P. E. Modeling the impacts of climatic change and variability on the reliability, resilience and vulnerability of a water resource system.  Water Resour. Res., 39, P. 1222 (2003); doi: 1029-2002WR001778
8. Gao B. C. Normalized difference water index for remote sensing of vegetation liquid water from space.  Proc. SPIE, 2480, 225—236 (1995).
https://doi.org/10.1117/12.210877
9. Gupta H. V., Bastidas L. A., Sorooshian S., et al. Parameter estimation of a land surface scheme using multicriteria methods. J. Geophys. Res., 104, 19,491— 19,503 (1999).
https://doi.org/10.1029/1999JD900154
10. Jackson R. D., Slater P. N., Pinter P. J. Discrimination of growth and water stress in wheat by various vegetation indices through clear and turbid atmospheres. Remote Sens. Environ., 15, 187—208 (1983).
https://doi.org/10.1016/0034-4257(83)90039-1
11. Kostyuchenko Yu. V., Kopachevsky I. M., Solovyov D. M., et al. Way to reduce the uncertainties on ecological consequences assessment of technological disasters using satellite observations.  Proc. of the 4th International Workshop on Reliable Engineering Computing «Robust Design –Coping with Hazards, Risk and Uncertainty», March 3—5, 2010, Singapore, 765—776 (National University of Singapore, Singapore, 2010).

12. Peters-Lidard C. D., Zion M. S., Wood E. F. A soil — vegetation — atmosphere transfer scheme for modeling spatially variable water and energy balance processes.  J. Geophys. Res., 102, 4303—4324 (1997).
https://doi.org/10.1029/96JD02948