UDC: 
DOI: 
10.22389/0016-7126-2022-986-8-33-38
1 Iskenderzadeh E.B.
2 Asadov H.H.
3 Aliyeva A.D.
4 Litvinov N.Yu.
Year: 
№: 
986
Pages: 
33-38

Azerbaujan National Aerocosmic Agency

1, 
2, 
3, 

Center of Geodesy, Cartography and SDI

4, 
Abstract:
The article deals with development of new spectral method for determination of spectral indices used to estimate the soil moisture content. The main disadvantage of such indices is that they use spectral absorption lines of water vapor. Consequently, using them requires adequate compensation of the atmospheric influence. The solution of this issue was carried out on the basis of the following provisions: (a) it is assumed that a model expression of the reflection spectrum dependence on the moisture content in the soil is known; (b) there are experimentally removed curves of the specified dependence; (c) the function of the experimentally measured soil reflection value dependence on the degree of soil moisture is introduced; (d) the search for the optimal type of the introduced function is carried out at which the square of the difference between the experimentally measured value of reflection and the known model function reaches the minimum. In this case, the specified search is carried out by the variational optimization method, subject to the introduction of some restrictive condition on the desired function, using continuous discrete sums form recording; (e) equating the calculated optimal function with the experimentally obtained reflection value at a specific wavelength, the water content of the soil is calculated. At the same time, permanent using of wavelength with minimal water content is recommended. The described experimental researches confirmed effectivity of the suggested method.
References: 
1.   Jel’sgol’c L. E. Differencial’nye uravnenija i variacionnoe ischislenie. Moscow: Nauka, 1974, 432 p.
2.   Ben-Dor E., Patkin K., Banin A., Karnieli A. (2002) Mapping of several soil properties using DAIS-7915 hyperspectral scanner data – A case study over clayey soils in Israel. International Journal of Remote Sensing, no. 23, pp. 1043–1062.
3.   Brocca L., Morbidelli R., Melone F., Moramarco T. (2007) Soil moisture spatial variability in experimental areas of central Italy. Journal of Hydrology, no. 333, pp. 356–373.
4.   Bryant R., Thoma D., Moran S., Holifield C., Goodrich D., Keefer T., Paige G., Williams D., Skirvin S. (2003) Evaluation of hyperspectral, infrared temperature and radar measurements for monitoring surface soil moisture. In Proceedings of the First Interagency Conference on research in the Watersheds. Benson, Arizona. pp. 528–533.
5.   Fabre S., Briottet X., Lesaignoux A. (2015) Estimation of soil moisture content from the spectral reflectance of bar soils in the 0,4–2,5 μm Domain. Sensors, no. 15, pp. 3262–3281. DOI: 10.3390/s150203262.
6.   Haurbrock S., Chabrillat S., Lemmnitz C., Kaufmann H. (2008) Surface soil moisture quantification models from reflectance data under field conditions. International Journal of Remote Sensing, no. 29 (1), pp. 3–29.
7.   Khanna S., Palacios-Orueta A., Whiting M. L., Ustin S. L., Riano D., Litago J. (2007) Development of angle indexes for soil moisture estimation, dry matter detection and land-cover discrimination. Remote Sensing of Environment, no. 109, pp. 154–165.
8.   Lesaignoux A., Fabre S., Briottet X. (2013) Influence of soil moisture content on spectral reflectance of bare soils in the 0,4–14 μm domain. International Journal of Remote Sensing, no. 34, pp. 2268–2285.
9.   Liu W., Baret F., Gu X., Tong Q., Zheng L., Zhang B. (2003) Evaluation of methods for soil surface moisture estimation from reflectance data. International Journal of Remote Sensing, no. 24, pp. 2069–2083.
10.   Lobell D., Asner G. (2002) Moisture effects on soil reflectance. Soil Science Society of America Journal, no. 66, pp. 722–727.
11.   Sanchez F. (2003) Soil moisture estimation by hyperspectral remote sensing in the Doode Bemde area in the valley of the Dijle River. Masters Thesis, Universiteit Gent. Flanders, Belgium.
12.   Whiting M. L., Li L., Ustin S. L. (2003) Predicting water content using Gaussian model on soil spectra. Remote Sensing of Environment, no. 89, pp. 535–552.
Citation:
Iskenderzadeh E.B., 
Asadov H.H., 
Aliyeva A.D., 
Litvinov N.Yu., 
(2022) A spectral method for determining soil moisture content. Geodesy and cartography = Geodezia i Kartografia, 83(8), pp. 33-38. (In Russian). DOI: 10.22389/0016-7126-2022-986-8-33-38