Estimating soil moisture based on image processing technologies

Lihua Zheng; Minzan Li; Jianying Sun; Xijie Zhang; Peng Zhao

doi:10.1117/12.614684

16 September 2005 Estimating soil moisture based on image processing technologies

Lihua Zheng, Minzan Li, Jianying Sun, Xijie Zhang, Peng Zhao

Proceedings Volume 5909, Applications of Digital Image Processing XXVIII; 59091R (2005) https://doi.org/10.1117/12.614684
Event: Optics and Photonics 2005, 2005, San Diego, California, United States

Abstract

Soil moisture is a critical factor to crop growth. Due to the facts of drought and less rain in northern China, it is necessary to introduce water controlled irrigating. Therefore, estimating soil moisture distribution rapidly and accurately is very important for decision making of water saving irrigating. This study took a farmland in Beijing as the experiment field. The aerial image at each experimental spot was taken from a balloon at the height of 100m above the land surface, the hyperspectral data of each test site was measured by a handheld spectroradiometer in the meantime, and the soil moisture of each sample was obtained in laboratory. With the obtained aerial images of the experiment field, the characteristics of each image were calculated by image processing technologies. And then the correlation analysis between soil moisture and each image characteristics was executed. Firstly, the coefficients of correlation between soil moisture and RGB values, as well as between soil moisture and HSV values were calculated respectively, and corresponding estimation models were established with R² of 0.887 and 0.706 respectively. Secondly, using the combination of RGB and HSV values, another estimation model was established, and its R² reached to 0.900. Finally, using the combination of the RGB values, HSV values and spectral reflectance data at 835 nm, a multiple linear regression model was also explored, which R² reached to 0.905. The result showed that the estimation of soil moisture content by using aerial images and hyperspectral data was rapid and accurate. Further more, high resolution image can be obtained conveniently now, thus it should be more practicable for forecasting the soil moisture accurately and timely by image processing technologies.

Citation Download Citation

Lihua Zheng, Minzan Li, Jianying Sun, Xijie Zhang, and Peng Zhao "Estimating soil moisture based on image processing technologies", Proc. SPIE 5909, Applications of Digital Image Processing XXVIII, 59091R (16 September 2005); https://doi.org/10.1117/12.614684

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