含水量
光谱辐射计
环境科学
RGB颜色模型
遥感
高光谱成像
土壤科学
水分
土工试验
土壤水分
反射率
地质学
地理
计算机科学
气象学
人工智能
物理
光学
岩土工程
作者
Lihua Zheng,Minzan Li,Jianying Sun,Xijie Zhang,Zhao Pen
摘要
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.
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