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Comparison of Two Prediction Models for Surface Soil Moisture Measurement Using Near-infrared Sensor

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  131596930,  2013 Kansas City, Missouri, July 21 - July 24, 2013. (doi: @2013
Authors:   Zhe Yin, Tingwu Lei, Zhanpeng Chen, Qinghong Yan, Yuequn Dong
Keywords:   Near infrared; Soil moisture; Reflectance; Relative absorption depth;

Abstract. Soil moisture is an important parameter in agricultural production, water resource conservation and soil erosion modeling. An approach to estimate surface soil moisture from reflection data of Near-infrared sensor in the wavelength of 1940nm and 1800nm is presented. The linear model and non-linear model for soil moisture content estimation from relative reflectance of Near-infrared sensors were discussed respectively. The prediction results of the models were compared. Reflection measurements were made in the laboratory with black soil samples. The results showed the relative absorption depth increased and relative reflectance decreased as soil water increased. Independent data sets were used to validate the two models. The prediction precision as indicated by the root mean squared error (RMSE) of the non-linear model was2.47%, higher accurate than the linear model with RMSE of 4.75%. But the Non-linear model did not well predict the high moisture contents. This method can be used to predict the soil moisture, because those two models had high prediction accuracy.

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