Prediction of Soil Moisture Content and Soil Salt Concentration from Hyperspectral Laboratory and Field Data

Remote Sensing

Chi Xu¹  Wenzhi Zeng¹  Jiesheng Huang¹  Jingwei Wu¹  Willem J.D. van Leeuwen³  Nicolas Baghdadi² 

[1] State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China;;State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, ChinaSchool of Natural Resources and the Environment, University of Arizona, Tucson, AZ 85721, USA;

关键词: waveband selection;    salinity;    water;    texture;    spectroscopy;    modeling;    stratifying;   

DOI  :  10.3390/rs8010042

来源: mdpi

【 摘 要 】

This research examines the simultaneous retrieval of surface soil moisture and salt concentrations using hyperspectral reflectance data in an arid environment. We conducted laboratory and outdoor field experiments in which we examined three key soil variables: soil moisture, salt and texture (silty loam, clay and silty clay). The soil moisture content models for multiple textures (M_SMC models) were based on selected hyperspectral reflectance data located around 1460, 1900 and 2010 nm and resulted in R² values higher than 0.933. Meanwhile, the soil salt concentrations were also accurately (R² > 0.748) modeled (M_SSC models) based on wavebands located at 540, 1740, 2010 and 2350 nm. When the different texture samples were mixed (SL + C + SC models), soil moisture was still accurately retrieved (R² = 0.937) but the soil salt not as well (R² = 0.47). After stratifying the samples by retrieved soil moisture levels, the R² of calibrated M_SSC_SMC models for soil salt concentrations improved to 0.951. This two-step method also showed applicability for analyzing soil-salt samples in the field. The M_SSC_SMC models resulted in R² values equal to 0.912 when moisture is lower than 0.15, and R² values equal to 0.481 when soil moisture is between 0.15 and 0.2.

【 授权许可】

CC BY   
© 2016 by the authors; licensee MDPI, Basel, Switzerland.