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Article

Identification of Infiltration Features and Hydraulic Properties of Soils Based on Crop Water Stress Derived from Remotely Sensed Data

1
Faculty of Agriculture, University of South Bohemia in České Budějovice, Studentská 1668, 370 05 České Budějovice, Czech Republic
2
Research Institute for Soil and Water Conservation, Žabovřeská 250, Praha 5–Zbraslav, 156 27 Prague, Czech Republic
3
Crop Research Institute, Drnovská 507/73, Praha 6–Ruzyně, 161 06 Prague, Czech Republic
*
Author to whom correspondence should be addressed.
Academic Editors: Carlos Antonio Da Silva Junior and Luciano Shozo Shiratsuchi
Remote Sens. 2021, 13(20), 4127; https://doi.org/10.3390/rs13204127
Received: 31 August 2021 / Revised: 4 October 2021 / Accepted: 12 October 2021 / Published: 15 October 2021
Knowledge of the spatial variability of soil hydraulic properties is important for many reasons, e.g., for soil erosion protection, or the assessment of surface and subsurface runoff. Nowadays, precision agriculture is gaining importance for which knowledge of soil hydraulic properties is essential, especially when it comes to the optimization of nitrogen fertilization. The present work aimed to exploit the ability of vegetation cover to identify the spatial variability of soil hydraulic properties through the expression of water stress. The assessment of the spatial distribution of saturated soil hydraulic conductivity (Ks) and field water capacity (FWC) was based on a combination of ground-based measurements and thermal and hyperspectral airborne imaging data. The crop water stress index (CWSI) was used as an indicator of crop water stress to assess the hydraulic properties of the soil. Supplementary vegetation indices were used. The support vector regression (SVR) method was used to estimate soil hydraulic properties from aerial data. Data analysis showed that the approach estimated Ks with good results (R2 = 0.77) for stands with developed crop water stress. The regression coefficient values for estimation of FWC for topsoil (0–0.3 m) ranged from R2 = 0.38 to R2 = 0.99. The differences within the study sites of the FWC estimations were higher for the subsoil layer (0.3–0.6 m). R2 values ranged from 0.12 to 0.99. Several factors affect the quality of the soil hydraulic features estimation, such as crop water stress development, condition of the crops, period and time of imaging, etc. The above approach is useful for practical applications for its relative simplicity, especially in precision agriculture. View Full-Text
Keywords: soil infiltration; field water capacity; crop water stress; machine learning; aerial remote sensing; precision agriculture soil infiltration; field water capacity; crop water stress; machine learning; aerial remote sensing; precision agriculture
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MDPI and ACS Style

Brom, J.; Duffková, R.; Haberle, J.; Zajíček, A.; Nedbal, V.; Bernasová, T.; Křováková, K. Identification of Infiltration Features and Hydraulic Properties of Soils Based on Crop Water Stress Derived from Remotely Sensed Data. Remote Sens. 2021, 13, 4127. https://doi.org/10.3390/rs13204127

AMA Style

Brom J, Duffková R, Haberle J, Zajíček A, Nedbal V, Bernasová T, Křováková K. Identification of Infiltration Features and Hydraulic Properties of Soils Based on Crop Water Stress Derived from Remotely Sensed Data. Remote Sensing. 2021; 13(20):4127. https://doi.org/10.3390/rs13204127

Chicago/Turabian Style

Brom, Jakub, Renata Duffková, Jan Haberle, Antonín Zajíček, Václav Nedbal, Tereza Bernasová, and Kateřina Křováková. 2021. "Identification of Infiltration Features and Hydraulic Properties of Soils Based on Crop Water Stress Derived from Remotely Sensed Data" Remote Sensing 13, no. 20: 4127. https://doi.org/10.3390/rs13204127

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