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Remote Sensing of Soil Moisture in Vineyards Using Airborne and Ground-Based Thermal Inertia Data
AbstractThermal remote sensing of soil moisture in vineyards is a challenge. The grass-covered soil, in addition to a standing grape canopy, create complex patterns of heating and cooling and increase the surface temperature variability between vine rows. In this study, we evaluate the strength of relationships between soil moisture, mechanical resistance and thermal inertia calculated from the drop of surface temperature during a clear sky night over a vineyard in the Niagara region. We utilized data from two sensors, an airborne thermal camera (height ≈ 500 m a.g.l.) and a handheld thermal gun (height ≈ 1 m a.g.l.), to explore the effects of different field of views and the high inter-row temperature variability. Spatial patterns of soil moisture correlated more with estimated thermal inertia than with surface temperature recorded at sunrise or sunset. Despite the coarse resolution of airborne thermal inertia images, it performed better than estimates from the handheld thermal gun. Between-row variation was further analyzed using a linear mixed-effects model. Despite the limited spatial variability of soil properties within a single vineyard, the magnitudes of the model coefficients for soil moisture and mechanical resistance are encouraging indicators of the utility of thermal inertia in vineyard management.
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Soliman, A.; Heck, R.J.; Brenning, A.; Brown, R.; Miller, S. Remote Sensing of Soil Moisture in Vineyards Using Airborne and Ground-Based Thermal Inertia Data. Remote Sens. 2013, 5, 3729-3748.View more citation formats
Soliman A, Heck RJ, Brenning A, Brown R, Miller S. Remote Sensing of Soil Moisture in Vineyards Using Airborne and Ground-Based Thermal Inertia Data. Remote Sensing. 2013; 5(8):3729-3748.Chicago/Turabian Style
Soliman, Aiman; Heck, Richard J.; Brenning, Alexander; Brown, Ralph; Miller, Stephen. 2013. "Remote Sensing of Soil Moisture in Vineyards Using Airborne and Ground-Based Thermal Inertia Data." Remote Sens. 5, no. 8: 3729-3748.