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The Contributions of High Resolution Multispectral Imagery to Precision Agriculture: A Case Study of Soil Moisture Estimations

Leila Hassan-Esfahani,Alfonso F. Torres‐Rua,Austin M. Jensen,Mac McKee-2014-01-01-Digital Commons - USU (Utah State University)
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TL;DRAbstract

Airborne and Landsat remote sensing are promising technologies for measuring the response of agricultural crops to variations in several agricultural inputs and environmental conditions. Of particular significance to precision agriculture is surface soil moisture, a key component of the soil water balance, which addresses water and energy exchanges at the surface/atmosphere interface and affects vegetation health. Its estimation using the spectral reflectance of agricultural fields could be of value to agricultural management decisions. While top soil moisture can be estimated using radiometric information from aircraft or satellites and data mining techniques, comparison of results from two different aerial platforms might be complicated because of the differences in spatial scales (high resolution of approximately 0.15m versus coarser resolutions of 30m). This paper presents a combined modeling and scale-based approach to evaluate the impact of spatial scaling in the estimation of su

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Airborne and Landsat remote sensing are promising technologies for measuring the response of agricultural crops to variations in several agricultural inputs and environmental conditions. Of particular significance to precision agriculture is surface soil moisture, a key component of the soil water balance, which addresses water and energy exchanges at the surface/atmosphere interface and affects vegetation health. Its estimation using the spectral reflectance of agricultural fields could be of value to agricultural management decisions. While top soil moisture can be estimated using radiometric information from aircraft or satellites and data mining techniques, comparison of results from two different aerial platforms might be complicated because of the differences in spatial scales (high resolution of approximately 0.15m versus coarser resolutions of 30m). This paper presents a combined modeling and scale-based approach to evaluate the impact of spatial scaling in the estimation of su

Keywords

Multispectral imageRemote sensingPrecision agricultureEnvironmental scienceMoistureWater contentResolution (logic)Agriculture

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