Emerging and Innovative Technologies

Oral

397397 - Soil Moisture Monitoring at Field Scales Using UAS: the Advancements and Challenges 

Tuesday, June 5
10:30 PM - 12:00 PM
Location: Lakeshore C
Co-Authors: Yeo Lim, Grand Forks, ND – University of North Dakota

Surface soil moisture content is one of the most important parameters related to the hydrologic cycle. Current satellite-based remote sensing technology has been shown useful in monitoring soil moisture content to assist in the prediction of floods, droughts ,and weather. However, satellite data for soil moisture has limitations in characterization at local scales, e.g. a spatial resolution of the typical size of agricultural fields, due to the inherent large scales setup. Current in-situ soil moisture measurements, while accurate, present a variety of limited capabilities.  Current soil moisture data retrieval methods require expensive equipment, are time consuming, have difficulties covering large areas in a brief time, and are limited to areas that are easily accessible. The usage of unmanned aerial vehicles to accurately assess surface soil moisture content offers numerous benefits including more accurate assessments over geographical regions, more economic and timely data collection, higher resolution images, and allows data collection to occur in otherwise difficult locations. This paper aims to utilize airborne spectral
data collected by an unmanned aerial system and explore correlations between the surface soil moisture, energy fluxes and emission spectra, with an overall objective to create a model to accurately represent surface soil moisture content from thermal data collection. Some of the challenges are model and algorithm calibration, correction of errors caused by sensors, and integrating data collected at a small scale to space-borne data. Further research will include training an artificial neural network to examine potential relationships between heat and energy fluxes at the surface and how they interact with the energy and water budget.

Daniel D. Fife

University of North Dakota

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397397 - Soil Moisture Monitoring at Field Scales Using UAS: the Advancements and Challenges 



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