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Assessing the Performance of Multispectral Sensors Mounted on Unmanned Aerial Vehicle for the Prediction of Soil Organic Carbon Levels at Field-Scale

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dc.contributor.advisor Berg, Aaron
dc.contributor.author March, Michael
dc.date.accessioned 2020-01-06T15:35:23Z
dc.date.copyright 2019-12
dc.date.created 2019-12-11
dc.date.issued 2020-01-06
dc.identifier.uri http://hdl.handle.net/10214/17716
dc.description.abstract The quantification of soil organic carbon (SOC) is critical for sustainable agricultural production. Conventional field measurements for assessing SOC content are time-consuming, costly and require large soil sampling efforts. The remote monitoring of SOC using unmanned aerial vehicles (UAVs) possesses the capability to be faster and more economically advantageous when compared to conventional soil sampling methods. This research sought to examine the potential of UAV-mounted multispectral (400-800nm) sensors for SOC prediction at the sub-field scale. To do so, UAV-based imagery was acquired over agricultural fields under bare soil conditions. A total of 806 georeferenced soil samples were collected at 20m intervals for each study site. We used multivariate regression analysis to assess the relationship between SOC and reflectance. The R2 and RMSE were calculated between estimated and observed SOC. Laboratory and UAV reflectance were combined to explore the potential of transferrable models that could estimate SOC across various platforms. en_US
dc.language.iso en en_US
dc.title Assessing the Performance of Multispectral Sensors Mounted on Unmanned Aerial Vehicle for the Prediction of Soil Organic Carbon Levels at Field-Scale en_US
dc.type Thesis en_US
dc.degree.programme Geography en_US
dc.degree.name Master of Science en_US
dc.degree.department Department of Geography, Environment and Geomatics en_US
dc.description.embargo 2020-12-11
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