| dc.contributor.author | Mack, Talon Clancy | |
| dc.description.abstract | Accurate measurements of soil moisture in a timely manner are necessary in making critical management decisions, but it is often very difficult to obtain. Even though soil moisture can be measured on the ground using various methods, or estimated via satellite imagery, soil moisture conditions at a field scale can be more beneficial. Since Unmanned Aircraft System (UAS) technology has become an effective tool in many different ways for producers and researchers, the spatial and temporal gaps between the ground and the satellite approaches can be fulfilled with the use of UAS. In this study, multi-spectral images were collected over an agricultural field in the Red River Valley from an UAS platform. Using this data, the soil moisture content was calculated, and a soil moisture map was developed. The remotely sensed soil moisture was then compared to the in-situ field moisture measurements to gage the soil moisture mapping accuracy. | en_US |
| dc.publisher | North Dakota State University | en_US |
| dc.rights | NDSU Policy 190.6.2 | |
| dc.title | Using UAS Images to Remotely Estimate Soil Moisture Content in the Red River Valley | en_US |
| dc.type | Thesis | en_US |
| dc.date.accessioned | 2022-06-10T18:52:59Z | |
| dc.date.available | 2022-06-10T18:52:59Z | |
| dc.date.issued | 2021 | |
| dc.identifier.uri | https://hdl.handle.net/10365/32739 | |
| dc.subject | mapping | en_US |
| dc.subject | multispectral | en_US |
| dc.subject | red river valley | en_US |
| dc.subject | remote sensing | en_US |
| dc.subject | soil moisture | en_US |
| dc.subject | uas | en_US |
| dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | |
| ndsu.degree | Master of Science (MS) | en_US |
| ndsu.college | Agriculture, Food Systems and Natural Resources | en_US |
| ndsu.department | Agribusiness and Applied Economics | en_US |
| ndsu.program | Agricultural and Biosystems Engineering | en_US |
| ndsu.advisor | Jia, Xinhua | |
