Multi-Temporal UAV Images and GeoDatabase Used to Estimate Temporal and Spatial Soil Moisture Content

We used small unmanned aerial vehicle (UAV) with optical digital camera to detect a land movement and to extract soil parameters. Using multi-temporal images in Garrard County, Kentucky, we detected land movement on three pairs of images that were captured one month apart. The multi-temporal images and the result of the movement analysis are available in folders. In addition, vertical displacement analysis is carried out using Differential Interferometry technique (DinSAR) to a pair of Synthetic Aperture Radar (SAR) images. Soil moisture data was estimated using linear regression machine learning model, and the python code and table used as training points are available in this page. Our results indicate that using UAV equipped with an optical digital camera, we can estimate land surface movement, and extract soil parameters such as soil moisture data using the technique presented in this research (https://doi.org/10.13023/etd.2021.369).