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Full-Text Articles in Engineering
Incorporation Of Unmanned Aerial Vehicle (Uav) Point Cloud Products Into Remote Sensing Evapotranspiration Models, Mahyar Aboutalebi, Alfonso F. Torres-Rua, Mac Mckee, William P. Kustas, Héctor Nieto, Maria Mar Alsina, Alex White, John H. Prueger, Lynn Mckee, Joseph Alfieri, Lawrence E. Hipps, Calvin Coopmans, Nick Dokoozlian
Incorporation Of Unmanned Aerial Vehicle (Uav) Point Cloud Products Into Remote Sensing Evapotranspiration Models, Mahyar Aboutalebi, Alfonso F. Torres-Rua, Mac Mckee, William P. Kustas, Héctor Nieto, Maria Mar Alsina, Alex White, John H. Prueger, Lynn Mckee, Joseph Alfieri, Lawrence E. Hipps, Calvin Coopmans, Nick Dokoozlian
Civil and Environmental Engineering Faculty Publications
In recent years, the deployment of satellites and unmanned aerial vehicles (UAVs) has led to production of enormous amounts of data and to novel data processing and analysis techniques for monitoring crop conditions. One overlooked data source amid these efforts, however, is incorporation of 3D information derived from multi-spectral imagery and photogrammetry algorithms into crop monitoring algorithms. Few studies and algorithms have taken advantage of 3D UAV information in monitoring and assessment of plant conditions. In this study, different aspects of UAV point cloud information for enhancing remote sensing evapotranspiration (ET) models, particularly the Two-Source Energy Balance Model (TSEB), over …
Spatial Scale Gap Filling Using An Unmanned Aerial System: A Statistical Downscaling Method For Applications In Precision Agriculture, Leila Hassan-Esfahani, Ardeshir M. Ebtehaj, Alfonso F. Torres-Rua, Mac Mckee
Spatial Scale Gap Filling Using An Unmanned Aerial System: A Statistical Downscaling Method For Applications In Precision Agriculture, Leila Hassan-Esfahani, Ardeshir M. Ebtehaj, Alfonso F. Torres-Rua, Mac Mckee
Civil and Environmental Engineering Faculty Publications
Applications of satellite-borne observations in precision agriculture (PA) are often limited due to the coarse spatial resolution of satellite imagery. This paper uses high-resolution airborne observations to increase the spatial resolution of satellite data for related applications in PA. A new variational downscaling scheme is presented that uses coincident aerial imagery products from “AggieAir”, an unmanned aerial system, to increase the spatial resolution of Landsat satellite data. This approach is primarily tested for downscaling individual band Landsat images that can be used to derive normalized difference vegetation index (NDVI) and surface soil moisture (SSM). Quantitative and qualitative results demonstrate promising …
Assessment Of Surface Soil Moisture Using High-Resolution Multi-Spectral Imagery And Artificial Neural Networks, Leila Hassan-Esfahani, Alfonso F. Torres-Rua, Austin M. Jensen, Mac Mckee
Assessment Of Surface Soil Moisture Using High-Resolution Multi-Spectral Imagery And Artificial Neural Networks, Leila Hassan-Esfahani, Alfonso F. Torres-Rua, Austin M. Jensen, Mac Mckee
Civil and Environmental Engineering Faculty Publications
Many crop production management decisions can be informed using data from high-resolution aerial images that provide information about crop health as influenced by soil fertility and moisture. Surface soil moisture is a key component of soil water balance, which addresses water and energy exchanges at the surface/atmosphere interface; however, high-resolution remotely sensed data is rarely used to acquire soil moisture values. In this study, an artificial neural network (ANN) model was developed to quantify the effectiveness of using spectral images to estimate surface soil moisture. The model produces acceptable estimations of surface soil moisture (root mean square error (RMSE) = …