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Full-Text Articles in Engineering
Multispectral Remote Sensing For Yield Estimation Using High-Resolution Imagery From An Unmanned Aerial Vehicle, Mahyar Aboutalebi, Alfonso F. Torres-Rua, Niel Allen
Multispectral Remote Sensing For Yield Estimation Using High-Resolution Imagery From An Unmanned Aerial Vehicle, Mahyar Aboutalebi, Alfonso F. Torres-Rua, Niel Allen
AggieAir Publications
Satellites and autonomous unmanned aerial vehicles (UAVs) are two major platforms for acquiring remotely-sensed information of the earth’s surface. Due to the limitations of satellite-based imagery, such as coarse spatial resolution and fixed schedules, applications of UAVs as low-cost remote sensing systems are rapidly expanding in many research areas, particularly precision agriculture. UAVs can provide imagery with high spatial resolution (finer than 1 meter) and acquire information in visible, near infrared, and even thermal bands. In agriculture, vegetation characteristics such as health, water stress, and the amount of biomass, can be estimated using UAV imagery. In this study, three sets …
Implications Of Sensor Inconsistencies And Remote Sensing Error In The Use Of Small Unmanned Aerial Systems For Generation Of Information Products For Agricultural Management, Mac Mckee, Ayman Nassar, Alfonso F. Torres-Rua, Mahyar Aboutalebi, William Kustas
Implications Of Sensor Inconsistencies And Remote Sensing Error In The Use Of Small Unmanned Aerial Systems For Generation Of Information Products For Agricultural Management, Mac Mckee, Ayman Nassar, Alfonso F. Torres-Rua, Mahyar Aboutalebi, William Kustas
AggieAir Publications
Small, unmanned aerial systems (sUAS) for remote sensing represent a relatively new and growing technology to support decisions for agricultural operations. The size and power limitations of these systems present challenges for the weight, size, and capability of the sensors that can be carried, as well as the geographical coverage that is possible. These factors, together with a lack of standards for sensor technology, its deployment, and data analysis, lead to uncertainties in data quality that can be difficult to detect or characterize. These, in turn, limit comparability between data from different sources and, more importantly, imply limits on the …