Proceedings
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| Filter results5 paper(s) found. |
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1. Privacy Issues and the Use of UASs/Drones in MarylandAccording to the Federal Aviation Administration (FAA), the lawful use of Unmanned Aerial Vehicles (UAV), also known as Unmanned Aircraft Systems (UAS), or more commonly as drones, are currently limited to military, research, and recreational applications. Under the FAA’s view, commercial uses of drones are illegal unless approved by the Federal government. This will change in the future. Congress authorized the FAA to develop regulations for the use of drones by private... P. Goeringer, A. Ellixson, J. Moyle |
2. Ownership and Protections of Farm DataFarm data has been a contentious point of debate with respect to ownership rights and impacts when access rights are misappropriated. One of the leading questions farmers ask deals with the protections provided to farm data. Although no specific laws or precedence exists, the possibility of trade secret is examined and ramifications for damages discussed. Farm management examples are provided to emphasize the potential outcomes of each possible recourse for misappropriating farm data. ... A. Ellixson, P. Goeringer, T. Griffin |
3. Assessing Precision Water Management in Cotton Using Unmanned Aerial Systems and Satellite Remote SensingThe goal of this study was to improve agricultural sustainability and water use efficiency by allocating the right amount of water at the right place and time within the field. The objectives were to assess the effect of variable rate irrigation (VRI) on cotton growth and yield and evaluate the application of satellites and Unmanned aerial systems (UAS) in capturing the spatial and temporal patterns of cotton growth response to irrigation. Irrigation treatments with six replications of three different... O. Adedeji, W. Guo, H. Alwaseela, B. Ghimire, E. Wieber, R. Karn |
4. Simulating Climate Change Impacts on Cotton Yield in the Texas High PlainsCrop yield prediction enables stakeholders to plan farming practices and marketing. Crop models can predict crop yield based on cropping system and practices, soil, and other environmental factors. These models are being used for decision support in agriculture in a variety of ways. Cultivar selection, water and nutrient input optimization, planting date selection, climate change analysis and yield prediction are some of the promising area of applications of the models in field level farm management.... B. Ghimire, R. Karn, O. Adedeji, G. Ritchie, W. Guo |
5. Predicting Within-field Cotton Yield Variability Using DSSAT for Decision Support in Precision AgricultureThe quantification of spatial and temporal variability of cotton (Gossypium hirsutum L.) yield provides critical information for optimizing resources, especially water, in the Southern High Plains (SHP), Texas, with a diminishing water supply. The within-field yield variation is mostly influenced by the properties of soil and their interaction with water and nutrients. The objective of this study was to predict within-field cotton yield variability using a crop growth model... B. Ghimire, R. Karn, O. Adedeji, W. Guo |