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Full-Text Articles in Engineering
Unmanned Aircraft System (Uas) Technology And Applications In Agriculture, Samuel C. Hassler, Fulya Baysal-Gurel
Unmanned Aircraft System (Uas) Technology And Applications In Agriculture, Samuel C. Hassler, Fulya Baysal-Gurel
Agricultural and Environmental Sciences Faculty Research
Numerous sensors have been developed over time for precision agriculture; though, only recently have these sensors been incorporated into the new realm of unmanned aircraft systems (UAS). This UAS technology has allowed for a more integrated and optimized approach to various farming tasks such as field mapping, plant stress detection, biomass estimation, weed management, inventory counting, and chemical spraying, among others. These systems can be highly specialized depending on the particular goals of the researcher or farmer, yet many aspects of UAS are similar. All systems require an underlying platform—or unmanned aerial vehicle (UAV)—and one or more peripherals and sensing …
Uas Flight Operations In Complex Terrain: Assessing The Agricultural Impact From Hurricane Maria In The Central Mountainous Region Of Puerto Rico, Kevin Adkins
Publications
Hurricane Maria struck Puerto Rico in September 2017 as a Category 4 storm causing major damage to infrastructure, agriculture and natural ecosystems, as well as the loss of many lives. Among the crops hardest hit was coffee, one of the most important crops in Puerto Rico. As a perennial system, coffee takes various production forms along a gradient from high shade/biodiversity coffee farms to low shade coffee monocultures and therefore offers an ideal means for the study of resistance and resilience of an agroecosystem to weather and climate disturbance. During the summer of 2018, 14 impacted farms across the production …
Seasonal Adaptation Of Vegetation Color In Satellite Images, Srinivas Jakkula, Vamsi K.R. Mantena, Ramu Pedada, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)
Seasonal Adaptation Of Vegetation Color In Satellite Images, Srinivas Jakkula, Vamsi K.R. Mantena, Ramu Pedada, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)
Electrical & Computer Engineering Faculty Publications
Remote sensing techniques like NDVI (Normal Difference vegetative Index) when applied to phenological variations in aerial images, ascertained the seasonal rise and decline of photosynthetic activity in different seasons, resulting in different color tones of vegetation. The rise and fall of NDVI values decide the biological response, either the green up or brown down [1]. Vegetation in green up period appears with more vegetative vigor and during brown down period it has a dry appearance. This paper proposes a novel method that identifies vegetative patterns in satellite images and then alters vegetation color to simulate seasonal changes based on training …