BAE Graduate Student Exit Seminar
Tuesday, August 19, 2014
2-3 pm, 2045 BAINER HALL
Topic:
"An inexpensive system to monitor canopy temperature in almond and walnut trees using a small unmanned aerial vehicle (UAV)"
Presenter: Mr. Kellen Crawford
MS degree candidate
Department of Biological & Agricultural Engineering
University of California, Davis
Abstract:
Improving water use efficiency in agriculture will be an essential task to optimize water use in the face of decreasing water resources and a growing population. In specialty crops, improving water use efficiency can even lead to a higher value crop. In typical irrigation practices, much of the field receives more water than it needs as a result of field heterogeneity. A system to monitor the needs of each plant or a block of plants within the field would be helpful in distributing irrigation water according to each plant or block of plants needs. The difference between leaf temperature and air temperature has been shown to be a good indicator of stress in almond and walnut trees, but current ground methods of leaf temperature monitoring are too slow for large-scale monitoring, and aircraft or satellite-based methods are too infrequent, imprecise, or too expensive. A small UAV was retrofitted with an inexpensive infrared (IR) temperature sensor and a digital camera. The camera provided a spatial awareness to the IR temperature measurements which would otherwise require a very expensive thermal imager to obtain. Each temperature measurement was assumed to be a weighted sum of four classes of material seen in the image: sunlit canopy, shaded canopy, sunlit soil, and shaded soil. With at least several measurements of the same tree, a linear system of equations could be established to estimate the temperature of the shaded and sunlit portions of the canopy. With leaf temperatures ranging from about 12 to 40 degrees Celsius between 23 flights over two years, least-squares minimization was able to estimate the temperature of the sunlit and shaded leaves to within several degrees of the sampled temperature in most cases, with an r-squared value of 0.96 during the first year, and 0.73 during the second year. An additional study was undertaken to detect spatial temperature distribution within the orchard. Ground measurements were taken of every other tree in two walnut rows and one almond row using the HHSS, and the UAV was flown over those rows immediately following each ground sampling. An interpolated temperature map of the UAVs temperature measurements indicated a very similar temperature distribution as that measured with the HHSS, but the UAV was much faster and in parts of the rows provided a higher spatial resolution than the HHSS.
Coffee and cookies will be served.
