To schedule fruit tree Syzygium samarangense to bloom and bear fruit is a challenging work, which requires highly experienced and knowledgeable professions. Specific amount of fertilizers should be supplemented at specific timing. Therefore, it is also a labor-intensive work. Our goal is to provide a method to automatically identify nutritional and growing conditions of Syzygium samarangense. In this work, we applied both multispectral and hyperspectral imaging techniques to measure parts of Syzygium samarangense, including branches, leaves, flowers, and fuiits. We examined several important spectral indexes: water content index, biomass content index, structure index, and chlorophyll content index. A custom-built hyperspectral imaging system was used here. The system includes two spectrographs, and two charge-coupled devices One of the spectrographs disperses light in visible wavelength, and the other spectrograph works in short wavelength infrared light region. With line-scanning data acquisition, the collected reflectance data included two-dimensional spatial image as well as reflectance spectrum. The hyperspectral imaging data were compared with results from a commercial multispectral imagery. The selected lightweight multispectral imagery was portable by an UAV. Among the spectral indexes we examined, data from the two techniques were highly linear correlated, indicating that data from multispectral imagery were sufficiently reliable for orchard management. On the other hand, additional spectral characteristics were only shown in hyperspectral imaging data. Calculated images that mapped hyperspectral indexes showed patterned of diseased area in leaves. Therefore, we built an on-site orchard monitoring procedure that combines both multispectral and hyperspectral imaging techniques for wax apple tree.
KEYWORDS: 3D modeling, Unmanned aerial vehicles, Sensors, RGB color model, Data modeling, Agriculture, 3D image processing, Control systems, Cameras, Systems modeling
As the Unmanned aerial vehicle (UAV) become ubiquitous, many early studies utilizing the UAV for three-dimensional (3D) modeling system are successively proposed as well. The advantage of using UAV successfully advances efficiency and reduces the cost time for simplifying the process of collecting data. Moreover, the characteristics of the light sized and suspension of new designed UAV could allow the users to gather the precise data from the rugged terrain and through a crowd of trees and may build a detail 3D and hyperspectral images. By those high-resolution 3D model data, the texture and shape of observation can be seen and brings research into further analysis. However, there are some limits that the information of 3D modeling data in RGB wide bands is not adequate to investigate vegetation research. The hyper spectrum collects the information of tens of bands with the narrow bandwidth could analyze the detail difference between abnormal and normal situations when the plant is growing. Therefore, how to combine hyperspectral data into a 3D modeling system would be important when researches want to attain the location data and spectral image simultaneously. In this study, the UAV will be loaded with two kinds of systems, and try to build the model include 3D modeling information and spectral information. As a result, it can monitor the growth condition of plants, their environment, also the precise location at the same time so that it can make vegetation analysis more complete.
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