Journal of Agricultural Big Data >
Near-Infrared Spectral and Imaging Datasets of Fruit Tree Blooming in China in 2016
Received date: 2020-10-09
Online published: 2021-05-18
Remote sensing technology must first determine tree species in the area of interest before carrying out various follow-up tasks. Therefore, the classification of fruit tree species is particularly important. Fruit tree flowers are easier to distinguish using traits other than leaves. However, most of the currently collected fruit tree flowering data is from flowering period images or the spectral data of a single tree line. The data are also confined to outdoor canopy spectra, with limited studies in which indoor and outdoor spectral and imaging data have been collected simultaneously. Consequently, here, the ASD FieldSpec3 portable spectrum analyzer was used to collect indoor and outdoor spectral data during pear, apple, and apricot tree flowering periods. To record the flower states, the indoor and outdoor imaging datasets from the fruit tree flowering periods were collected for future evaluation. Using ground spectral test data to scientifically identify fruit tree species will provide a foundation for further research.
Key words： fruit tree; flowering period; near-infrared spectrum; image; scientific data
Xiaoli Wang, Qianhao Hu, Rui Man, Tingting Liu . Near-Infrared Spectral and Imaging Datasets of Fruit Tree Blooming in China in 2016[J]. Journal of Agricultural Big Data, 2021 , 3(1) : 88 -93 . DOI: 10.19788/j.issn.2096-6369.210110
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