APPLICATION
Based on rice tillering stage of agricultural precision fertilizer as the research object, using unmanned aerial vehicle imaging hyperspectral remote sensing image of nitrogen concentration inversion model is established through the PSO -ELM, comprehensive consideration of agricultural related operation parameters, combined with the experts recommend fertilization build according to standard field, build the precision fertilizer model, finally using unmanned aerial vehicle precision fertilizer in agriculture.
The 900-1700nm band contains more information about the composition of meat, which is more reflective of the characteristics of meat and may be more suitable for the identification of meat adulteration. In order to expand the comprehensiveness and applicability of the model, the test should be extended to the long-wave NIR band (1700-2500nm). Further validation is needed.
UAV hyperspectral can better identify the distribution location of tea trees. The hyperspectral data of tea obtained under good flight conditions is more conducive to analysis and research, and can further improve the accuracy of classification and identification.
The hyperspectral imager is used to obtain hyperspectral data on mineral rocks and to analysis them spectroscopically to determine their composition.
Compared with ordinary RGB imaging system, hyperspectral has high dimensional features, information redundancy, significant uncertainty, small samples, and space-spectrum unity, etc., and it faces great challenges for data processing. In recent years, with the emergence of new techniques of deep learning, hyperspectral images based on deep learning have been fully developed in the fields of dimensionality reduction, hybrid image element decomposition and classification.