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机器学习算法在高光谱感.知作物信息中的应用及展望.

Authors :
赵金龙
张学艺
李 阳
Source :
Chinese Journal of Agrometeorology. Nov2023, Vol. 44 Issue 11, p1057-1071. 15p.
Publication Year :
2023

Abstract

Machine learning, as a new technique combining statistics and computer science, has been widely used in crop information acquisition tasks in recent years. Traditional methods for obtaining crop information mainly rely on chemical detection methods, which is time-consuming and labor-intensive. Based on machine learning algorithms and hyperspectral remote sensing techniques, crop appearance and internal physical and chemical parameters can be quickly sensed in a non-destructive way, which has obvious application advantages and development prospects. First, the researches related to the hyperspectral remote sensing of crop information were systematically reviewed in this paper. Second, the application, advantages and disadvantages and uncertainties of different machine learning algorithms in hyperspectral sensing crop information were summarized. Finally, it was pointed out that the future development trends of hyperspectral sensing crop information were as follows: (1) complementary crop information acquisition methods could be realized through multi-source remote sensing collaborative observations. (2) The assimilation technologies of hyperspectral remote sensing and crop model as well as the deep integration technologies of hyperspectral remote sensing and artificial intelligence could be developed. (3) The intelligent acquisition of key information oriented to the whole growth period of crops and decision-making could be realized. [ABSTRACT FROM AUTHOR]

Details

Language :
Chinese
ISSN :
10006362
Volume :
44
Issue :
11
Database :
Academic Search Index
Journal :
Chinese Journal of Agrometeorology
Publication Type :
Academic Journal
Accession number :
173769228
Full Text :
https://doi.org/10.3969/j.issn.1000-6362.2023.11.007