Abstract
Currently, hyperspectral remote sensing has been fully applied to wheat, paddy, soybean, corn and other crops (Teng et al. 2009). As a simple, fast, low-cost and non-invasive spectral analysis technique, hyperspectral technique gets much concern in agricultural production applications, mainly used in crop growth monitoring and yield estimation, nutrition diagnosis and fertilizer, agricultural product quality and safety testing and many other aspects. In recent years, the application research in the field of agriculture of hyperspectrum focuses on the following areas: food crops, including wheat, paddy, soybean, maize, etc.; agricultural products, including fruits and livestock products; economic crops, including cotton, tea and tobacco and so on.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Lou QS, Chen L et al (2008) The application and prospecting of the hyperspectral remote sensing technology in marine research. Trans Oceanol Limnol 3:168–173
Pei CK, Fu J (2007) Status and prospect of hyperspectral remote sensing technique in rock and mineral identification. World Nucl Geosci 24(1):32–38
Tan BX, Li ZY et al (2008) Research advance in forest information extraction from hyperspectral remote sensing Data. For Res 21(supplement):105–111
Tan BX, Li ZY, Chen E et al (2006) Estimating forest crown closure using hyperion hyperspectral data. J Beijing For Univ 28(3):95–101
Teng AG, Gao F et al (2009) Progress of hyperspectral technology application research in agriculture. Jiangsu Agric Sci 3:8–11
Tong QX, Zhang B, Lanfen Z (2006) Hyperspectral remote sensing: principle, technology and application. Higher Education Press, Beijing
Zhang CY, Cheng HF et al (2008) The development of hyperspectral remote sensing and its threatening to military equipments. Electro-optic Technol Appl 23(1):10–12
Zhou L, Xin XP et al (2009) Application of hyperspectral remote sensing in the monitoring of the grassland. Sci Grass Ind 26(4):20–27
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2016 National Defense Industry Press, Beijing and Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Wang, L., Zhao, C. (2016). Introduction of Hyperspectral Remote Sensing Applications. In: Hyperspectral Image Processing. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47456-3_9
Download citation
DOI: https://doi.org/10.1007/978-3-662-47456-3_9
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-47455-6
Online ISBN: 978-3-662-47456-3
eBook Packages: EngineeringEngineering (R0)