Estimation of Maize Leaf Area Index and Aboveground Biomass Based on Hyperspectral Data
In order to assess maize growth status accurately and quickly for improving maize precise management, field experiment was conducted in Gongzhuling research station, Jilin Academy of Agricultural Sciences, Jilin province. Experimental design included 3 planting densities and 5 maize materials. The n...
Guardado en:
Autores principales: | SHU Meiyan, CHEN Xiangyang, WANG Xiqing, MA Yuntao |
---|---|
Formato: | article |
Lenguaje: | EN ZH |
Publicado: |
Editorial Office of Smart Agriculture
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/1690d6b0d1744e8ab94bb35f9f879c05 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Hyperspectral retrieval of leaf physiological traits and their links to ecosystem productivity in grassland monocultures
por: Yujin Zhao, et al.
Publicado: (2021) -
Estimating the maize biomass by crop height and narrowband vegetation indices derived from UAV-based hyperspectral images
por: Yue Zhang, et al.
Publicado: (2021) -
The use of machine learning methods to estimate aboveground biomass of grasslands: A review
por: Tiago G. Morais, et al.
Publicado: (2021) -
Evaluating different methods for retrieving intraspecific leaf trait variation from hyperspectral leaf reflectance
por: Kenny Helsen, et al.
Publicado: (2021) -
Modelling Aboveground Biomass Carbon Stock of the Bohai Rim Coastal Wetlands by Integrating Remote Sensing, Terrain, and Climate Data
por: Shaobo Sun, et al.
Publicado: (2021)