DESIS Hyperspectral Satellite Data for Cropping Pattern Classification

DESIS Hyperspectral Satellite Data for Cropping Pattern Classification

Cropping patterns, including intercropping, are recognized as sustainable agricultural practices in many parts of Africa. However, there is a lack of data and information regarding their extent and specific locations. This study aims to understand the dynamics of these cropping patterns using hypers...

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Bibliographic Details
Main Authors: Mbali Mahlayeye, Roshanak Darvishzadeh, Charlynne Jepkosgei, Kelvin Aslen Mlawa, Andrew Nelson
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Cropping patterns
DESIS hyperspectral satellite data
principal component analysis (PCA)
random forest (RF) classification
Online Access:https://ieeexplore.ieee.org/document/10675363/

Internet

https://ieeexplore.ieee.org/document/10675363/

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