Improving Satellite-Based Retrieval of Maize Leaf Chlorophyll Content by Joint Observation with UAV Hyperspectral Data

Improving Satellite-Based Retrieval of Maize Leaf Chlorophyll Content by Joint Observation with UAV Hyperspectral Data

While satellite-based remote sensing offers a promising avenue for large-scale LCC estimations, the accuracy of evaluations is often decreased by mixed pixels, attributable to distinct farming practices and diverse soil conditions. To overcome these challenges and to account for maize intercropping...

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Bibliographic Details
Main Authors: Siqi Yang, Ran Kang, Tianhe Xu, Jian Guo, Caiyun Deng, Li Zhang, Lulu Si, Hermann Josef Kaufmann
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Drones
Subjects:
UAV hyperspectral
chlorophyll content
maize intercropping
random linear mixed model
spectral matching
Online Access:https://www.mdpi.com/2504-446X/8/12/783
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