Exploring low order fractional derivative spectra indices for estimating leaf fuel moisture content across a variety of plant species
Author:
Affiliation:
1. Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Ministry of Education, Nanning Normal University, Nanning, China
2. Faculty of Agriculture, Shizuoka University, Shizuoka, Japan
Publisher
Informa UK Limited
Subject
General Earth and Planetary Sciences
Link
https://www.tandfonline.com/doi/pdf/10.1080/01431161.2023.2201384
Reference56 articles.
1. A possible fractional order derivative and optimized spectral indices for assessing total nitrogen content in cotton
2. Single bands leaf reflectance prediction based on fuel moisture content for forestry applications
3. Quantifying Leaf Chlorophyll Concentration of Sorghum from Hyperspectral Data Using Derivative Calculus and Machine Learning
4. Sensitivity of spectral reflectance to variation in live fuel moisture content at leaf and canopy level
5. Retrieval of leaf fuel moisture contents from hyperspectral indices developed from dehydration experiments
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