Hyperspectral reflectance and machine learning for multi-site monitoring of cotton growth
Author:
Funder
Oak Ridge Institute for Science and Education
Great Plains Center for Agricultural Health
Publisher
Elsevier BV
Reference48 articles.
1. Machine learning optimized hyperspectral remote sensing retrieves cotton nitrogen status;Marang;Remote Sens.,2021
2. Hyperspectral remote sensing in precision agriculture: present status, challenges, and future trends;Singh;Hyperspectral Remote Sens.,2020
3. Nutrient prediction for tef (Eragrostis tef) plant and grain with hyperspectral data and partial least squares regression: replicating methods and results across environments;Flynn;Remote Sens.,2020
4. Hyperspectral imagery to monitor crop nutrient status within and across growing seasons;Liu;Remote Sens. Environ.,2021
5. Imaging spectroscopy algorithms for mapping canopy foliar chemical and morphological traits and their uncertainties;Singh;Ecol. Appl.,2015
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