Predicting Foliar Nutrient Concentrations across Geologic Materials and Tree Genera in the Northeastern United States Using Spectral Reflectance and Partial Least Squares Regression Models
Spectral data can potentially offer a rapid assessment of nutrients in leaves and reveal information about the geologic history of the soil. This study evaluated the capability of the partial least squares regression (PLSR) for estimating foliar macro- and micronutrients (Ca, Mg, K, P, Mn, and Zn) u...
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| Autori principali: | , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
American Association for the Advancement of Science (AAAS)
2024-01-01
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| Serie: | Journal of Remote Sensing |
| Accesso online: | https://spj.science.org/doi/10.34133/remotesensing.0093 |
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