Comparative Evaluation of Machine Learning Models for Predicting Leaf Gas Exchange Traits from Hyperspectral Reflectance

Hyperspectral remote sensing has been successfully used to retrieve parameters such as chlorophyll and nitrogen content. However, effective models for inverting dynamic physiological processes like gas exchange are lacking, and the predictive accuracy and applicable limits of such inversions remain...

وصف كامل

التفاصيل البيبلوغرافية
الحاوية / القاعدة:Agriculture
المؤلفون الرئيسيون: Zhipeng Ren, Haoze Zhang, Wei Cai, Zehao Liu, Tao Ma, Wenzhi Zeng
التنسيق: مقال
اللغة:الإنجليزية
منشور في: MDPI AG 2026-05-01
الموضوعات:
hyperspectral inversion
maize
machine learning
SHAP values
spectral vegetation indices
الوصول للمادة أونلاين:https://www.mdpi.com/2077-0472/16/9/1015

الانترنت

https://www.mdpi.com/2077-0472/16/9/1015

مواد مشابهة