Hybrid Machine Learning and Geostatistical Methods for Gap Filling and Predicting Solar-Induced Fluorescence Values

Sun-induced chlorophyll fluorescence (SIF) has proven to be advantageous in estimating gross primary production, despite the lack of a stable relationship. Satellite-based SIF measurements at Level 2 offer comprehensive global coverage and are available in near real time. However, these measurements...

وصف كامل

التفاصيل البيبلوغرافية

الحاوية / القاعدة:	Remote Sensing
المؤلفون الرئيسيون:	Jovan M. Tadić, Velibor Ilić, Slobodan Ilić, Marko Pavlović, Vojin Tadić
التنسيق:	مقال
اللغة:	الإنجليزية
منشور في:	MDPI AG 2024-05-01
الموضوعات:	kriging with external drift machine learning solar-induced chlorophyll fluorescence (SIF) gap-filling techniques remote sensing geostatistics
الوصول للمادة أونلاين:	https://www.mdpi.com/2072-4292/16/10/1707