Beyond assimilation of leaf area index: Leveraging additional spectral information using machine learning for site-specific soybean yield prediction-Reference-Cited by-同舟云学术

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Beyond assimilation of leaf area index: Leveraging additional spectral information using machine learning for site-specific soybean yield prediction

Published:2024-05 Issue: Volume:351 Page:110022
ISSN:0168-1923
Container-title:Agricultural and Forest Meteorology
language:en
Short-container-title:Agricultural and Forest Meteorology

Author:

Gaso Deborah V.^ORCID,Paudel Dilli,de Wit Allard^ORCID,Puntel Laila A.,Mullissa Adugna,Kooistra Lammert

Funder

Agencia Nacional de Investigacion e Innovacion

Publisher

Elsevier BV

Reference52 articles.

1. Dual-polarimetric descriptors from Sentinel-1 GRD SAR data for crop growth assessment;Bhogapurapu;ISPRS J. Photogramm. Remote Sensing,2021

2. A global perspective on sustainable intensification research;Cassman;Nat. Sustain.,2020

3. Using the Red-Edge Bands on Sentinel-2 For Retrieving Canopy Chlorophyll and Nitrogen Content;Clevers,2012

4. High-resolution soybean yield mapping across the us midwest using subfield harvester data;Dado;Remote Sens.,2020

5. Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance;Daughtry;Remote Sens. Environ.,1999

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