Estimation of district-level spring barley yield in southern Sweden using multi-source satellite data and random forest approach

Estimation of district-level spring barley yield in southern Sweden using multi-source satellite data and random forest approach

Remote sensing observations and artificial intelligence algorithms have emerged as key components for crop yield estimation at various scales during the past decades. However, the utilization of multi-source satellite data and machine learning for estimating aggregated crop yield at the regional lev...

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Bibliographic Details
Main Authors: Xueying Li, Hongxiao Jin, Lars Eklundh, El Houssaine Bouras, Per-Ola Olsson, Zhanzhang Cai, Jonas Ardö, Zheng Duan
Format: Article
Language:English
Published: Elsevier 2024-11-01
Series:International Journal of Applied Earth Observations and Geoinformation
Subjects:
Crop yield
Sentinel-2
Solar-induced chlorophyll fluorescence
Machine learning
Remote sensing
Online Access:http://www.sciencedirect.com/science/article/pii/S1569843224005399
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