Title
Improved sugarcane LAI estimation using radiative transfer models with spatial constraint
Abstract
Sugarcane crop, cultivated in subtropical and tropical regions, provides major sugar supply, and makes great contributions to human life and economic development. The sugarcane leaf area index (LAI) is highly related to the production. Our research aims at estimating sugarcane LAI through remote sensing observations. The physically-based radiative transfer model (RTM) inversion methods are widely applied in vegetation variable estimation. However, ill-posedness problem widely exists in the model inversion processes. Therefore, the study develops a spatial constraint method to regularize the RTM inversion, and LAI variable is estimated on object-level. The estimated object-level LAI variable is compared with the pixel-level, and validated using the SNAP biophysical processor. The results shows that the object-level LAI estimates show great performance.
Year
DOI
Venue
2019
10.1109/Agro-Geoinformatics.2019.8820249
2019 8th International Conference on Agro-Geoinformatics (Agro-Geoinformatics)
Keywords
Field
DocType
LAI estimation,ill-posedness,radiative transfer model,PROSAIL
Leaf area index,Vegetation,Model inversion,Inversion (meteorology),Atmospheric radiative transfer codes,Subtropics,Atmospheric sciences,Environmental science,Radiative transfer,Tropics
Conference
ISSN
ISBN
Citations 
2334-3168
978-1-7281-2117-8
0
PageRank 
References 
Authors
0.34
3
5
Name
Order
Citations
PageRank
Yingpin Yang100.34
Qiting Huang230.76
Jian-Cheng Luo39920.75
Wei Wu412454.63
Yingwei Sun500.68