Normalizing the Local Incidence Angle in Sentinel-1 Imagery to Improve Leaf Area Index, Vegetation Height, and Crop Coefficient Estimations

Normalizing the Local Incidence Angle in Sentinel-1 Imagery to Improve Leaf Area Index, Vegetation Height, and Crop Coefficient Estimations

Public domain synthetic-aperture radar (SAR) imagery, particularly from Sentinel-1, has widened the scope of day and night vegetation monitoring, even when cloud cover limits optical Earth observation. Yet, it is challenging to combine SAR images acquired at different incidence angles and from ascen...

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Bibliographic Details
Main Authors: Gregoriy Kaplan, Lior Fine, Victor Lukyanov, V. S. Manivasagam, Josef Tanny, Offer Rozenstein
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Land
Subjects:
Sentinel-1
SAR
RVI
incidence angle
crop coefficient
leaf area index
Online Access:https://www.mdpi.com/2073-445X/10/7/680

Internet

https://www.mdpi.com/2073-445X/10/7/680

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