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Estimating the Leaf Area Index of agricultural crops using multi-temporal dual-polarimetric TerraSAR-X data: A case study on North East Germany

Ahmadian, Nima and Borg, Erik and Roth, Achim and Zölitz, Reinhard (2016) Estimating the Leaf Area Index of agricultural crops using multi-temporal dual-polarimetric TerraSAR-X data: A case study on North East Germany. Photogrammetrie, Fernerkundung, Geoinformation (5-6), pp. 301-317. E. Schweizerbartsche Verlagsbuchhandlung. DOI: 10.1127/pfg/2016/0303 ISSN 1432-8364

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Abstract

Leaf area index (LAI) is one of the most important ndicators of agricultural variables because of its relation to biophysical and biochemical properties of agricultural crops. Variations in LAI can be related to changes in leaf scattering properties, and these variations in leaf scattering properties can lead to changes in canopy backscattering behaviour. The objective of this study was to explore the potential of estimating LAI using multi-temporal dual polarimetric TerraSAR-X data in three different agricultural field crops, including winter wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), and canola (Brassica napus L.). The relationship between LAI and the scattering coefficient (σ0) in TerraSAR-X was explored using three different approaches, including univariate regression, i.e., simple linear and nonlinear regression, multivariate regression, i.e., stepwise regression, and a semi-empirical water cloudmodel(WCM). The multivariate stepwise regression showed is capability to retrieve the LAI without any external input data, such as soil moisture, based solely on the polarization channels, i.e., HH or VV, and polarization variables, e.g. HH/VV or HH+VV. However, unlike the WCM, the stepwise method is not applicable with just one polarization channel. The results indicate that the leaf area index (LAI) was significantly and consistently correlated with σ0 throughout the growth stages using the stepwise regression and WCM approaches, whereas simple linear and nonlinear regression yielded relatively poor results except with barley.

Item URL in elib:https://elib.dlr.de/111961/
Document Type:Article
Title:Estimating the Leaf Area Index of agricultural crops using multi-temporal dual-polarimetric TerraSAR-X data: A case study on North East Germany
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Ahmadian, Nimaahmadian.n (at) gmail.comUNSPECIFIED
Borg, ErikErik.Borg (at) dlr.deUNSPECIFIED
Roth, AchimAchim.Roth (at) dlr.deUNSPECIFIED
Zölitz, Reinhardzoelitz (at) uni-greifswald.deUNSPECIFIED
Date:2016
Journal or Publication Title:Photogrammetrie, Fernerkundung, Geoinformation
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
DOI :10.1127/pfg/2016/0303
Page Range:pp. 301-317
Editors:
EditorsEmail
Kresse, WolfgangUNSPECIFIED
Hinz, StefanUNSPECIFIED
Rottensteiner, FranzUNSPECIFIED
Conrad, ChristopherUNSPECIFIED
Bernhard, LarsUNSPECIFIED
Seyfert, EckhardtUNSPECIFIED
Publisher:E. Schweizerbartsche Verlagsbuchhandlung
ISSN:1432-8364
Status:Published
Keywords:TerraSAR-X, agricultural crop, leaf area index, stepwise regression, water cloud model, DEMMIN
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Remote sensing and geoscience
Location: Neustrelitz
Institutes and Institutions:German Remote Sensing Data Center > National Ground Segment
Deposited By: Borg, Dr.rer.nat. Erik
Deposited On:28 Sep 2017 15:02
Last Modified:06 Sep 2019 15:29

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