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A New Concept of Soil Line Retrieval from Landsat 8 Images for Estimating Plant Biophysical Parameters

Ahmadian, Nima and Demattê, José A. M. and Xu, Dandan and Borg, Erik and Zölitz, Reinhard (2016) A New Concept of Soil Line Retrieval from Landsat 8 Images for Estimating Plant Biophysical Parameters. Remote Sensing, 8 (9), pp. 1-23. Multidisciplinary Digital Publishing Institute (MDPI). doi: doi:10.3390/rs8090738. ISBN ISSN: 2072-4292. ISSN 2072-4292.

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Official URL: http://www.mdpi.com/2072-4292/8/9/738


Extraction of vegetation information from remotely sensed images has remained a long-term challenge due to the influence of soil background. To reduce this effect, the slope and intercept of the soil line (SL) should be known to calculate SL-related vegetation indices (VIs). These VIs can be used to estimate the biophysical parameters of agricultural crops. However, it is a difficult task to retrieve the SL parameters under the vegetation canopy. A feasible method for retrieving these parameters involves extracting the bottom boundary line in two-dimensional spectral spaces (i.e., red and near-infrared bands). In this study, the slope and intercept of the SL was extracted from Landsat 8 OLI images of a test site in northeastern Germany. Different statistical methods, including the Red-NIRmin method, quantile regression method (using a floating tau with the smallest p-value), and a new approach proposed in this paper using a fixed quantile tau known as the diffuse non-interceptance (DIFN) value, were applied to retrieve the SL parameters. The DIFN value describes the amount of light visible below the canopy that reaches the soil surface. Therefore, this value can be used as a threshold for retrieving the bottom soil line. The simulated SLs were compared with actual ones extracted from ground truth data, as recorded by a handheld spectrometer, and were also compared with the SL retrieved from bare soil pixels of the Landsat 8 image collected after harvest. Subsequently, the SL parameters were used to separately estimate the dry biomasses of winter wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), and canola (Brassica napus L.) at the local and field scales using different SL-related vegetation indices. The SL can be retrieved more accurately at the local scale compared with the field scale, and its simulation can be critical in the field due to significant differences from the actual SL. Moreover, the slope and intercept of the simulated SLs found using the floating and fixed quantile tau (slope � 1.1 and intercept � 0.05) show better agreement with the actual SL parameters (slope � 1.2 and intercept � 0.03) in the late growing stages (i.e., end of ripening and senescence stages) of crops. The slope and intercept of the soil line extracted from bare soil pixels of the Landsat 8 OLI data after harvest (slope = 1.3, intercept = 0.03, and R2 = 0.94) are similar to those of the simulated SL. The correlation coefficient (R2) of the simulated SLs are greater than 0.97 during different growing stage and all of the SL parameters are statistically significant (p < 0.05) at the local scale. The results also imply the need for different vegetation indices to best retrieve the crop biomass depending on the growing stage, but relatively small differences in performances were observed in this study.

Item URL in elib:https://elib.dlr.de/105760/
Document Type:Article
Title:A New Concept of Soil Line Retrieval from Landsat 8 Images for Estimating Plant Biophysical Parameters
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Ahmadian, Nimaahmadian.n (at) gmail.comUNSPECIFIED
Demattê, José A. M.jamdemat (at) usp.brUNSPECIFIED
Xu, Dandanxudd0621 (at) gmail.comUNSPECIFIED
Borg, ErikErik.Borg (at) dlr.deUNSPECIFIED
Zölitz, Reinhardzoelitz (at) uni-greifswald.deUNSPECIFIED
Date:9 September 2016
Journal or Publication Title:Remote Sensing
Refereed publication:Yes
Open Access:Yes
Gold Open Access:Yes
In ISI Web of Science:Yes
DOI :doi:10.3390/rs8090738
Page Range:pp. 1-23
EditorsEmailEditor's ORCID iD
Baghdadi, Nicolasremotesensing@mdpi.comUNSPECIFIED
Thenkabail, Prasad S.remotesensing@mdpi.comUNSPECIFIED
Publisher:Multidisciplinary Digital Publishing Institute (MDPI)
Series Name:Remote Sensing
ISBN:ISSN: 2072-4292
Keywords:remote sensing; soil line (SL); Landsat 8 OLI; soil line related vegetation indices biomass; bare soil; DEMMIN
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Vorhaben Fernerkundung der Landoberfläche (old)
Location: Neustrelitz
Institutes and Institutions:German Remote Sensing Data Center > National Ground Segment
Deposited By: Borg, Dr.rer.nat. Erik
Deposited On:19 Sep 2016 12:18
Last Modified:14 Dec 2019 04:26

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