[865] - UAV-based Imaging for Multi-Temporal, very high Resolution Crop Surface Models to monitor Crop Growth Variability

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Features
Citation
Bendig, J., Bolten, A., Bareth, G., 2013. UAV-based Imaging for Multi-Temporal, very high Resolution Crop Surface Models to monitor Crop Growth Variability. PFG (Photogrammetrie - Fernerkundung - Geoinformation), 2013 (6), 551 - 562. DOI: 10.1127/1432-8364/2013/0200.
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Identification
Title(s):Main Title: UAV-based Imaging for Multi-Temporal, very high Resolution Crop Surface Models to monitor Crop Growth Variability
Description(s):Abstract: This paper describes the generation of multi-temporal crop surface models (CSMs) with very high resolution of < 0.05 m. Data collection was carried out with a low-cost and low-weight UAV-system with a weight of less than 5 kg and the possibility of mounting different sensors. Key focus is the detection of crop growth variability and its dependency on cultivar, crop treatment and stress. The study area is a barley experiment field in Bonn in the west of Germany. Four replications of four cultivars of barley were investigated of which half of them where treated with a fungicide. Five UAV-campaigns were carried out during the growing season between early May and late July 2012. Ground control points (GCPs) measured with a Hi-Per Pro Topcon DGPS allowed for appropriate ground truth (< 0.02 m). Ground based infield control surveys on three dates served as validation of the method. Additionally, various destructive and non-destructive ground data were collected. The stereo images captured were processed into CSMs by using the structure-from-motion (SfM) software Agisoft PhotoScan. Generated plant heights ranged between 0.16 m and 0.983 m. R (n = 32) for the correlation between plant heights in the CSM and infield control surveys is 0.69. Lower plant heights were detected in those plots of the field where no fungicide was applied. Height differences between cultivars were observed and increased during growing season. The accuracy assessment of DEMs generated with the proposed UAV-based imaging showed a correlation coefficient of 0.99 (n = 10) between the DGPS GCPs and the DEMs with a mean difference of 0.01 m in z-direction.
Identifier(s):DOI: 10.1127/1432-8364/2013/0200
Citation Advice:Bendig, Juliane; Bolten, Andreas; Bareth, Georg (2013): UAV-based Imaging for Multi-Temporal, very high Resolution Crop Surface Models to monitor Crop Growth Variability. PFG 2013 (6), pp.551-562. http://dx.doi.org/10.1127/1432-8364/2013/0200
Responsible Party
Creator(s):Author: Juliane Bendig
Author: Andreas Bolten
Author: Georg Bareth
Publisher:E. Schweizerbart'sche Verlagsbuchhandlung
Topic
TR32 Topic:Remote Sensing
Subject(s):CRC/TR32 Keywords: UAV, Vegetation, Plant Growth, Remote Sensing, Agriculture, Remote Sensing Methods, Winter Barley, Canopy, Classification, GIS
File Details
File Name:Bendig_et_al_UAV_CSM_PFG_2013.pdf
Data Type:Text
File Size:16455 kB (16.069 MB)
Date(s):Created: 2014-05-14
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
Constraints
Download Permission:Free
Download Information:PFG Open Access Publication: http://www.ingentaconnect.com/content/schweiz/pfg/2013/00002013/00000006/art00001
General Access and Use Conditions:no conditions apply
Access Limitations:no limitations
Licence:TR32DB Data policy agreement
Geographic
North:-no map data
East:-
South:-
West:-
Measurement Region:NorthRhine-Westphalia
Measurement Location:--NorthRhine-Westphalia--
Specific Informations - Publication
Status:Published
Review:NoPeerReview
Year:2013
Type:Article
Article Type:Journal
Source:PFG (Photogrammetrie - Fernerkundung - Geoinformation)
Issue:6
Volume:2013
Number Of Pages:12
Page Range:551 - 562
Metadata Details
Metadata Creator:Georg Bareth
Metadata Created:2014-05-14
Metadata Last Updated:2014-05-14
Subproject:Z1
Funding Phase:2
Metadata Language:English
Metadata Version:V40
Dataset Metrics
Page Visits:1211
Metadata Downloads:0
Dataset Downloads:28
Dataset Activity
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