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Dive into the research topics where Holger Lilienthal is active.

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Featured researches published by Holger Lilienthal.


Environmental Modelling and Software | 2014

Enhanced biomass prediction by assimilating satellite data into a crop growth model

Miriam Machwitz; Laura Giustarini; Christian Bossung; David Frantz; Martin Schlerf; Holger Lilienthal; Loise Wandera; Patrick Matgen; Lucien Hoffmann; Thomas Udelhoven

Complex crop growth models (CGM) require a large number of input parameters, which can cause large errors if they are uncertain. Furthermore, they often lack spatial information. The coupling of a CGM with a radiative transfer model offers the possibility to assimilate remote sensing data while taking into account uncertainties in input parameters. A particle filter was used to assimilate satellite data into a CGM coupled with a leaf-canopy radiative transfer model to update biomass simulations of maize. The synthetic experiment set up to test the reliability of the procedure, highlighted the importance of the acquisition time. The real case study with RapidEye observations confirmed these findings. Data assimilation increased the accuracy of biomass predictions in the majority of the six maize fields where biomass validation data was available, with improvements of up to 15%. The smallest and largest errors in biomass prediction after assimilation were 82?kg/ha and 2116?kg/ha, respectively. Furthermore, data assimilation enabled the production of biomass maps showing detailed spatial variability. Data assimilation using a particle filter for biomass estimation was conducted.Proof of concept with synthetic case studies.Multispectral satellite data (visible and near infrared) was found to be suitable for data assimilation.Assimilation of satellite data allowed biomass prediction on a pixel basis.


Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV | 2012

Using hyperspectral remote sensing data for the assessment of topsoil organic carbon from agricultural soils

Bastian Siegmann; Thomas Jarmer; Thomas Selige; Holger Lilienthal; Nicole Richter; Bernhard Höfle

Detecting soil organic carbon (SOC) changes is important for both the estimation of carbon sequestration in soils and the development of soil quality. During a field campaign in May 2011 soil samples were collected from two agricultural fields northwest of Koethen (Saxony-Anhalt, Germany) and the SOC content of the samples was determined in the laboratory afterwards. At the same time image data of the test site was acquired by the hyperspectral airborne scanner AISA-DUAL (450-2500 nm). The image data was corrected for atmospheric and geometric effects and a spectral binning has been performed to improve the signal-to-noise ratio (SNR). For parameter prediction, an empirical model based on partial least squares regression (PLSR) was developed from AISA-DUAL image spectra extracted at the geographic location of the soil samples and analytical laboratory results. The obtained SOC concentrations from the AISA-DUAL data are in accordance with the concentration range of the chemical analysis. For this reason, the PLSR-model has been applied to the AISA-DUAL image data. The predicted SOC concentrations reflect the spatial conditions of the two investigated fields. The results indicate the potential of the used method as a quick screening tool for the spatial assessment of SOC, and therefore an appropriate alternative to time- and cost-intensive chemical analysis in the laboratory.


Julius-Kühn-Archiv | 2016

Satellitenfernerkundung für die Landwirtschaft – Anwendungsbeispiele jenseits der Agrarsubventionskontrolle

Burkhard Golla; Holger Lilienthal; Anja Kroll; Heike Gerighausen

Die Daten der Vergleichsbetriebe stellen den Status quo im Pflanzenschutz in Deutschland dar. Der Behandlungsindex in Mohre und Frischkohl betrug im Durchschnitt der Jahre (2007-2014) bei 6,2 bzw. 9,2. Mohren wurden vorrangig mit Herbiziden und Frischkohl mit Insektiziden behandelt. Unter dem Aspekt des Pflanzenschutzes und zur Reduktion der Behandlungsintensitat mit Insektiziden kann Abbildung 1: Behandlungsindex der Herbizide (Herbizid-BI) in Abhangigkeit der Vorfrucht in den Vergleichsbetrieben fur Mohre, 2007-2014, in Deutschland, ungleiche Buchstaben symbolisieren signifikante Unterschiede (p<0,05), nBlattfrucht=58, nGemuse=28, nHalmfruchte=115 208 72. ALVA-Tagung, Seminarhotel Wesenufer, 2017 der Fruhkohlanbau empfohlen werden. Im Kohl- und Mohrenanbau konnen Halmvorfruchte Schadlingsbefall vorbeugen. Die Mittelaufwandmengen wurden vorrangig bei Herbizidanwendungen reduziert In beiden Kulturen wurden Abweichungen vom notwendigen Mas verzeichnet. Die Pflanzenschutzberatung sowie die regelmasige Durchfuhrung von Bonituren konnen Pflanzenschutzmittelanwendungen dem notwendigen Mas naher bringen und die Umsetzung des IPS in der Praxis verbessern. Fur die Ausschopfung nichtchemischer Masnahmen sind Praxisdemonstrationen und der intensive Austausch zwischen Wissenschaft und Praxis notig, genauso wie Forschungsforderung zur Entwicklung neuer und Optimierung bestehender integrierter Verfahren und neuer Wirkstoffe. Vorbildhaft wird der IPS von den Demonstrationsbetrieben u. a. in den Kulturen Mohre und Weiskohl, seit 2014 umgesetzt. Die Betriebe werden individuell und intensiv betraten, um Pflanzenschutzmittelanwendungen auf das notwendige Mas zu beschranken. Hierfur werden Bonituren unter Nutzung von Schadschwellen, Warndiensthinweisen und Monitoringverfahren durchgefuhrt.


Isprs Journal of Photogrammetry and Remote Sensing | 2015

Comparative classification analysis of post-harvest growth detection from terrestrial LiDAR point clouds in precision agriculture

Kristina Koenig; Bernhard Höfle; Martin Hämmerle; Thomas Jarmer; Bastian Siegmann; Holger Lilienthal


ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences | 2013

RADIOMETRIC CORRECTION OF TERRESTRIAL LIDAR DATA FOR MAPPING OF HARVEST RESIDUES DENSITY

Kristina Koenig; Bernhard Höfle; L. Müller; Martin Hämmerle; Thomas Jarmer; Bastian Siegmann; Holger Lilienthal


17. und 18. Workshop Computer-Bildanalyse in der Landwirtschaft: 05. Mai 2011, Stuttgart, 09. Mai 2012, Osnabrück = Computerised image analysis in agriculture | 2012

Simulation landwirtschaftlicher Online-Sensorik mit Hilfe abbildender Hyperspektraldaten

Holger Lilienthal; Nicole Richter; Thomas Jarmer; Bastian Siegmann; Thomas Selige; Bernhard Höfle


Landbauforschung Völkenrode : FAL agricultural research | 2004

Significance of radar remote sensed imagery for agricultural applications

Erik Zillmann; Holger Lilienthal; Thomas Schrage; Ewald Schnug


Landbauforschung Völkenrode : FAL agricultural research | 2004

Application of LASSIE to improve agricultural field experimentation

Holger Lilienthal; Mikhail Ponomarev; Ewald Schnug


61. Jahrestagung der Gesellschaft für Pflanzenbauwissenschaften e. V., 25. bis 27. September 2018, Kiel - From Big Data to Smart Farming: Kurzfassungen der Vorträge und Poster | 2018

Phänotypisierung von Winterraps mithilfe eines mobilen, bodengestützten Hyperspektralsystems

Heike Gerighausen; Jorita Krieger; Holger Lilienthal


25th International Symposium of the Scientific Centre for Fertilizers “Signifi cance of Sulfur in High-Input Cropping Systems” : Groningen (Netherlands) ; September 5-8, 2017 | 2017

Spectral responses of sulfur deficiency in oilseed rape - first results of a field experiment

Holger Lilienthal; Heike Gerighausen; Jorita Krieger; Ewald Schnug

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Thomas Jarmer

University of Osnabrück

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