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Sensor requirements for biodiversity research. The role of spatial and spectral resolution in mapping habitat of zoological communities

Leutner, Benjamin and Wegmann, Martin and Müller, Jörg and Bachmann, Martin and Dech, Stefan (2015) Sensor requirements for biodiversity research. The role of spatial and spectral resolution in mapping habitat of zoological communities. The 36th International Symposium on Remote Sensing of Environment (ISRSE), 11.-15. Mai 2015, Berlin, Germany.

Full text not available from this repository.

Official URL: http://meetingorganizer.copernicus.org/ISRSE36/ISRSE36-523.pdf

Abstract

Modelling forest habitat types is of crucial importance for biodiversity research on landscape scales. Substantial progress has been made in the development of remote sensing based habitat mapping, for which a multitude of different sensor systems have been employed. Yet, researchers frequently face the decision which remote sensing data to acquire for a particular modelling task. There is no general understanding on how fundamental sensor characteristics such as spectral and spatial resolution interplay in determining mapping success. Based on airborne hyperspectral data we developed a modelling framework for the identification of both sufficient and optimal sensor characteristics for a given modelling task with respect to spectral and spatial resolution of optical imagery. To this end, we simulate a spatial resolution gradient and a spectral resolution gradient. Furthermore, we simulate different space-borne sensors to evaluate the practical relevance of the simulated sensor systems. The focus of our study lays on mapping habitat for different zoological communities in montane mixed forest stands in the Bavarian Forest national park in Germany. Habitats are defined for continuous gradients of community similarity obtained by means of multivariate ordination of zoological ground survey data and are subsequently modelled using random forest regression. We show that optimal sensor choice is primarily driven by an appropriate spatial resolution. In terms of spectral resolution multispectral sensor systems perform equally well as hyperspectral data. However, overall model quality depends on the organism group under investigation and their functional properties such as habitat fidelity. The presented approach allows us to estimate optimal sensor set-ups or the expected increase in model accuracy if transitioning from less suitable data to more suitable data making this a valuable tool to support the definition of sensor requirements for future missions in an objective, data-driven way.

Item URL in elib:https://elib.dlr.de/99053/
Document Type:Conference or Workshop Item (Speech)
Title:Sensor requirements for biodiversity research. The role of spatial and spectral resolution in mapping habitat of zoological communities
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Leutner, Benjaminbenjamin.leutner (at) uni-wuerzburg.deUNSPECIFIED
Wegmann, Martinmartin.wegmann (at) uni-wuerzburg.deUNSPECIFIED
Müller, JörgNationalparkverwaltung Bayerischer WaldUNSPECIFIED
Bachmann, Martinmartin.bachmann (at) dlr.deUNSPECIFIED
Dech, Stefanstefan.dech (at) dlr.deUNSPECIFIED
Date:2015
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:spatial resolution, spectral resolution, habitat mapping, hyperspectral, multispectral, biodiversity
Event Title:The 36th International Symposium on Remote Sensing of Environment (ISRSE)
Event Location:Berlin, Germany
Event Type:international Conference
Event Dates:11.-15. Mai 2015
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 - Vorhaben Geowissenschaftl. Fernerkundungs- und GIS-Verfahren
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center
German Remote Sensing Data Center > Leitungsbereich DFD
German Remote Sensing Data Center > Land Surface
Deposited By: Wöhrl, Monika
Deposited On:10 Nov 2015 11:25
Last Modified:10 May 2016 23:33

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