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Remote sensing and GIS based ecological modelling of potential red deer habitats in the test site region DEMMIN (TERENO)

McKenna, Amelie and Schultz, Alfred and Borg, Erik and Neumann, Matthias and Mund, Jan-Peter (2020) Remote sensing and GIS based ecological modelling of potential red deer habitats in the test site region DEMMIN (TERENO). EGU General Assembly 2020, 04.-08. Mai 2020 (ONLINE), Vienna, Austria. doi: 10.5194/egusphere-egu2020-19953.

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Official URL: https://meetingorganizer.copernicus.org/EGU2020/EGU2020-19953.html


Introduction: The destruction of habitats has not only reduced biological diversity but also affected essential ecosystem services of the Central European cultural landscape. Therefore, in the further development of the cultural landscape and in the management of natural resources, special importance must be attached to the habitat demands of species and the preservation of ecosystem services. The study of ecosystem services has extended its influence into spatial planning and landscape ecology, the integration of which can offer an opportunity to enhance the saliency, credibility, and legitimacy of landscape ecology in spatial planning issues. Objective: This paper proposes a methodology to detect red deer habitats for e.g. huntable game. The model is established on remote sensing based value-added information products, the derived landscape structure information and the use of spatially and temporally imprecise in-situ data (e.g. available hunting statistics). In order to realize this, four statistical model approaches were developed and their predictive performance assessed. Methods: Altogether, our results indicate that based on the data mentioned above, modeling of habitats is possible using a coherent statistical model approach. All four models showed an overall classification of > 60% and in the best case 71,4%. The models based on logistic regression using preference data derived from 5-year hunting statistics, which has been interpreted as habitat suitability. The landscape metrics (LSM) will be calculated on the basis of the Global Forest Change dataset (HANSEN et al. 2013b ). The interpolation of landcover data into landscape-level was made with the software FRAGSTAT and the moving window approach. Correlation analysis is used to identify relevant LSM serving as inputs; logistic regression was used to derive a final binary classifier for habitat suitability values. Three model variations with different sets of LSM are tested using the unstandardized regression coefficient. Results lead to an insight of the effect of each LSM but not on the strength of the effect. Furthermore, the predicted outcome is rather difficult to interpret as different units and scales for each LSM are used. Hence, we calculated the fourth model using the standardized regression coefficient. It harmonized the measurement units of the LSM and thus allowed a better comparison, interpretation, and evaluation.Conclusion: Our research reveals that applying a statistical model using coarse data is effective to identify potential red deer habitats in a significant qualitative manner. The presented approach can be analogously applied to other mammals if the relevant structural requirements and empirical habitat suitability data (e.g. home range, biotopes, and food resources) are known. The habitat preferences of red deer are best described by LSM concerning area-relation and wildlifeedge relations. Most important are edges between meadows, pastures or agricultural field and forest, as well as short paths between those elements for food resources. A large proportion of forest is important for species survival and positively influences the occurrence of red deer. Outcomes help to understand species habitat relation and on which scale wildlife perceives the landscape. In addition, they support the practical habitat management and thus the overall species diversity.

Item URL in elib:https://elib.dlr.de/135483/
Document Type:Conference or Workshop Item (Speech)
Title:Remote sensing and GIS based ecological modelling of potential red deer habitats in the test site region DEMMIN (TERENO)
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
McKenna, Amelieamelie.mckenna (at) hnee.deUNSPECIFIED
Schultz, AlfredUniversity for Sustainable Development Eberswalde, GIS and Remote Sensing, Faculty for Forest and EnvironmentUNSPECIFIED
Borg, Erikerik.borg (at) dlr.dehttps://orcid.org/0000-0001-8288-8426
Neumann, MatthiasThünen Institute of Forest Ecosystems, Federal Research Institute for Rural Areas, Forestry and Fisheries, Eberswalde,UNSPECIFIED
Mund, Jan-PeterUniversity for Sustainable Development Eberswalde, GIS and Remote Sensing, Faculty for Forest and EnvironmentUNSPECIFIED
Date:10 May 2020
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
DOI :10.5194/egusphere-egu2020-19953
Page Range:pp. 1-20
Keywords:habitat, red deer (Cervus elaphus), remote sensing, ground-truth, landscape metrics, logistic regression, COPERNICUS, TERENO
Event Title:EGU General Assembly 2020
Event Location:Vienna, Austria
Event Type:international Conference
Event Dates:04.-08. Mai 2020 (ONLINE)
Organizer:European Geosciences Union
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 - Remote Sensing and Geo Research
Location: Neustrelitz
Institutes and Institutions:German Remote Sensing Data Center > National Ground Segment
Deposited By: Borg, Dr.rer.nat. Erik
Deposited On:21 Jul 2020 11:11
Last Modified:21 Jul 2020 11:11

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