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Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces

Affiliation
Helmholtz Centre for Environmental Research (UFZ), Department Computational Landscape Ecology, Germany ; Humboldt University Berlin, Geography Department, Germany
Lausch, Angela;
Affiliation
University of Zurich–Irchel, Remote Sensing Laboratories, Department of Geography, and University Research Priority Program on Global Change and Biodiversity, Switzerland
Schaepman, Michael E.;
Affiliation
University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC), The Netherlands ; Macquarie University, Department of Earth and Environmental Science, Australia
Skidmore, Andrew K.;
Affiliation
Friedrich Schiller University Jena, Department for Earth Observation, Institute of Geography, Germany ; DLR Institute of Data Science, Germany
Truckenbrodt, Sina C.;
Affiliation
Flinders University, College of Science and Engineering, Australia ; Airborne Research Australia (ARA), Parafield Airport, Australia
Hacker, Jörg M.;
Affiliation
Friedrich Schiller University Jena, Department of Physical Geography, Institute of Geography, Germany
Baade, Jussi;
Affiliation
Institut for Geoinformation and Surveying, Department of Architecture, Facility Management and Geoinformation, Germany
Bannehr, Lutz;
Affiliation
German Remote Sensing Data Center–DFD, German Aerospace Center-DLR, Germany ; University of Applied Sciences Neubrandenburg, Geodesy and Geoinformatics, Germany
Borg, Erik;
Affiliation
Helmholtz Centre for Environmental Research (UFZ), Department Monitoring and Exploration Technologies, Germany
Bumberger, Jan;
Affiliation
Helmholtz Centre for Environmental Research (UFZ), Department Monitoring and Exploration Technologies, Germany
Dietrich, Peter;
Affiliation
Martin Luther University Halle-Wittenberg, Department of Remote Sensing, Germany
Gläßer, Cornelia;
Affiliation
Helmholtz Centre for Environmental Research (UFZ), Department Computational Landscape Ecology, Germany ; Humboldt University Berlin, Geography Department, Germany
Haase, Dagmar;
Affiliation
Bavarian Forest National Park, Department of Conservation and Research, Germany ; University of Freiburg, Faculty of Environment and Natural Resources, Germany
Heurich, Marco;
Affiliation
German Aerospace Center (DLR) Microwaves and Radar Institute, Germany
Jagdhuber, Thomas;
Affiliation
MILAN Geoservice GmbH, Germany
Jany, Sven;
Affiliation
Helmholtz Centre for Environmental Research (UFZ), Department Computational Landscape Ecology, Germany
Krönert, Rudolf;
GND
1173645446
Affiliation
Julius Kühn-Institute (JKI), Institute for Crop and Soil Science, Germany
Möller, Markus;
Affiliation
Helmholtz Centre for Environmental Research (UFZ), Department Monitoring and Exploration Technologies, Germany
Mollenhauer, Hannes;
Affiliation
Forschungszentrum Jülich GmbH, Institute of Bio- and Geoscience, Agrosphere (IBG-3), Germany
Montzka, Carsten;
Affiliation
Technical University Dresden, Institut of Photogrammetry and Remote Sensing, Germany
Pause, Marion;
Affiliation
Helmholtz Centre for Environmental Research (UFZ), Department Computational Landscape Ecology, Germany
Rogass, Christian;
Affiliation
Friedrich Schiller University Jena, Department for Earth Observation, Institute of Geography, Germany
Salepci, Nesrin;
Affiliation
Friedrich Schiller University Jena, Department for Earth Observation, Institute of Geography, Germany
Schmullius, Christiane;
Affiliation
University of Nottingham, School of Geography, UK
Schrodt, Franziska;
Affiliation
Helmholtz Centre for Environmental Research (UFZ), Computational Hydrosystems, Germany
Schütze, Claudia;
Affiliation
German Environment Agency, Germany
Schweitzer, Christian;
Affiliation
Helmholtz Centre for Environmental Research (UFZ), Department Monitoring and Exploration Technologies, Germany
Selsam, Peter;
Affiliation
Helmholtz Center Potsdam, German Research Center for Geosciences, Germany
Spengler, Daniel;
Affiliation
Institute for Geography, Geoinformatics and Remote Sensing, Germany ; Leipzig University, Remote Sensing Centre for Earth System Research, Germany
Vohland, Michael;
Affiliation
Helmholtz Centre for Environmental Research (UFZ), Department Computational Landscape Ecology, Germany
Volk, Martin;
Affiliation
Helmholtz Centre for Environmental Research (UFZ), Computational Hydrosystems, Germany
Weber, Ute;
Affiliation
Helmholtz Centre for Environmental Research (UFZ), Department Computational Landscape Ecology, Germany ; Humboldt University Berlin, Geography Department, Germany
Wellmann, Thilo;
Affiliation
Helmholtz Centre for Environmental Research (UFZ), Department Monitoring and Exploration Technologies, Germany
Werban, Ulrike;
Affiliation
Helmholtz Centre for Environmental Research (UFZ), Department Monitoring and Exploration Technologies, Germany
Zacharias, Steffen;
Affiliation
DLR Institute of Data Science, Germany
Thiel, Christian

The status, changes, and disturbances in geomorphological regimes can be regarded as controlling and regulating factors for biodiversity. Therefore, monitoring geomorphology at local, regional, and global scales is not only necessary to conserve geodiversity, but also to preserve biodiversity, as well as to improve biodiversity conservation and ecosystem management. Numerous remote sensing (RS) approaches and platforms have been used in the past to enable a cost-effective, increasingly freely available, comprehensive, repetitive, standardized, and objective monitoring of geomorphological characteristics and their traits. This contribution provides a state-of-the-art review for the RS-based monitoring of these characteristics and traits, by presenting examples of aeolian, fluvial, and coastal landforms. Different examples for monitoring geomorphology as a crucial discipline of geodiversity using RS are provided, discussing the implementation of RS technologies such as LiDAR, RADAR, as well as multi-spectral and hyperspectral sensor technologies. Furthermore, data products and RS technologies that could be used in the future for monitoring geomorphology are introduced. The use of spectral traits (ST) and spectral trait variation (STV) approaches with RS enable the status, changes, and disturbances of geomorphic diversity to be monitored. We focus on the requirements for future geomorphology monitoring specifically aimed at overcoming some key limitations of ecological modeling, namely: the implementation and linking of in-situ, close-range, air- and spaceborne RS technologies, geomorphic traits, and data science approaches as crucial components for a better understanding of the geomorphic impacts on complex ecosystems. This paper aims to impart multidimensional geomorphic information obtained by RS for improved utilization in biodiversity monitoring.

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