@article{f6b7ceab506a453881dc07ee7752ae10,
title = "Remote sensing of geomorphodiversity linked to biodiversity—Part III: Traits, processes and remote sensing characteristics",
abstract = "Remote sensing (RS) enables a cost-effective, extensive, continuous and standardized monitoring of traits and trait variations of geomorphology and its processes, from the local to the continental scale. To implement and better understand RS techniques and the spectral indicators derived from them in the monitoring of geomorphology, this paper presents a new perspective for the definition and recording of five characteristics of geomorphodiversity with RS, namely: geomorphic genesis diversity, geomorphic trait diversity, geomorphic structural diversity, geomorphic taxonomic diversity, and geomorphic functional diversity. In this respect, geomorphic trait diversity is the cornerstone and is essential for recording the other four characteristics using RS technologies. All five characteristics are discussed in detail in this paper and reinforced with numerous examples from various RS technologies. Methods for classifying the five characteristics of geomorphodiversity using RS, as well as the constraints of monitoring the diversity of geomorphology using RS, are discussed. RS-aided techniques that can be used for monitoring geomorphodiversity in regimes with changing land-use intensity are presented. Further, new approaches of geomorphic traits that enable the monitoring of geomorphodiversity through the valorisation of RS data from multiple missions are discussed as well as the ecosystem integrity approach. Likewise, the approach of monitoring the five characteristics of geomorphodiversity recording with RS is discussed, as are existing approaches for recording spectral geomorhic traits/ trait variation approach and indicators, along with approaches for assessing geomorphodiversity. It is shown that there is no comparable approach with which to define and record the five characteristics of geomorphodiversity using only RS data in the literature. Finally, the importance of the digitization process and the use of data science for research in the field of geomorphology in the 21st century is elucidated and discussed.",
keywords = "data science, earth observation, ecosystem integrity, functions, genesis, geodivesity, biodiversity, traits, geomorphic traits, geomorphodiversity, geomorphology, land-use intensity, landforms, multi-mission, remote sensing, spectral traits, structure, taxonomy, terrain, ITC-ISI-JOURNAL-ARTICLE, ITC-GOLD",
author = "Angela Lausch and Schaepman, {Michael E.} and A.K. Skidmore and Eusebiu Catana and Lutz Bannehr and Olaf Bastian and Erik Borg and Jan Bumberger and Peter Dietrich and Cornelia Gl{\"a}sser and Hacker, {Jorg M.} and Rene H{\"o}fer and Thomas Jagdhuber and Sven Jany and Andr{\'a}s Jung and Arnon Karnieli and Reinhard Klenke and Toralf Kirsten and Uta K{\"o}del and Wolfgang Kresse and Ulf Mallast and Carsten Montzka and Markus M{\"o}ller and Hannes Mollenhauer and Marion Pause and Minhaz Rahman and Franziska Schrodt and Christiane Schmullius and Claudia Sch{\"u}tze and Peter Selsam and Syrbe, {Ralf Uwe} and Sina Truckenbrodt and Michael Vohland and Martin Volk and Thilo Wellmann and Steffen Zacharias and Roland Baatz",
note = "Funding Information: Acknowledgments: Our special thanks go to the Helmholtz Centre for Environmental Research— UFZ and the TERENO project funded by the Helmholtz Association and the Federal Ministry of Education and Research for providing the hyperspectral equipment. This work was supported by the Helmholtz Association in the framework of MOSES (Modular Observation Solutions for Earth Systems). At the same time, we truly appreciate the support that we received from the project “GEOEssential—Essential Variables workflows for resource efficiency and environmental management”. The authors also thank the reviewers for their very valuable comments and recommendations. The authors gratefully acknowledge the German Helmholtz Association for supporting the activities. This study was conducted under the the HGF Alliance HA-310 “Remote Sensing and Earth System Dynamics”. U.M. is grateful to the Helmholtz-funded virtual institute, DESERVE. Airborne Research Australia is substantially supported by the Hackett Foundation, Adelaide. One of the ARA ECO-Dimonas was donated by the late Don and Joyce Schultz of Glen Osmond, South Australia. A.J. was supported by project no. TKP2021-NVA-29, which has been implemented with the support provided by the Ministry of Innovation and Technology of Hungary from the National Research, Development, and Innovation Fund, financed under the TKP2021-NVA funding scheme. T.W. wishes to thank the German Federal Environmental Foundation (Deutsche Bundesstiftung Umwelt (DBU) and for the CLEARING HOUSE (Collaborative Learning in Research, Information-sharing, and Governance on How Urban Forest-based Solutions Support Sino-European Urban Futures) Horizon 2020 project (No 1290/2013). Funding Information: Our special thanks go to the Helmholtz Centre for Environmental Research— UFZ and the TERENO project funded by the Helmholtz Association and the Federal Ministry of Education and Research for providing the hyperspectral equipment. This work was supported by the Helmholtz Association in the framework of MOSES (Modular Observation Solutions for Earth Systems). At the same time, we truly appreciate the support that we received from the project “GEOEssential—Essential Variables workflows for resource efficiency and environmental management”. The authors also thank the reviewers for their very valuable comments and recommendations. The authors gratefully acknowledge the German Helmholtz Association for supporting the activities. This study was conducted under the the HGF Alliance HA-310 “Remote Sensing and Earth System Dynamics”. U.M. is grateful to the Helmholtz-funded virtual institute, DESERVE. Airborne Research Australia is substantially supported by the Hackett Foundation, Adelaide. One of the ARA ECO-Dimonas was donated by the late Don and Joyce Schultz of Glen Osmond, South Australia. A.J. was supported by project no. TKP2021-NVA-29, which has been implemented with the support provided by the Ministry of Innovation and Technology of Hungary from the National Research, Development, and Innovation Fund, financed under the TKP2021-NVA funding scheme. T.W. wishes to thank the German Federal Environmental Foundation (Deutsche Bundesstiftung Umwelt (DBU) and for the CLEARING HOUSE (Collaborative Learning in Research, Information-sharing, and Governance on How Urban Forest-based Solutions Support Sino-European Urban Futures) Horizon 2020 project (No 1290/2013). Publisher Copyright: {\textcopyright} 2022 by the authors. Licensee MDPI, Basel, Switzerland.",
year = "2022",
month = may,
day = "9",
doi = "10.3390/rs14092279",
language = "English",
volume = "14",
pages = "1--48",
journal = "Remote sensing",
issn = "2072-4292",
publisher = "MDPI",
number = "9",
}