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Monitoring vegetation- and geodiversity with remote sensing and traits.

Authors :
Lausch, Angela
Selsam, Peter
Pause, Marion
Bumberger, Jan
Source :
Philosophical Transactions of the Royal Society A: Mathematical, Physical & Engineering Sciences. 4/1/2024, Vol. 382 Issue 2269, p1-20. 20p.
Publication Year :
2024

Abstract

Geodiversity has shaped and structured the Earth's surface at all spatio-temporal scales, not only through long-term processes but also through medium- and short-term processes. Geodiversity is, therefore, a key control and regulating variable in the overall development of landscapes and biodiversity. However, climate change and land use intensity are leading to major changes and disturbances in bio- and geodiversity. For sustainable ecosystem management, temporal, economically viable and standardized monitoring is needed to monitor and model the effects and changes in vegetation- and geodiversity. RS approaches have been used for this purpose for decades. However, to understand in detail how RS approaches capture vegetation- and geodiversity, the aim of this paper is to describe how five features of vegetation- and geodiversity are captured using RS technologies, namely: (i) trait diversity, (ii) phylogenetic/genese diversity, (iii) structural diversity, (iv) taxonomic diversity and (v) functional diversity. Trait diversity is essential for establishing the other four. Traits provide a crucial interface between in situ, close-range, aerial and space-based RS monitoring approaches. The trait approach allows complex data of different types and formats to be linked using the latest semantic data integration techniques, which will enable ecosystem integrity monitoring and modelling in the future. This article is part of the Theo Murphy meeting issue 'Geodiversity for science and society'. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1364503X
Volume :
382
Issue :
2269
Database :
Academic Search Index
Journal :
Philosophical Transactions of the Royal Society A: Mathematical, Physical & Engineering Sciences
Publication Type :
Academic Journal
Accession number :
175366185
Full Text :
https://doi.org/10.1098/rsta.2023.0058