new publication: Satellite remote sensing of ecosystem functions: opportunities, challenges and way forward

new publication: Satellite remote sensing of ecosystem functions: opportunities, challenges and way forward

June 21, 2018

A new publication on “Satellite remote sensing of ecosystem functions: opportunities, challenges and way forward” has been published in the recent issue of RSEC lead by Nathalie Pettorelli. From the abstract: “Societal, economic and scientific interests in knowing where biodiversity is, how it is faring and what can be done to efficiently mitigate further biodiversity loss and the associated loss of ecosystem services are at an all‐time high. So far, however, biodiversity monitoring has primarily focused on structural and compositional features of ecosystems despite growing evidence that ecosystem functions are key to elucidating the mechanisms through which biological diversity generates services to humanity. This monitoring gap can be traced to the current lack of consensus on what exactly ecosystem functions are and how to track them at scales beyond the site level. This contribution aims to advance the development of a global biodiversity monitoring strategy by proposing the adoption of a set of definitions and a typology for ecosystem functions, and reviewing current opportunities and potential limitations for satellite remote sensing technology to support the monitoring of ecosystem functions worldwide. By clearly defining ecosystem processes, functions and services and their interrelationships, we provide a framework to improve communication between ecologists, land and marine managers, remote sensing specialists and policy makers, thereby addressing a major barrier in the field.” read more here:

Pettorelli, N. , Schulte to Bühne, H. , Tulloch, A. , Dubois, G. , Macinnis‐Ng, C. , Queirós, A. M., Keith, D. A., Wegmann, M. , Schrodt, F. , Stellmes, M. , Sonnenschein, R. , Geller, G. N., Roy, S. , Somers, B. , Murray, N. , Bland, L. , Geijzendorffer, I. , Kerr, J. T., Broszeit, S. , Leitão, P. J., Duncan, C. , El Serafy, G. , He, K. S., Blanchard, J. L., Lucas, R. , Mairota, P. , Webb, T. J., Nicholson, E. , Rowcliffe, M. and Disney, M. (2018), Satellite remote sensing of ecosystem functions: opportunities, challenges and way forward. Remote Sens Ecol Conserv, 4: 71-93

 

follow us and share it on:

you may also like:

EORC at the Zugspitze

EORC at the Zugspitze

The CSU Working Group for Environment and Consumer Protection recently visited the Environmental Research Station Schneefernerhaus (UFS) on the Zugspitze. The visit provided an opportunity to present current research activities connected to this unique high-alpine...

UAS analysis of fire and drought stress under controlled conditions

UAS analysis of fire and drought stress under controlled conditions

New update from the field work of our PhD researcher Luisa Pflumm in Kruger National Park! After weeks of fieldwork in the open savanna, Luisa's work now moves into a more controlled setting, a burn chamber experiment carried out together with our collaborators from...

Conference paper of the Super-Test-Site team published

Conference paper of the Super-Test-Site team published

The conference paper "From spatial to platial decision support in planning – Collecting platial experiences of wellbeing" develop from our 'Super test site Würzburg' team has now been published in the proceedings of the Fifth International Symposium on Platial...

Welcome, Prof. Dr. Stefan Dech!

Welcome, Prof. Dr. Stefan Dech!

Big news at the EORC: as of today, October 1st, 2026, Stefan Dech is officially a senior professor at the University of Würzburg, and he's staying right where he belongs, with us at the EORC. Stefan will keep working with us on a whole range of Earth Observation...

bzgl. Art. 50 Verordnung (EU) 2024/1689 (AI Act):

Überwiegend werden eigene originäre Texte und Bilder des EORC genutzt, jedoch sind einige Inhalte von blog post Texten teilweise mit Hilfe von KI überarbeitet worden und einige Bilder sind ganz mit KI erstellt, die jedoch deutlich keine photorealistische Darstellungen abbilden. Aussnahmen sind KI generierte fernerkundliche Datensätze, die explizit für Forschungszwecke mit KI erstellt wurden, hier wird aber durch den assoziierten Text der wissenschaftliche Grund der KI generierten Bilder erläutert.

Share This