new article: Measuring β-diversity by remote sensing: a challenge for biodiversity monitoring

new article: Measuring β-diversity by remote sensing: a challenge for biodiversity monitoring

February 1, 2018

Another article lead by Duccio Rocchini was published on “Measuring β-diversity by remote sensing: a challenge for biodiversity monitoring” in Methods in Ecology and Evolution. Collecting field data is difficult, especially when aiming at modelling biodiversity changes in space and time. This would assume statistically sound sampling schemes. Airborne or satellite remote sensing provide data over large areas, however many biodiversity maps obtained from earth observation have been based on the inference of species richness by regression analysis. Estimating compositional turnover (β-diversity) might add crucial information related to relative abundance of different species instead of just richness. This approach is further discussed in this article. The full article can be read in Methods in Ecology and Evolution.

Rocchini, D, Luque, S, Pettorelli, N et al. (2017) Measuring β-diversity by remote sensing: a challenge for biodiversity monitoring. Methods in Ecology and Evolution. ISSN 2041-210X (In Press)

follow us and share it on:

you may also like:

Successful MSc Defense by Christina Krause

Successful MSc Defense by Christina Krause

Congratulations to our EAGLE student Christina Krause, who successfully defended her MSc thesis titled "Active Learning and Parameter-Efficient Feature Adaptation for Cross-City Seismic Building Type Transfer Using DINOv2 and Street-Level Imagery" on November 12,...

Successful MSc Defense by Marlene Bauer

Successful MSc Defense by Marlene Bauer

Congratulations to our EAGLE student Marlene Bauer, who successfully defended her MSc thesis titled "Robust and Uncertainty-Aware Informal Settlement Mapping – Cross-City Generalisation Across Diverse Urban Morphologies Using High-Resolution Satellite Imagery in...

Help Us Understand Ticks: Join the MONID HABITRACK Study

Help Us Understand Ticks: Join the MONID HABITRACK Study

Lyme borreliosis and tick-borne encephalitis (TBE) are the most common tick-borne diseases in Germany, and they are becoming more relevant. Many infections go unnoticed because they cause mild symptoms or none at all. The MONID HABITRACK project, funded by the BMFTR,...

Setting Up for the 2nd EO4CAM Nutzerworkshop

Setting Up for the 2nd EO4CAM Nutzerworkshop

Right now our staff are busy hauling cases, mounting displays and testing every cable for the 2nd EO4CAM Nutzerworkshop, “Erdbeobachtung für die Klimaanpassung, behördliche Akteure in Bayern”. The doors open tomorrow, and the exhibition...

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