new article: Adding structure to land cover – using fractional cover to study animal habitat selection

new article: Adding structure to land cover – using fractional cover to study animal habitat selection

December 30, 2014

our new article just got published online in “Movement Ecology” on the added value of fractional cover analysis using remote sensing data to explain spatio-temporal animal movement patterns. More in-depth analysis are needed to compare and evaluate the importance of different remote sensing derived parameters for this kind of analysis.

Linking animal movements to landscape features is critical to identify factors that shape the spatial behaviour of animals. Habitat selection is led by behavioural decisions and is shaped by the environment, therefore the landscape is crucial for the analysis. Land cover classification based on ground survey and remote sensing data sets are an established approach to define landscapes for habitat selection analysis.We investigate an approach for analysing habitat use using continuous land cover information and spatial metrics. This approach uses a continuous representation of the landscape using percentage cover of a chosen land cover type instead of discrete classes. This approach, fractional cover, captures spatial heterogeneity within classes and is therefore capable to provide a more distinct representation of the landscape. The variation in home range sizes is analysed using fractional cover and spatial metrics in conjunction with mixed effect models on red deer position data in the Bohemian Forest, compared over multiple spatio?temporal scales.resized_forest_hymap_model_NZ

We analysed forest fractional cover and a texture metric within each home range showing that variance of fractional cover values and texture explain much of variation in home range sizes. The results show a hump?shaped relationship, leading to smaller home ranges when forest fractional cover is very homogeneous or highly heterogeneous, while intermediate stages lead to larger home ranges.

The application of continuous land cover information in conjunction with spatial metrics proved to be valuable for the explanation of home-range sizes of red deer.

 

Mirjana Bevanda, Ned Horning, Bjoern Reineking, Marco Heurich, Martin Wegmann and Joerg Mueller

Adding structure to land cover – using fractional cover to study animal habitat selection

Movement Ecology 2014, 2:26

http://www.movementecologyjournal.com/content/2/1/26/abstract

follow us and share it on:

you may also like:

Teaching activities in the Arctic: EORC at UNIS on Svalbard

Teaching activities in the Arctic: EORC at UNIS on Svalbard

It started a few years ago, when Mirjana Bevanda built up a collaboration with partners at UNIS, the University Centre in Svalbard. Jakob Schwalb-Willmann joined soon after, and today a growing group from EORC heads north to teach there, including Antonio...

A First Get-Together with the New EAGLE Generation 🦅

A First Get-Together with the New EAGLE Generation 🦅

A new EAGLE generation means new faces, new ideas, and the start of another journey in Earth Observation. And what better way to kick things off than with a relaxed evening at the pub? Our first social event brought together the new students, older EAGLE generations,...

An Evening with Professor Jarugu Narasimha Moorthy

An Evening with Professor Jarugu Narasimha Moorthy

It was a pleasure to have dinner with Professor Jarugu Narasimha Moorthy, who received an honorary doctorate from the Faculty of Chemistry and Pharmacy in recognition of his achievements. The ceremony took place on 29 September 2026 in the Chemistry Central Building....

Ecology or Sampling Bias? A Roadside Perspective on Invasion Risk

Ecology or Sampling Bias? A Roadside Perspective on Invasion Risk

At the 2026 annual meeting of the AK Fernerkundung (German Working Group on Remote Sensing), which was hosted by the Thünen Institute in Braunschweig, our EORC team member Dr. Insa Otte presented research results on sampling bias in species distribution models in...

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