English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

The authors apply three methods of prospective modelling to high resolutiongeoreferenced land cover data in a Mediterranean mountain area: GIS approach,non linear parametric model and neuronal network. Land cover prediction to thelatest known date is used to validate the models. In the frame ofspatial-temporal dynamics in open systems results are encouraging andcomparable. Correct prediction scores are about 73 %. The results analysisfocuses on geographic location, land cover categories and parametric distanceto reality of the residues. Crossing the three models show the high degree ofconvergence and a relative similitude of the results obtained by the twostatistic approaches compared to the GIS supervised model. Steps under work arethe application of the models to other test areas and the identification ofrespective advantages to develop an integrated model.

Mod\'elisations prospectives de l'occupation du sol. Le cas d'une montagne m\'editerran\'eenne