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AniMove R cheat sheets

AniMove R cheat sheets for spatial data handling and general R commands now available: general R commands and R spatial commands


Georg Wittemyer, Eliezer Gurarie, Justin Calabrese and others are joining us for this years AniMove!

AniMove'14 evening talks

we are glad to have Woody Turner (NASA) and Matt Hansen (UMD) as invited evening speakers - more to come


AniMove RT @esa: Start here: RT @Satdecrypter: @esa Sentinel1 data are available for public? where can I find them? cheers.
AniMove RT @IBIS_journal: Information acquisition during migration: A social perspective Auk #ornithology @BioOneNews
AniMove RT @ZSLScience: Learn more about #RemoteSensing for Conservation at our symposium in May: and present a poster on yo…
AniMove RT @AnimalConserv: Rapid assessment of abundance: estimating animal density with track counts using body mass–day range scaling rules http:…
AniMove RT @RolandKays: @icouzin packs the house to talk math & animal movement @ncsu
  • Interested in AniMove 2014? Interested in AniMove 2014?

    Interested in AniMove 2014?

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  • AniMove 2013 AniMove 2013

    impressions of our last AniMove - 2013 at MPI in Germany

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  • Software SkillsSoftware Skills

    Learning how to apply OpenSource software to analyse your animal movement data and remote sensing

  • Evening keynotesEvening keynotes

    Evening talks by international experts

Welcome to the AniMove webpage!

The AniMove activities cover different topics related to the combination of Animal Movement and Remote Sensing for Conservation

Information about our last Summer School AniMove 2013 in Germany and future activities can be found on these pages. Further detailed information about approaches and upcoming events will be added constantly.


... AniMove is a ground-breaking capacity-building contribution [... ] great opportunities for students to learn about the cutting edge of movement ecology and the important insights which it opens for conservation ...


Thomas Brooks,head of IUCN science and Knowledge


Our Aim

AniMove is aiming at providing theory and practical approaches to use animal movement, modelling and remote sensing for Biodiversity research and Conservation. Only OpenSource software will be used and as far as possible also only OpenAccess data. All members of AniMove have long experiences in teaching these topics and are highly committed to support and develop interdisciplinary collaboration in order to provide valuable insights for conservation application and biodiversity research.


Knowledge about applying remote sensing and GIS within Biodiversity research and Conservation application will be taught using OpenSource software only (R, GRASS, QGIS), moreover the basic and advanced skills to handle remote sensing and GIS data plus developing new ecological relevant data sets are covered as well. Spatial modelling techniques (SDMs, Species Distribution Models, using e.g. RandomForest, GLM, GAM or MaxEnt) are covered by AniMove as well, however the main focus will be on analysing animal movement patterns in conjunction with spatial environmental data sets using e.g. step selection function, BCPA, BB. All these technical expertise are embedded in conservation frameworks in order to ensure the real world applicability.


If you are interested in a Summer School in your region, a course at your institute in order to gain valuable information how to get started and going beyond that, please contact us.


We have already started to plan related courses and Summer Schools in upcoming years - please check this page again for updates.


topics of these courses are:

  • theory and practice of AniMove topics
  • remote sensing (different sensors, methods (VI, classification)
  • GIS analysis (data formats, spatial data handling)
  • species distribution models (SDMs: GLM, RF, MaxEnt, GAM etc.)
  • animal movement analysis (BCPA etc.)

using only OpenSource software such as R and GRASS:

  • introduction to R
  • introduction to GRASS
  • spatial data handling in R
  • remote sensing and GIS with GRASS
  • landcover classification, fCover, landcover change with R
  • spatial statistics and modelling with R




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