moveVis R package released

we are happy to announce the release of the R package “moveVis” for animal movement visualization. Beside the simple animation of movement path also static or dynamic remote sensing data can be included to visualize the dependencies of movement and environmental conditions. We are working on further functions and will provide updates soon.

Please install it with install.packages() and look here for more details:

https://cran.r-project.org/web/packages/moveVis/index.html

https://github.com/16eagle/movevis

moveVis() R package

a first version of the moveVis() R package for animating animal movement tracks with static or dynamic remote sensing data is nearly ready for the CRAN submission. The new package allows to animate your tracks on a blank landscape, a landscape with a static map such as a land cover classification (as seen on the left) or with a dynamic land cover data sets. The dynamic option allows to fit a remote sensing time-series with corresponding landscape information to the movement tracks. This can either be the NDVI or spectral information depending on the data you feed into the command.

The moveVis() R package has been written by Jakob Schwalb-Willmann a M.Sc. student from the EAGLE M.Sc. program.

 

We will announce when the moveVis() package is available through CRAN and can be installed easily in R. We are in the final stage to submit it to CRAN and will provide you with updates.

attendees for 2017 selected

We received again many very good applications for AniMove 2017 at MPI but unfortunately we can only host 20 participants. The AniMove core team worked through all applications and selected the top 20 applicants. All applicants are informed about the outcome. We are looking forward to our next AniMove and will decide during the next AniMove if and when we will have the next one. Due to the fact that AniMove is a non for profit initiative and all lecturer are not paid for AniMove teaching, we have to find a good balance of AniMove activities and the normal work of our lecturer – hence we decided to organize it just once a year. If you have not received an acceptance letter this time, we encourage you to apply again next time.

AniMove logo

After quite some years of AniMove courses and realizing that this idea of one (1) AniMove developed into a series of AniMove science schools, we decided back in summer 2016 during our AniMove at MPI that a logo for AniMove would be great. 6 months later and going through many discussions in 2016 and 2017 we finally have a logo that nicely reflects AniMove topics. We would have loved to have a track, DBB, a satellite, remote sensing or some code in it, but quickly realized that we cannot have a logo which includes all of our topics covered during the 2 intense AniMove weeks. Now we can use it for our upcoming AniMove in August/September at MPI, close to Lake Konstanz, Germany.

Successful AniMove at BIK-F finished

Two intense weeks of AniMove at BIK-F in Frankfurt successfully finished. The highly motivated and skilled attendees from various countries and studying movement patterns of various animals learned a wide range of animal movement analytics as well as spatial data handling and remote sensing. All approaches were explained in detail and all following analysis were done using actual data in an open source environment (R). We are very thankful to Thomas Müller and Chloe Bracis who organised the AniMove this time and we are looking forward to an exiting 2017 with one or more AniMoves! More details about upcoming AniMoves and respective application dates will be posted on our webpage soon. Moreover, we will also update our image galleries for the two AniMoves in 2017 over the christmas break. We hope all attendees apply the learned techniques successfully in their ongoing research and do not hesitate to ask about approaches or problems, especially with R code on your listserv: https://mailman.uni-konstanz.de/mailman/listinfo/animove

AniMove 2017 at BIK-F started

 

The AniMove at BIK-F in Frankfurt started successfully and will cover a variety of animal movement analysis approaches as well as remote sensing and GIS tasks in the next two weeks.  We are very much looking forward to an exciting time and highly interested and motivated to work on animal tracking data, learn the statistical approaches and combining it with environmental data derived through remote sensing. All tasks will be achieved using Open Source software such as R and QGIS. All attendees will be exposed to lots of R coding in this science school. Evening talks are organized as well and introduce general advances within the AniMove topics.animove_2017_bik-f_frankfurt_2animove_2017_bik-f_frankfurt_1

preview of the content of the book “Analysing and Mapping of Animal Movement in R”

the first outline of the content of the book  “Analysing and Mapping of Animal Movement in R” by Kamran Safi and Bart Kranstauber can be checked below. The book will provide theoretical background to animal movement analysis as well as practical hands-on exercises how to analyse the data using R.

 

  1. Introduction to R
  2.  Methods of data collection and implications for analysis
    1.  Tracking technologies
    2.  Movement in space
    3. Loading movement data
  3. Initial exploration of movement data
    1. mapping
    2. temporal organization of the trajectories
    3. spatial organization of the track
    4. unused locations
  4. Trajectory centered analysis
    1. within track analysis
    2. computer-intense models: simulating walks
    3. Auto-correlation structure of trajectories
    4. Segmentation of trajectories
    5. Track analysis
    6. Consensus paths
  5. Area centered analysis
    1. MCP, kernel, Brownian Bridges: From trajectories to utilization distributions
    2. methods of calculating UD overlap
    3. Statistical approaches in area based analysis
  6. Movement in context
    1. geoinformation (remote sensing, raster and vector data)
    2. contextual annotation of trajectories
    3. raster resolution and UD calculation
    4. compositional analysis
    5. species distribution models in movement analysis
    6. step selection functions
  7. Visualisation of animal movement
    1. general mapping of spatio-temporal data
    2. time-space cubes
    3. plotting of additional information
    4. animations
    5. web applications using shiny
    6. more advances options
  8. The future of animal movement analysis

AniMove summerschool application deadline approaching

rhino_freigestellt_Martin_WegmannThe deadline for the AniMove course in 2016 (September 18th – 30th) is approaching. Please submit your applications until March 1st.

Participants learn new skills through lectures and hands-on exercises in data collection, management, analysis and modeling approaches. All necessary state-of-the-art animal movement analysis and remote sensing data methods are covered using OpenSource programs (mainly R). All necessary pre-processing steps for working with these spatial data sets, as well as spatial statistical analysis will be taught (MCP to DBB and BCPA). Especially the linkages of movement and remote sensing data are covered.
In the second week participants will work alone or in small groups on projects with datasets provided by course participants or instructors. Participants are encouraged to bring their own data and research questions to be addressed by themselves or by one of the working groups. This allows to work on different tracking data sets including their own challenges and potential.