Software
A variety of software apps, tools and packages are designed to work with data in Movebank format. We also offer management and analysis tools integrated within Movebank, including the Env-DATA System for annotating environmental data and the beta release of the MoveApps analysis platform. All of these resources are free of charge unless noted otherwise. For questions about these tools, please contact the maintainer listed below. To have your software listed, contact support@movebank.org.
Animal Tagger App
The Animal Tagger app allows researchers in the field to collect capture and deployment information. Information can be stored and edited offline, sent to a central platform for further editing, and then exported or sent directly to a related study in Movebank. In combination with the Animal Tracker app (below), researchers can use this platform to manage photographs, correspondence, and other notes related to their data in Movebank.
Download for Android for iPhone and iPad
Maintained by Couchbits
Animal Tracker App
The Animal Tracker app allows you to follow up-to-date movements of live-tracked animals in Movebank on your mobile. Users can animate recent movements, view information about research projects and individual animals, and contribute images of the animals or their habitat. The app can also be used to privately share non-public data, intended to help researchers in the field. In combination with the Animal Tagger app (above), researchers can use this platform to manage photographs, correspondence, and other notes related to their data in Movebank.
Download for Android for iPhone and iPad
Maintained by Couchbits
ctmm: Continuous-Time Movement Modeling
The R package ctmm provides functions for identifying, fitting, and applying continuous-space, continuous-time stochastic movement models to animal tracking data. The package implements all major continuous-time models that have been applied to animal movement. In comparison to discrete-time and correlated-random-walk models, continuous-time models are insensitive to sampling schedule and can account for a wider range of autocorrelation structures. Fitted models can be leveraged to estimate home range, interpolate missing data, filter/smooth errors, etc.
Download at https://cran.r-project.org/web/packages/ctmm/index.html or access the R Shiny app at https://ctmm.shinyapps.io/ctmmweb
Maintained by Chris Fleming and Justin Calabrese at the Smithsonian Institute
Additional resources:
Calabrese JM, Fleming CH, Gurarie E. 2016. ctmm: an r package for analyzing animal relocation data as a continuous-time stochastic process. Methods Ecol Evol. 7(9):1124-32. http://dx.doi.org/10.1111/2041-210X.12559
Other citatons listed at r-project.org.
Douglas Argos Filter
The Douglas Argos Filter can be used to filter Argos-Doppler-based location estimates, removing inaccurate locations based on user-defined thresholds that can be tuned to species' movement behaviors and research questions. Users can choose from three filtering methods:
- Maximum redundant distance (MRD) filter: retains locations based on spatial redundancy between consecutive locations
- Distance angle rate (DAR) filter: retains spatially redundant locations and locations that pass movement rate and turning angle tests
- Hybrid filter: optimally combines the MRD and DAR results by extracting DAR outcomes only during migration periods and combines them with all MRD outcomes.
This program was developed by David Douglas at the U.S. Geological Survey and has been implemented directly in Movebank.
Download at https://www.usgs.gov/media/files/douglas-argos-filter-algorithm or run in Movebank
Maintained by Movebank and David Douglas at the U.S. Geological Survey Alaska Science Center
Additional resources:
Instructions from Movebank's user manual
User manual from the U.S. Geological Survey
Douglas D, Weinzierl R, Davidson SC, Kays R, Wikelski M, Bohrer G. 2012. Moderating Argos location errors in animal tracking data: Methods Ecol Evol. 3(6):999-1007. http://dx.doi.org/10.1111/j.2041-210X.2012.00245.x
DynamoVis
A desktop Java program to dynamically visualize and animate tracking data along with other data attributes. Supports exploratory analysis and export of videos for presentation. This program automatically reads .csv files downloaded from Movebank.
Download at https://github.com/move-ucsb/DynamoVis/releases
Maintained by Somayeh Dodge at the University of California Santa Barbara
Additional resources:
Dodge S, Toka M, Bae CJ. 2021. DynamoVis 1.0: an exploratory data visualization software for mapping movement in relation to internal and external factors. Mov Ecol. 9:55. https://doi.org/10.1186/s40462-021-00291-5
ECODATA
The Environmental COntextual-Data And TrAk (ECODATA) Prepare and Animate apps support movement ecology data exploration and analysis, integrating information from remote sensing and other geospatial datasets. ECODATA-Prepare processes large animal tracking, remote sensing, and other geospatial data files for subsequent analysis. ECODATA-Animate is a MATLAB® App that offers custom static and animated visualizations of animal movements with environmental background layers.
Download at https://www.movebank.org/cms/movebank-content/ecodata#download_and_support
Maintained by Justine Missik at the Ohio State University
Additional resources:
Env-DATA
The Environmental Data Automated Track Annotation (Env-DATA) system allows users to request annotation of their location data with environmental variables
Use directly from the Studies Page
Maintained by Movebank
Additional resources
Firetail
The stand-alone software program Firetail offers advanced visualization and analysis tools for location and acceleration data, with support for large, high-resolution datasets. A built-in AI FireSOM supports interactive interpretation and annotation of acceleration data, with a semi-automated workflow that enables annotation at unprecedented scale and can be adapted to a wide range of species and behaviors. You can customize underlying feature sets and capture details using time-restricted models. Broad support for contextual data (tag sensors, BMNG, NDVI, chlorophyll, Blue Marble) and orientation (IMU) data allows visualization, animation, and interpretation of predictions within Firetail. The Free Edition supports up to 100K GPS fixes and 1 million ACC samples without any time limit. For larger datasets, a license can be purchased that includes updates for 12 months.
Download at http://www.firetail.de
Maintained by Schäuffelhut Berger Software Engineering
Additional resources:
FLightR
The R package FLightR computes estimated animal paths using light-level data from solar geolocators using a hidden Markov model via a particle filter algorithm. The package provides a FlightR2Movebank function to summarize location estimates for import to Movebank.
Download at https://cran.r-project.org/src/contrib/Archive/FLightR
Maintained by Eldar Rakhimberdiev at the University of Groningen
Additional resources:
Light-level geolocation analyses manual
Lisovski S, Bauer S, Briedis M, Davidson SC, Dhanjal-Adams KL, Hallworth MT, Karagicheva J, Meier CM, Merkel B, Ouwehand J, Pedersen L, Rakhimberdiev E, Roberto-Charron A, Seavy NE, Sumner MD, Taylor CM, Wotherspoon SJ, Bridge ES. 2020. Light-level geolocator analyses: a user’s guide. Journal Anim Ecol. 89(1):221-36. https://doi.org/10.1111/1365-2656.13036
Rakhimberdiev E, Saveliev A, Piersma T, Karagicheva J. 2017. FLightR: an R package for reconstructing animal paths from solar geolocation loggers. Methods Ecol Evol. 8(11):1482-7. https://doi.org/10.1111/2041-210X.12765
Rakhimberdiev E, Senner NR, Verhoeven MA, Winkler DW, Bouten W, Piersma T. 2016. Comparing inferences of solar geolocation data against high‐precision GPS data: annual movements of a double‐tagged black‐tailed godwit. J Avian Biol. 47(4):589-96. https://doi.org/10.1111/jav.00891
Rakhimberdiev E, Winkler DW, Bridge E, Seavy NE, Sheldon D, Piersma T, Saveliev A. 2015. A hidden Markov model for reconstructing animal paths from solar geolocation loggers using templates for light intensity. Movement Ecology 3:25. https://doi.org/10.1186/s40462-015-0062-5
GeoLight
The R package GeoLight provides functions to determining location based on data obtained from solar geolocators (light-level loggers). Functions allow users to
- determine sunrise and sunset
- determine movement and residency periods based on sun events independent of any seasonal inaccuracy (behavior, vegetation, weather) and equinox periods
- choose from period-specific calibration methods (civil twilight calibration, in-habitat-calibration and Hill-Ekstrom calibration)
- calculate geographic positions
Mapping and graphical tools are available for most functions.
Download at https://cran.r-project.org/src/contrib/Archive/GeoLight
Maintained by Simeon Lisovski, Simon Wotherspoon, Michael Sumner, Silke Bauer, Tamara Emmenegger, and the Swiss Ornithological Institute
Additional resources:
Light-level geolocation analyses manual
Lisovski S, Bauer S, Briedis M, Davidson SC, Dhanjal-Adams KL, Hallworth MT, Karagicheva J, Meier CM, Merkel B, Ouwehand J, Pedersen L, Rakhimberdiev E, Roberto-Charron A, Seavy NE, Sumner MD, Taylor CM, Wotherspoon SJ, Bridge ES. 2020. Light-level geolocator analyses: a user’s guide. Journal Anim Ecol. 89(1):221-36. https://doi.org/10.1111/1365-2656.13036
Lisovksi S, Hahn S. 2012. GeoLight—processing and analysing light-based geolocator data in R. Methods Ecol Evol. 3(6):1055–9. https://doi.org/10.1111/j.2041-210X.2012.00248.x
move2
The R package move2 provides functions to access data stored in Movebank's format and create move objects in R, as well as tools to visualize and statistically analyze animal movement data. Functions allow users to
- access data in the Movebank format, including tabular text files and data stored at movebank.org for which the user has access rights
- calculate track metrics as speed, distance, turning angle, time lags
- filter tracks for outliers, duplicated timestamps
- visualize tracks as points and lines, easily integrated into any ggplot function
Download at https://bartk.gitlab.io/move2
Maintained by Bart Kranstauber (University of Amsterdam) and Anne Scharf (Max Planck Institute of Animal Behavior)
Additional resources:
See http://animove.org.
Kranstauber, B, Safi K, Scharf AK. 2024. move2: R package for processing movement data. Methods Ecol Evol. 15(9):1561-1567. https://doi.org/10.1111/2041-210X.14383
Kranstauber B, Kays R, LaPoint SD, Wikelski M, Safi K. 2012. A dynamic Brownian bridge movement model to estimate utilization distributions for heterogeneous animal movement. J Anim Ecol. 81(4):738-746. https://doi.org/10.1111/j.1365-2656.2012.01955.x
Kranstauber B, LaPoint S. 2014. The R package move: tutorial presented at the Symposium on Animal Movement and the Environment, May 7 2014. www.youtube.com/watch?v=izSfH8e_lX4
Kranstauber B. 2014. Dynamic Brownian bridge movement models: tutorial presented at the Symposium on Animal Movement and the Environment, May 7 2014. www.youtube.com/watch?v=2UreY2ViVTE
LaPoint S. 2014. Animal-defined movement corridors: tutorial presented at the Symposium on Animal Movement and the Environment, May 7 2014. www.youtube.com/watch?v=9Kr_mEtLdwA
movekit
Movekit is a software package written in Python for the processing and analysis of movement data, including data pre-processing, extraction of movement metrics, group-level analysis, network analysis and creating interactive graphics of results. The package supports data in Movebank and other formats.
Download at https://github.com/dbvis-ukon/movekit
Maintained by the Data Analysis and Visualization Group at the University of Konstanz
Additional resources:
movepub
The R package movepub offers functions to transform GPS tracking data in Movebank format to Frictionless Data Packages and Darwin Core.
Download at https://github.com/inbo/movepub
Maintained by Peter Desmet at the Research Institute for Nature and Forest (INBO)
Additional resources:
van der Kolk H-J, Desmet P, Oosterbeek K, Allen AM, Baptist MJ, Bom RA, Davidson SC, de Jong J, de Kroon H, Dijkstra B, et al. 2022. GPS tracking data of Eurasian oystercatchers (Haematopus ostralegus) from the Netherlands and Belgium. ZooKeys. 1123:31–45. https://doi.org/10.3897/zookeys.1123.90623
MoveApps
MoveApps is a free no-code data analysis platform where users can draw their data directly from Movebank and build workflows to automate analysis.
Use at moveapps.org
Maintained by Couchbits
Additional Resources
Kölzsch A, Davidson SC, Gauggel D, Hahn C, Hirt J, Kays R, Lang I, Lohr A, Russell B, Scharf AK, et al. 2022. MoveApps: a serverless no-code analysis platform for animal tracking data. Movement Ecol. 10(30). https://doi.org/10.1186/s40462-022-00327-4
Movebank Acceleration Viewer
The Acceleration Viewer visualizes acceleration and GPS data that were acquired by e-obs and madebytheo tags. In addition, users can manually annotate information, such as behavioral categories, to the acceleration datasets. GPS data can be visualized in a timeline along with acceleration values and linked to a view of the track on a map with satellite imagery. Access data directly from Movebank or from your computer. This software has been superceded by the Firetail program.
Download at the User Manual
Maintained by Matthias Berger at Schaeuffelhut Berger GmbH
Additional resources:
See the Movebank Acceleration Viewer Manual.
MoveVis
The R package MoveVis allows you to create animations of animal movements with web-based maps or environmental data in the background. Works with Movebank-format data.
Download at https://cran.r-project.org/web/packages/moveVis/index.html
Maintained by Jakob Schwalb-Willmann
Additional resources
See http://movevis.org and http://animove.org.
Schwalb-Willmann J, Remelgado R, Safi K, Wegmann M. 2020. moveVis: Animating movement trajectories in synchronicity with static or temporally dynamic environmental data in R. Methods Ecol Evol. 11(5):664-669. https://doi.org/10.1111/2041-210X.13374
SGAT
The R package SGAT estimates animal movements based on data from satellite tags and solar geolocators (light-level loggers). The package provides an SGAT2Movebank function to summarize location estimates for import to Movebank.
Download at https://rdrr.io/github/SWotherspoon/SGAT/man/SGAT-package.html
Maintained by Simon Wotherspoon at the University of Tasmania
Additional resources
Light-level geolocation analyses manual
Lisovski S, Bauer S, Briedis M, Davidson SC, Dhanjal-Adams KL, Hallworth MT, Karagicheva J, Meier CM, Merkel B, Ouwehand J, Pedersen L, Rakhimberdiev E, Roberto-Charron A, Seavy NE, Sumner MD, Taylor CM, Wotherspoon SJ, Bridge ES. 2020. Light-level geolocator analyses: a user’s guide. Journal Anim Ecol. 89(1):221-36. https://doi.org/10.1111/1365-2656.13036
TAME: Tagged Animal Movement Explorer
TAME is an interactive web-based data visualization tool for rapid exploration of spatial and temporal patterns of tagged animal movements. Datasets can be dynamically filtered with linked histograms (cross-filters) of derived and user-supplied variables. As users filter data with one or more variables, the filtered subset of tagging observations is redrawn in near-real-time on the map. TAME is geared toward small to medium sized datasets (< 100,000 rows) loaded as a .csv file. The default mapping of variable names is coded to work with data in the Movebank format. Users can optionally register for an account to save or publish projects.
Access at https://www.usgs.gov/apps/ecosheds/tame
Mantained by Jeffrey Walker and Benjamin Letcher at the U.S. Geological Survey
Additional resources
Wildlife Tracker Web App
GIS4 Wildlife offers personalized and customized web platforms for wildlife movement analytics. Movement analysis is performed by movingpandas algorithms and updated on the fly with satellite live feeds from Movebank. The platform can be embedded as a real-time web map animation in websites with customized study information.
Access at https://www.gis4-wildlife.com
Maintained by Bryan R. Vallejo at GIS4 Wildlife
Additional resources