Group15 Report

Bird, Where Art Thou?
An interactive visual analytics approach to bird migration

Proposal	Poster	Application	Report	Project Groups

MOTIVATION

Animal migration has long received much attention as a research topic in biology. Information about animal movement serves to allow us to understand animal behavior and their interactions with each other and the environment. In addition, it allows us to address environmental challenges such as climate and land use change.

Understanding animal migration helps conservationists to conserve these animals through the protection of their habitats and their resources.

We utilize trajectory data to provide an interactive visual analytics approach for valuable insights into the migration of these animals.

OBJECTIVES

We present an interactive visual approach to explore and analyze animal movement data. We applied this approach to a data set of Osprey bird migration flows.

Through this project, we hope that ecologists and conservationists alike will be able to gain insights into the following:

• Bird migration (both as a group and individual) flight path over a period of time. • How differences in individual characteristics (e.g. female vs male, juvenile vs adult) affect flight behavior. • The home range a of these birds.

To achieve the objectives above, we used trajectory data available in the Osprey data set.

REVIEW AND CRITICS OF PAST WORKS

There are plenty of studies on animal migration, each which comes with its own different set of visualization tools. These are customized tools which have been designed by the researchers of the studies in the course of the study. The links to some of these tools are no longer working and they do not allow for upload of user data set, further limiting its widespread adoption for other animal migration studies.

Our application makes use of RStudio, a free popular open software and Shiny which make interactive web applications for visualizing data. In order to use the application, the researchers can easily download the required software from the internet. They can make use of their own animal movement data to extract the migration flows which they wish to analyze.

DEMONSTRATION

The purpose of this section is to demonstrate the main aspects of our application using some use cases.

DISCUSSION

Our application has been designed to study animal movement using bird migration as an example. Utilizing trajectory data from the Osprey data set, we developed our application to include the following visualizations:
• Group movement of birds
• Individual movement of birds
• Home range of birds
• Directions the birds traveled in

The user will be able to derive findings from the visualizations. Findings from our use cases includes the following:
• Flight patterns of the birds: From March – April, the birds travel from South America to North America and vice versa from September – October.
• Ground Speed by age: The median speed of adults is higher than juveniles.
• Ground speed by sex: The median speed of females is higher than males.

FUTURE WORK

Our current work only looks at the Osprey population in North and South America. Using the application, the study could be extended to Osprey found in other regions of the world. In addition, the application could also be used to study the flight migration of other bird types.

Environmental data such as weather (e.g. wind speed and temperature), sea currents, daylight and night should be incorporated into the study, to better understand how the environmental conditions affects their migration.

To incorporate stopover sites in the application. Stopover sites are where birds pause during their migratory flights. These serve as areas for the birds to rest and forage. Birds often use the same stopover sites each year, knowing where their stopover sites are will allow us to better protect their habitats. Algorithmic calculations could be used to derive stopover sites.

A home range is the area in which an animal lives and moves on a periodic basis. There are various ways of calculating the home range. To build into the application different methods of deriving home range such as minimum convex polygon (MCP), kernel density estimation (KDE), and local convex hull (LoCoH).