Machine Learning for bird migration analysis using python libraries
One fascinating area of research uses GPS to track movements of animals. It is now possible to manufacture a small GPS device that is solar charged, so you don’t need to change batteries and use it to track flight patterns of birds.
The data for this case study comes from the LifeWatch INBO project. Several data sets have been released as part of this project. We will use a small data set that consists of migration data for three gulls named Eric, Nico, and Sanne. The bird_tracking used dataset csv file contains eight columns and includes variables like latitude, longitude, altitude, and time stamps. We will first load the data, visualize some simple flight trajectories, track flight speed, learn about daytime and much, much more.
Aim: Track the movement of three gulls namely – Eric, Nico & Sanne.
Dataset: https://inbo.carto.com/u/lifewatch/datasets
Dependencies: Matplotlib, Pandas, Numpy, Cartopy, Shapely
The repository contains five modules ::::
-->> 1. Visualizing longitude and latitude data of the gulls.
-->> 2. Visualize the variation of the speed of the gulls.
-->> 3. Visualize the time required by the gulls to cover equal distances over the journey.
-->> 4. Visualize the daily mean speed of the gulls.
-->> 5. Cartographic view of the journey of the gulls.