4 Ways Big Data and Machine Learning Are Helping Conservation

The field of computational sustainability is using machine learning algorithms in a bid to help conservation efforts. By analysing and extracting valuable insights from sets of data gathered from environmental fields. It’s not just about having large data sets or advanced pattern-finding algorithms, but how we use them. The following projects highlight how Machine Learning and Big Data are helping conservation efforts of all kinds.

Earthcube Project

The ambitious Earthcube project has been in development for the past five years. It aims to produce a living 3D replica of Earth to serve scientists of different disciplines. It has been built upon interconnected projects using computer science, big data, and geoscience. There is a gold mine of data when it comes to Earth sciences that have been collected over years of study.

Research that has the potential to benefit environmental causes greatly. Earthcube funds a variety of projects, such as the Coral Reef Science & Cyberinfrastructure-Network (CRESCYNT). By using species databases, image analysis software and 3d mapping, they can monitor the decline of the coral reef. Problems like structural changes, disturbances, coral disease, sea temperatures, and coral bleaching. The research will allow for a greater understanding to help protect and preserve what we can of the coral reef.


The Great Elephant Census

Since 2006, over 12,000 elephants have been killed each year in Africa alone. The protection of ecosystems is vital not only to wildlife but the communities around them and data is helping. In 2014, Microsoft co-founder Paul Allen launched a 2-year survey, The Great Elephant Census. The census has a goal to achieve a greater understanding of the numbers of elephants in Africa. Teams including 90 researchers traversed over 285,000 miles of the African continent, over 21 countries conducting this research. It’s resulted in one of the largest raw data sets of its kind.

This data has informed African conservation efforts. Reserves and wildlife centers have received more funding and rangers to support operations and security. The survey has shown that elephant numbers are down by 30% in seven years. Now showing 352,271 African elephants in 18 countries. The differentials in numbers highlight the need for ongoing monitoring to make ensure better response times to emergency situations. Big Data is having a positive impact on conservation efforts and will help better protect the Elephant population of Africa.



Launched in 2002, the eBird app lets users record bird sightings as they come across them and input this data into the app. The aim is to help create usable Big Data sets valuable to professional and recreational bird watchers. These data sets are shared with professionals across various disciplines. People such as teachers, land managers, ornithologists, biologists and conservation workers. They’ve used the data so far to create BirdCast. A regional migration forecast that gives real-time predictions of bird migration for the first time ever. This uses machine learning and computer vision techniques to follow and predict migration and roosting patterns of different species of bird. This will benefit conservation efforts greatly by providing more accurate intelligence for land planning and management. Moreover, it will allow areas prone to roosting bird gatherings time for necessary preparations.


Leafsnap is an electronic field guide app available in North Eastern America, Canada, and the UK. It’s been developed by researchers from Columbia University, the University of Maryland and the Smithsonian Institution. The app uses visual recognition algorithms, derived from machine learning facial recognition techniques and allows users to identify species of trees from pictures of their leaves. The imaging system takes into consideration other signifiers such as flowers, fruits, and bark. The datasets available with Leafsnap includes 185 tree species, 23147 lab images, and 7719 field images.

This data is set to grow as the app develops. As stated on their website, Leafsnap aims to ‘build an ever-greater awareness of and appreciation for biodiversity.’ The City College of New York is finding educational benefits from using the app to support their curriculum. Data produced by app users and researchers can help conservation efforts through understanding how natural and man-made disasters can affect tree populations, distribution, and growth patterns. Through a greater understanding of the natural world around us, we can work towards conserving it and data is playing a huge part in that.

Get in touch if you can think of any other great ways big data and machine learning is shaping conservation!

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