The Great Wildebeest Migration is the largest terrestrial mammal migration on our planet, driving multiple ecological processes that support the health of humans and wildlife across the region. However, due to climate and land cover/use change, this natural process is becoming compromised. Developing accurate, cost-effective monitoring methods has quickly become a vital necessity to protect wildebeests and the ecosystem. To address this issue, a recent study by Dr Tiejun Wang demonstrates, for the first time, the capability of satellite remote sensing and machine learning techniques to automatically and accurately count very large populations of wildebeest and zebras across the highly heterogeneous landscape of their migration journey.
MSc Zijing Wu, first author of the paper -We are currently in the first year of implementing the post-2020 global biodiversity framework, which was adopted at the 15 Conference of Parties to the UN Convention on Biological Diversity. We have also recently witnessed the establishment of the Global Sustainability Development Goals as well as the first round of risk assessments on biodiversity and ecosystem services through the Intergovernmental Platform on Biodiversity and Ecosystem Services- explains Tiejun.
AI + Satellite remote sensingNew satellite remote sensing and machine learning techniques offer unprecedented possibilities to monitor global biodiversity with speed and precision. These efficiencies promise to reveal novel ecological insights at spatial scales which are germane to the management of populations and entire ecosystems. Tiejun Wang’s research demonstrates, for the first time, the capability of satellite remote sensing and machine learning techniques to automatically and accurately count very large populations of terrestrial mammals across a highly heterogeneous landscape.
As can be seen in the purple dots, approximately 120.000 individual wildebeests are accurately detected by the algorithm in this large area.
Wildebeests are caught avoiding a tree, presumably due to the presence of lions under its shadow.
The wildebeest are massing along the bank of the Mara River ahead of crossing.
The Great Wildebeest Migration drives multiple ecological processes that support the health of humans and wildlife across the region. In addition, the spectacle of the great migration supports a robust tourism industry, which underpins regional economies across Kenya and Tanzania.
This study yielded highly accurate results and the largest training dataset ever published from a satellite-based wildlife survey (53,906 annotations). Beyond providing a truly open-source and transferable method for satellite-based wildlife surveys, our approach holds extreme promise for scaling spatially to produce the first ever total counts of migratory ungulates in open landscapes. In addition to facilitating total counts for multiple species, the ability to observe expansive herds of migratory ungulates from space presents an exciting opportunity for the study of the ecology of animal aggregations from an entirely novel perspective.
Dr Tiejun Wang is an associate professor of Remote Sensing and Geospatial Ecology in the department of Natural Resources ( Faculty of ITC, University of Twente ). His publication, entitled -Deep learning enables satellite-based monitoring of large populations of terrestrial mammals across heterogeneous landscape-, has been published in the scientific journal Nature Communications. It is open access and can be read online.