How can AI help predict locust outbreaks in West Africa?

A data scientist from Mali is part of a team using machine learning to help predict, and hopefully stop, devastating locust swarms in West Africa's Sahel region.

During West Africa's last major locust outbreak from 2003 to 2005, authorities spent more than $450 million trying to end the epidemic, which caused an estimated $2.5 billion in crop damage. Another disaster loomed in 2012, threatening food security for more than 50 million people, but successful control efforts mitigated the impact.

Fatoumata Haidara, a machine learning engineer with the SERVIR West Africa Small Scale Innovation Grant Program, recognized the need for better locust predictions, leading to the integration of machine learning techniques to improve locust prediction accuracy on the P_Locust platform. It explains.

“This work is crucial as locust swarms can devastate crops, leading to severe food shortages and economic instability. By improving the platform, we aim to provide more accurate predictions and enable timely interventions that protect agricultural livelihoods,” she says.

Haidara explains that her research focuses on analyzing weather patterns, vegetation conditions, and ecological conditions to predict locust outbreaks. By incorporating diverse environmental indicators and real-time data, researchers can alert decision makers earlier and more accurately.

“This is critical for early intervention, which can help prevent crop damage and ensure food security and economic stability for communities in West Africa,” she says. “The platform's improved accuracy and extended turnaround times will enable policymakers and communities to make proactive decisions to prevent crop damage. Impact of locust outbreaks is.”

Machine learning in Mali

Haidara grew up in Mali's wealthy agricultural city of Sikasso, where his parents owned a field and often helped water the vegetables.

“This experience sparked my interest in automating agricultural operations to simplify them and protect crops from climate hazards. This early fascination led me to graduate studies in physics and ultimately I decided to pursue a career in artificial intelligence applied to climate science,” she says.

Haidara explains that her current role as a machine learning engineer allows her to address the challenges of managing and mitigating the impacts of locust infestations, which can be devastating to local crops and livelihoods.

“It is critical for scientists in the Global South to investigate solutions to global challenges because they rely on their local backgrounds, cultures, and specific Because we fundamentally understand the problem, this deep local insight allows us to develop better and more sustainable solutions,” she added, empowering local scientists. He added that giving builds scientific capacity and prepares communities to independently tackle future challenges.

Drones could reduce conflict between farmers and herders in Benin

Elsewhere in West Africa, another group of researchers is using high-tech solutions to help farmers and pastoralists. Daniel David Tossou, director of ATLAS-GIS Sa and Benin Flying Lab, said the team's drone flights created high-resolution land-use maps and then conducted topographical surveys to identify areas along cattle transport routes. He says he has created a plot map of the estimated owners of the land.

For decades, the expansion of farmland due to lack of livestock grazing space and poor soil has led to conflicts between pastoralists and farmers, but now drones are helping to navigate routes that minimize conflict. It helps you find it.

“The 156-kilometer corridor is currently demarcated with cement markers, and provincial and municipal authorities have issued ordinances encouraging pastoralists to use the corridor,” Tosso said, adding that conflicts between farmers and herders continue. He added that the corridor issue is a national concern. Causing death or serious damage with loss of life.

“Awareness campaigns are being carried out in the areas where the corridor is located using mass media (sensitization and information panels) and village meetings,” he says.Unlike other areas where the phenomenon is still prevalent, the results are dramatic.