AI for Land Conflict Management: Turning Data into Policy Insights
Land conflicts affect communities, agriculture, forests, and industrial development. Yet information about these conflicts is often scattered across news reports and policy documents, making it difficult for decision-makers to identify patterns and develop effective responses.
In this webinar, we'll explore how AI and Natural Language Processing (NLP) can help identify, analyze, and map land conflicts through a real-world Omdena project.
We'll look at how machine learning was applied to thousands of news articles to identify land conflict events, extract key information, and connect those events with relevant government policies to support informed decision-making.
What You'll Learn
Identifying Land Conflicts with AI: How NLP can analyze news reports to detect and categorize land conflict events.
Extracting Key Information: Identifying conflict locations, stakeholders, events, and underlying issues from unstructured text.
Mapping Conflict Patterns: Visualizing land conflicts across regions and over time to better understand land-use challenges.
Connecting Conflicts to Policies: Using AI to match identified conflicts with relevant government policies and support evidence-based decisions.
Who Should Attend?
This webinar is relevant for policymakers, NGOs, environmental organizations, land management professionals, researchers, and anyone exploring how AI can support sustainable land use and policy decisions.
Join us to discover how AI can transform complex land conflict information into practical insights for better land management and policy responses.
Note: This is a pre-recorded webinar with an AI-generated voice.