EAASI companies: Sixense Helimap and Flai
Project Overview
In the wake of a powerful storm that struck La Chaux-de-Fonds, Switzerland, Sixense Helimap and Flai rapidly mobilized to assess widespread forest damage. Conducted just two days after the storm, this aerial survey utilized advanced crewed helicopter technology and AI-powered point cloud classification to deliver critical insights.
Data analysis and damage assessment were requested by Service de la Géomatique, which is a part of the Neuchatel canton, Switzerland. To provide the services to the community, they extensively use airborne, mobile and bathymetry LiDAR data.
Technical Solution
The assessment leveraged high-resolution airborne LiDAR data captured via helicopter to map the affected area comprehensively. The Flai team was tasked with point cloud classification and initial vectorization of all fallen trees marked by the classification procedure. Utilizing FlaiNet, an AI-powered semantic classification platform, the team conducted advanced forestry AI modeling to identify fallen tree trunks with exceptional precision.
Key techniques included:
Semantic Classification: FlaiNet identified points associated with fallen trunks, even those at sharp angles or partially obscured by vegetation.
2D Rasterization: The fallen tree mask was rasterized for efficient processing, ensuring accuracy across the storm-damaged landscape.
Vectorization: Over 10,000 fallen trees or parts were vectorized, delivering a detailed and actionable dataset.
This seamless integration of aerial mapping and AI transformed raw LiDAR data into a detailed damage assessment map, highlighting areas requiring urgent intervention.
Image courtesy: Flai. Identified and vectorised trunks are shown by cyan vectors.
Project Benefits
The project delivered precise vector files that proved invaluable for forest management teams. These files enabled authorities to:
Define the storm’s impact across urban and forested areas.
Prioritize areas requiring immediate inspection and intervention.
Determine the orientation of fallen trunks, streamlining forestry operations and recovery planning.
The survey supported timely and efficient recovery efforts by accelerating the typically labor-intensive damage assessment process, reducing costs and resource use.
Future Outlook
The La Chaux-de-Fonds project highlights the critical role of crewed aerial surveys in disaster response, especially when large-scale environmental damage demands rapid assessment. As Charlène Negrello of Sixense Helimap noted during a recent EAASI panel, “The integration of AI and aerial data is transforming how we address environmental challenges, enabling faster and more effective solutions.”
This method, which merges crewed aerial surveys with cutting-edge AI technology, establishes a new standard for effective storm damage evaluation and recovery planning. It highlights the distinct advantages of aerial mapping in providing extensive, high-resolution data that cannot be matched by satellite or drone technologies. In the future, the combination of AI-driven tools such as FlaiNet with crewed aerial surveys is set to transform forest management and disaster response in areas susceptible to environmental emergencies.
This case study appeared in the article Crewed aerial surveying: a key tool in modern forest monitoring published by GIM International.
Flai has also published an article about this case: Forest damage assessment from LiDAR point cloud using Artificial Intelligence
Learn more about how other EAASI members utilize crewed aerial technology to address global challenges in our Use Cases series, a dedicated section showcasing real-world applications, and achievements by EAASI’s diverse members.
This collection of use cases highlights the unique advantages and capabilities of crewed aerial surveying in various fields, from environmental monitoring to infrastructure planning.
Comments