Crewed aerial surveying: a key tool in modern forest monitoring

This article presents five real-world cases illustrating how crewed aerial platforms are helping to preserve vital ecosystems: forests. With the planet’s forests facing numerous threats, advanced monitoring techniques are essential to monitor and manage them. Crewed aerial platforms offer significant benefits in terms of flexibility, efficiency and coverage.

Covering 31% of the Earth’s surface, forests are crucial ecosystems supporting over 80% of terrestrial biodiversity. In addition, they provide livelihoods for 1.6 billion people, offering both tangible resources – such as food and fuel – and intangible benefits like spiritual and cultural significance. However, climate change threatens these ecosystems, increasing the frequency of extreme weather events and making trees more vulnerable to pests and diseases. In Europe, species like spruce, beech and pine face significant habitat loss. Forests are also impacted by land use changes, urbanization and pollution.

Technology has emerged as a powerful ally in forest monitoring and management in response to these challenges. The Food and Agriculture Organization of the United Nations (FAO), which has been monitoring the world’s forests since 1946, emphasizes the critical role of rapid, rigorous and scalable forest monitoring tools in supporting data-driven policies. Remote sensing, in particular, has become an indispensable technology in forestry, offering valuable insights into forest dynamics, health and changes over time.

Remote sensing technologies in forest mapping

Remote sensing technologies have transformed forest mapping across various platforms. In forest monitoring, applying photogrammetric techniques and data captured by different types of equipment is essential for generating detailed maps, measuring tree heights and crown diameters, assessing forest damage, and monitoring changes in forest structure over time. Multispectral and hyperspectral cameras capture the invisible signatures of vegetation health and species composition. At the same time, thermal sensors detect subtle heat variations that can indicate stress or disease, and also offer a significant advantage in wildfire management by providing real-time, accurate information about fire behaviour and conditions.

Lidar systems, the pillars of forest structure mapping, create intricate 3D canopy architecture and biomass distribution models. Complementing these, microwave sensors like synthetic aperture radar (SAR) penetrate cloud cover and dense canopies, offering insights even in challenging weather conditions. The resolution of SAR is low compared to other technologies, but it can be helpful in high cloud-cover areas.

While satellites offer broad coverage, and uncrewed aerial vehicles (UAVs or ‘drones’) provide high-resolution data for smaller areas, crewed aerial platforms strike a balance. For example, they offer flexibility in flight altitude, and a substantial payload capacity that allows them to carry large-format sensors or multiple smaller advanced sensors simultaneously. This facilitates tailored, multi-layered data collection crucial for comprehensive forest monitoring. Their capacity for rapid response, extended flight duration, and consistent data collection in various conditions makes them invaluable for global forest management and conservation efforts, as illustrated by the five cases below.

Case 1: High-resolution aerial photogrammetry for parasite detection in Poland

In Poland, the fir mistletoe (Viscum album) infestation poses a serious challenge to forest health and timber production. Traditional methods of assessing this issue were slow and labour-intensive, which prompted the Polish company AlterGeo to adopt innovative solutions. It employed high-resolution aerial photogrammetry to efficiently map forest areas at a rate of about 4,000 hectares per hour. This approach is significantly more productive, being 50 to 100 times faster than comparable drone-based methods.

A key factor in this efficiency is the use of the Phase One 280 aerial system, installed on AlterGeo’s ultra-light Alter-Eye aircraft. This setup combines a large-format camera with a stabilizing mount, offering an unprecedented blend of mobility and imaging capability. The system captures images with a ground sample distance (GSD) of 2cm, delivering exceptional detail (Figure 1). The aircraft operates at low altitudes and speeds, allowing for 60% longitudinal photo coverage, and uses special imaging techniques to differentiate trees based on health.

This method allows AlterGeo to identify tree species, sizes and parasitic infestations with precision. The high-resolution images reveal tree health conditions down to individual branches, enabling accurate identification of infested trees and their stages of decline (Figure 2). This innovative technique has the potential to become a standard in forestry, providing more precise mapping and measurements compared to traditional field inventories.

Case 2: Lidar for forest inventory and assessment in Finland

Airborne Lidar has revolutionized forest monitoring, offering extensive coverage and detailed insights into both canopy and sub-canopy structures. Its ability to penetrate forest gaps allows for precise mapping of tree trunks, understorey and topography, enabling the derivation of crucial forest parameters. This technology enhances biodiversity assessments, biomass estimations and forest management strategies across diverse landscapes.

Finland exemplifies the successful adoption of aerial Lidar for nationwide forest inventory, complemented by extensive field data collection. Since 2010, the Finnish Forest Centre (FFC) has conducted comprehensive Lidar surveys, coordinated by the national land survey organization Maanmittauslaitos (MML). This programme combines laser scanning and aerial photography on a six-year cycle, with more frequent photography in most areas. Additionally, field crews measure approximately 800 to 1,000 sample plots within each inventory area, corresponding to a Lidar block. This extensive ground-level data collection constitutes a significant portion of the overall inventory process (Figure 3).

BSF Swissphoto, a member company of the European Association of Aerial Surveying Industries (EAASI), has been instrumental in these efforts. Between 2014 and 2015, BSF Swissphoto, together with a partner, was able to carry out large-scale laser data acquisition over approximately 45,720km² for MML. The company was again commissioned for Lidar flights in 2018 and scanned almost 41,000km² at 1pt/m² in 12 sub-areas in southern to central Finland by the end of 2019. This required a total of around 250 flight hours. Since then, it has been commissioned to collect laser scan data for MML with a density of 5pt/m² for a total area of 109,886km².

This high-density Lidar data enables precise measurement of forest parameters such as tree height, canopy density and biomass. The data is used to create detailed forest stand maps, helping forest managers make informed decisions about harvesting, conservation and sustainable forest management practices.

Case 3: Lidar and AI for storm damage assessment in Switzerland

When a severe storm struck La Chaux-de-Fonds in Switzerland, a swift assessment of forest damage became imperative. Sixense Helimap was tasked with conducting an urgent aerial survey via helicopter just two days after the storm. Following data acquisition, the team from the AI-powered point cloud classification platform Flai applied their FlaiNet artificial intelligence (AI) models for point cloud semantic classification. This offered a detailed view of the damage in both urban and forested areas. Both companies belong to EAASI.

This approach combined aerial mapping with advanced forestry AI models for thorough classification, enabling the direct identification of points associated with fallen tree trunks –even those on the ground, at sharp angles or obscured by other vegetation. Key steps in the process included the 2D rasterization of the fallen tree mask for efficient processing, and the vectorization of more than 10,000 fallen trees or tree parts in the surveyed area (Figure 4).

The resulting vector files were crucial for forest damage management, helping to define the extent of damage and pinpoint areas needing urgent inspection. They also determined the orientation of fallen trunks, streamlining manual processes and aiding forestry operations in planning and executing effective recovery efforts.

Case 4: Hyperspectral data in forest monitoring

Developing accurate tree species identification methods is essential for assessing biodiversity and supporting forest management. With novel approaches, the extent and patterns of species diversity can be mapped and understood more precisely. Hyperspectral data significantly enhances tree species classification by leveraging detailed spectral information, improved algorithms, texture analysis, cross-sensor integration and versatile applications. Unlike multispectral data, hyperspectral imaging captures reflectance across hundreds of narrow spectral bands, enabling the identification of subtle differences in tree species’ spectral signatures. By combining these bands, it is possible to obtain information on the biochemical properties of vegetation and its health status.

In 2022, Group AVT, a member of EAASI, undertook a project to assess tree health in Italy’s Bruneck forest department. The company covered an area of 340km² using hyperspectral data at a GSD of 2-4m, repeating the project a year later (Figure 5). This data enabled the creation of various indices such as the Normalized Difference Vegetation Index (NDVI), Photochemical Reflectance Index (PRI), and Plant Senescence Reflectance Index (PSRI), and produced maps of tree species and dead trees. This information is useful for tracking threats like the bark beetle.

The integration of hyperspectral data with technologies such as Lidar improves classification by providing insights into tree structure and crown characteristics. Its versatility supports applications ranging from field-based identification to large-scale forest monitoring, enabling tailored management and conservation strategies. For instance, tree crown segmentation can also be combined with tree species data for enhanced analysis. While satellites and UAVs can also acquire hyperspectral images, aerial platforms can cover a complete forest in a reasonable timeframe (at most a few days), minimizing time differences between images and offering a spatial resolution that facilitates tree identification and detailed analysis.

Case 5: A digital twin of the rainforest in La Gamba, Costa Rica

Green Cubes, an initiative by Hexagon’s green-tech subsidiary R-evolution, is pioneering the creation of a digital twin of the rainforest in La Gamba, Costa Rica, to support ongoing monitoring and protection efforts. Green Cubes are sponsorable assets that corporate entities can purchase as a way of supporting biodiversity conservation and fulfilling their environmental, social and governance (ESG) commitments. In partnership with La Gamba Tropenstation, an Austrian research station associated with the University of Vienna, R-evolution is mapping 500 hectares to establish the first 125 million Green Cubes.

By employing cutting-edge airborne technology from Leica Geosystems alongside terrestrial Lidar scanners, the project accurately measures and virtually visualizes the rainforest, ensuring continuous conservation efforts. This initiative not only encourages collaboration between scientists and the local community, but also offers forest owners sustainable income opportunities.

The project utilizes the Leica CountryMapper hybrid airborne system, which uniquely combines Lidar and large-format imagery within a single sensor to generate a comprehensive 3D digital landscape of the rainforest (Figures 6 and 7). This system facilitates the quantification of forest volume and the monitoring of vegetation changes over time. By capturing image data across multiple spectral bands, the system registers these with Lidar data to create detailed representations of the rainforest canopy, constructing an index of various species. The data is further refined through integration with high-resolution ground-truthing data from the Leica BLK2GO terrestrial Lidar scanner, setting new benchmarks for analysing tree biomass volume and diameter.

Conclusion

As climate change increasingly threatens forests, advanced monitoring techniques are essential. Crewed aerial platforms offer significant benefits in data collection by efficiently covering large areas and providing broad coverage in a single flight. Their flexibility allows multiple sensors to be deployed simultaneously, collecting comprehensive data across various spectral bands. This capability is advantageous for generating diverse datasets and enhancing the depth and breadth of analysis. Crewed platforms are also valuable in emergencies, offering rapid response and timely data collection crucial for effective disaster assessment and management. The partners of EAASI lead this technological advancement, helping to preserve and sustainably manage forests for future generations.

Further reading

Lidar technology for scalable forest inventory, GIM International Vol. 37, issue 3 https://www.gim-international.com/content/article/lidar-technology-for-scalable-forest-inventory

Lidar surveys in Finland, https://www.metsakeskus.fi/en/open-forest-and-nature-information/collection-of-forest-resource-information

National Land Survey of Finland, https://www.maanmittauslaitos.fi/en