Forest work can be time-consuming and expensive. By modeling a digital twin of the forest from drone data, forestry practitioners can increase the efficiency of management operations and reduce costs.
Forest modeling – 3D recreations of forests help management and research teams learn more about how forests are structured through the creation of useful geospatial data like digital terrain models.
Inventory counting – Remote sensing allows research and management teams to quickly survey large areas and automate the generation of tree parameters such as inventory counts, GPS locations of tree positions, canopy heights and much more.
Disturbance forecasting – Prevalent forest disturbances such as fires, flooding, windstorms, droughts, overharvesting, pollution, fragmentation and biological invasions by insects and pathogens threaten the ecosystem. To mitigate disturbances and stress requires understanding where it occurs and what influences it may have at several spatial and temporal scales.
Monitoring growth and health – Aerial imagery and maps collected over time serve as a chronological record of the forest and aid in detecting new trees, monitoring growth and determining health assessments of healthy, stressed and degraded targets.
Land management – Aerial data is extremely useful to organizations working with government officials to improve inventory admittance, access and protection.
Time savings – Fixed-wing drones enable land surveyors to capture data faster and more efficiently than terrestrial equipment alone.
Research-grade imagery – Multiple RGB and multispectral image acquisitions at 60-cm spatial resolution allow for detailed analysis and segmentation of individual trees using pre-determined parameters.
Environmental sustainability – Drones, and the aerial data they collect, are key tools to ensure sustainable, responsible forest management.
Digital Elevation Models (DEMs) – High-resolution 3D models enable forest managers to accurately measure tree heights, and density across terrain and perform environmental monitoring and forecasting.
High-density point cloud – Point cloud maps comprise millions of individual points featuring X, Y, Z geospatial coordinates and an RGB value. The forestry industry uses them to calculate distances and to watch for changes in inventory volume as a result of environmental and stress influences.
2D orthomosaic maps – Geospatially accurate and detailed 2D representation of a forest. Researchers typically leverage two orthomosaic maps, (RGB and multispectral) for respective study comparisons.
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