engleski

The influence of different orientation methods of UAV images on the quality of point cloud generation and plot-level tree height estimates

digital photogrammetry ; forest inventory ; unmanned aerial vehicle

digital photogrammetry ; forest inventory ; unmanned aerial vehicle

Unmanned Aerial Vehicles (UAVs) have the potential to provide data of very high spatial and temporal resolution, and therefore they recently attracted great attention in many environmental sciences, including forest inventory. By photogrammetric processing of UAV-images, a dense point cloud of forest canopy can be derived. To obtain normalized point cloud (height above ground) useful for forest inventory, a highly accurate Digital Terrain Model (DTM) is needed. In combination with field reference data, the normalized point clouds could serve to estimate various forest inventory attributes which has been confirmed by a number of recent studies. However, due to a high variation in the technical characteristics of UAVs which are currently present in the market, and even more due to a high diversity of forest structure across the planet, further research is required. Namely, in the dense forests, it is very difficult to obtain the regular and dense spatial distribution of Ground Control Points (GCPs) for quality Indirect Sensor Orientation (ISO). Another option for sensor orientation in such scenarios is GNSS supported sensor orientation. Q