Forests Growth Monitoring Based on Tree Canopy 3D Reconstruction Using UAV Aerial Photogrammetry: Fid-Bau Portal

Forests Growth Monitoring Based on Tree Canopy 3D Reconstruction Using UAV Aerial Photogrammetry

Yanchao Zhang / Hanxuan Wu / and Wen Yang

Land cover monitoring is a major task for remote sensing. Comparing to traditional methods for forests monitoring which mostly use orthoimages from satellite or aircraft, there are very few researches use forest 3D canopy structure to monitor the forest growth. UAV aerial can be a novel and feasible platform to provide high resolution and more timely images that can be used to generate high resolution forest 3D canopy. In spring, the small forest is supposed to experience rapid growth. In this research, we used a small UAV to monitor campus forest growth in spring at 2days interval. Each time 140 images were acquired and the ground surface dense point cloud was reconstructed at high precision. Color indexes ExG (Excess Green) was used to extract the green canopy point. The segmented point cloud was triangulated using greedy projection triangulation method into a mesh and its area was calculated. Forest canopy growth was analyzed at 3 level: forest level, selected group level and individual tree level. Logistic curve was used to fit the time series canopy growth. Strong correlation was found R² = 0.8517 at forest level, R²=0.9652 at selected group level and R² = 0.9606 at individual tree level. Moreover, high correlation was found between canopy by observing these results, we can conclude that the ground 3D model can act as a useful data type as orthography to monitor the forest growth. Moreover the UAV aerial remote sensing has advantages at monitoring forest in periods when the ground vegetation is growing and changing fast.