A geomatics data integration approach for veteran chestnut trees 3D modeling

Nowadays data-integration opens up new possibilities for land surveys, involving both remote and proximal sensing devices. The fast advancement of both technology and devices allowed researchers to gather data from afar, making these acquisitions affordable and suitable even in locations with limited accessibility. We surveyed 3 veteran chestnut trees (Castanea sativa) by integration of Mobile Laser Scanner clouds with the top of the canopies reconstructed through photogrammetry, using an Unmanned Aerial Vehicle (UAV) equipped with RGB camera. These 3D models can be used to extract  precise tree metric data, compared with those collected in the field with traditional measurements, such as diameter at breast height (DBH), total height (TH), crown basal area (CBA) and crown volume (CV), providing valuable information on tree assessment and its potential carbon stock. Moreover, the veteran trees have exceptional genetic and cultural values and therefore must be properly inventoried, monitored and protected. We conducted our surveys during summer, when the trees had a crown full of leaves and in winter, when they were almost completely defoliated. We used a GNSS and a total station to collect ground control points, based on available satellites signal. We followed a circular path all around the three veteran chestnut trees with the MLS device, scanning the entire tree from multiple angles and thus obtaining detailed and accurate point clouds of the trees’ skeleton and including at least 3 highly reflective targets. With the UAV, we collected nadiral RGB images to reconstruct the upper part of the canopies and, using the same targets, we merged them with the MLS outputs. We used a Sony Alpha77 single-lens reflex camera to collect detailed, high-quality 3D data of our veteran trunks through the process of close-range photogrammetry. The latter have been merged with the previous 3D models obtained and thus completing the veteran trees reconstruction. Through manual segmentation, we split between trees skeleton and canopy. We extracted the TH and the crown basal area in both seasons using 3DForest software. DBH has been extracted by slicing the RGB trunks at 1.30m and creating a mesh of the sliced portions while the space occupied by the crowns has been computed through the volume obtained by the mesh created with the Alpha Shape algorithm. The volume of the canopies was determined in both the winter and summer seasons to compare the space they occupy when they are in vigor with the space they take up when there are no leaves. Our results, for the 3 individuals, appear to be concordant with the DBH and the TH obtained in the field by traditional measurements while the CBA and CV have not been measured in the field since they are challenging with these ancient trees. The DBH range values are between 150 - 190 cm, the TH is between 18 - 23 m, the CBA and CV range are respectively between 165 - 176 m² and 255 – 314 m³ in winter while 180 – 258 m² and 328 – 406 m³ in the summer surveys.