FUSIÓN DE NUBES DE PUNTOS DE ESCÁNER LÁSER TERRESTRE Y FOTOGRAMETRÍA AÉREA BASADA EN IMÁGENES DE DRONES PARA EL INVENTARIO DE BOSQUES MEDITERRÁNEOS

Autor: Manuel Torres, Fernando José Aguilar Torres, Alberto Peñalver Romeo, Abderrahim Nemmaoui
Rok vydání: 2019
Předmět:
Zdroj: DYNA INGENIERIA E INDUSTRIA. 94:131-136
ISSN: 1989-1490
DOI: 10.6036/8892
Popis: In this work, the hypothesis of the convenience of merging data of complementary techniques to carry out forest inventories is tested by fusing data from Remotely Piloted Aircraft System Digital Aerial Photogrammetry (RPAS-DAP) and Terrestrial Laser Scanning (TLS). The work area was in the Natural Park "Sierra Maria-Los Velez" (Almeria, Spain), constituted of a representative Mediterranean forest composed of two main forest layers: i) predominant trees (reforested Aleppo pine (Pinus halepensis Mill.)), and ii) understory forest (holm oak (Quercus ilex L.) and different shrubs species). An Object Based Image Analysis (OBIA) pipeline was applied over the corresponding RPAS-DAP RGB orthoimage and a high-resolution Canopy Height Model (CHM) directly derived from the image-based point cloud. This allowed the automatic obtaining of tree delineation, species classification and forest structural attributes (tree height, position and projected crown area). Geometric features derived from the CHM and Green Leaf Index were used to feed a tailored devised OBIA-based method. The very high-resolution fused point cloud, made up from combining TLS and RPAS-DAP point clouds, provided tree-based biometric information such as tree position, diameter at breast height, crown projected area and tree height to estimate forest Above-Ground dry Biomass (AGB) for predominant trees through the allometric equation corresponding to Aleppo pine. In conclusion, the results obtained from the pipeline proposed in this work have shown the complementarity of RPAS image-based methods and TLS to provide timely and efficiently high value-added products such as forest AGB and tree species spatial distribution over Mediterranean forest.
Databáze: OpenAIRE