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Chinese fir (Cunninghamia lanceolate (Lamb.) Hook) individual tree parameters extraction is important for scientific forest management. However, high-precision parameters extraction by field investigation or spaceborne optical remote sensing is difficult when the forest is dense and the terrain is complex. This article proposes a framework for extracting individual tree parameters by combining low-cost and high-efficiency unmanned aerial vehicle-based oblique photogrammetry with manned airborne light detection and ranging data and explores the influence of spatial resolution on the accuracy of parameter extraction. The variable window filtering (VWF) was used to detect an individual tree. The marker-controlled watershed segmentation (MCWS) and seed region growing algorithms were used to delineate the crown. The individual tree detection using VWF based on 1 m resolution achieves precision of 80%. For the crown delineation, it is more accurate based on the 0.25 m resolution using MCWS algorithm with the detection accuracy of 65%. The results show that the proposed framework can effectively detect the tree and delineate the crown under complex terrain conditions and the optimal resolution for different parameter extraction is determined, which has important guiding significance to determine the flight parameters and reduce unnecessary data processing.

ieee journal of selected topics in applied earth observations and remote sensing

Individual Tree Parameters Estimation for Chinese Fir (<italic>Cunninghamia lanceolate</italic> (Lamb.) Hook) Plantations of South China Using UAV Oblique Photography: Possibilities and Challenges

Individual Tree Parameters Estimation for Chinese Fir (Cunninghamia lanceolate (Lamb.) Hook) Plantations of South China Using UAV Oblique Photography: Possibilities and Challenges