The invention discloses an unmanned aerial vehicle
LiDAR-based high-
canopy-density
crop plant height double-end adaptive inversion method and
system, and relates to the technical field of agricultural
remote sensing. The method comprises the following steps: acquiring a
crop canopy point cloud and extracting density, skewness and original ground elevation characteristics; constructing a near-surface pseudo
ground layer thickness correction model, introducing a pseudo
ground layer thickness parameter to carry out pressing correction of a
physical layer on an original ground elevation, and reconstructing a real bare soil layer ground reference; constructing a
canopy end density-form adaptive model, and dynamically calculating the optimal upper boundary percentile by using the
point cloud density and the elevation distribution skewness; and calculating the final
plant height based on a double-end correction result. According to the method, the problems of systematic overestimation caused by near-surface pseudo ground blocking and poor adaptability of a fixed threshold value to the canopy form in
LiDAR ground detection under the high-canopy-density canopy are effectively solved, and high-precision and robust
plant height automatic extraction under multiple varieties and different flight heights is realized under the condition that external
terrain auxiliary data is not needed.