Abstract

In this paper, multi-spectral satellite images, Light Detection and Ranging (LiDAR) point clouds and thematic data are used for recognition and extraction of interference areas, and based on high resolution digital orthophoto map, use hue-saturation-value (HSV) or red-green-blue (RGB) color model to identify individual red-attack pine trees. Then compare the recognition results and accuracy between the different color models according to visual interpretation and field verification. Research shows that the recognition ac-curacy based on HSV color model is much higher than that based on RGB color model. At the same time, the collaborative utilization of multi-source data can greatly reduce the interference of dead grasslands, shadows, bare land, and roads, and reduce the error rate from 60% to 20%. This paper provides technical ideas and methods for accurate recognition of red-attack pine trees based on unmanned aerial vehicle (UAV) high resolution images.