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Forest resources have their own importance in human survival and development. Forest plot survey is used to obtain forest information and analyze the status of forest resources. With the advancement in sensor technology, remote sensing, especially LiDAR, is used to obtain point cloud data by scanning plots which can be used to extract forestbased factors. The improvement of SLAM algorithm enables the positioning without GPS signal coverage. So that, the combination of LiDAR and SLAM system can be used to get a globally consistent point cloud of a plot under the canopy which can ensure the integrity and accuracy of the extracted plot properties. However, the estimations can not be checked and the omissions or errors can not be corrected. A plot survey system based on RGB-D SLAM mobile phone was developed, which constructed the process of plot survey, the estimation of treebased properties and forestbased properties. Augmented reality technology was used to show the observer estimation results and the way of reestimation, which ensured the reliability and integrity of the acquired plot information through human intervention. The system was tested in 18 circular plots with radius of 7.5m.The average DBH estimations showed 0.36cm BIAS and 069cm RMSE; the average tree height estimations showed 006m BIAS and 063m RMSE; the volume estimations showed 8.5959m3/hm2 BIAS and 25.7358m3/hm2 RMSE; the crosssectional area estimations showed 0.9497m2/hm2 BIAS 〖JP2〗and 1.9873m2/hm2 RMSE; the stem density estimations showed -3 stems/hm2 BIAS and 13 stems/hm2 RMSE; the slope estimations showed 0.30° BIAS and 0.88° RMSE; and the aspect estimations showed -0.44° BIAS and 7.61° RMSE. The aspect estimations had a large RMSE due to the estimated pose errors of the SLAM system, but the aspect measurements were still unbiased as a whole.