New Method for Forest Resource Data Collection Based on Smartphone Fusion with Multiple Sensors

Abstract

Tree parameter measurement is an important part of forest resource monitoring. Smartphones play an important role in forest resource surveys. Although sensors inside smartphones, such as gyroscopes and angle sensors, can meet the needs of the public for entertainment or games, the measurement accuracy in professional forest resource monitoring is slightly insufficient. In this paper, a method of collecting tree measurement factors based on personal smart space fusion with a variety of high-precision sensors is proposed. First of all, a high-precision attitude sensor measurement module and a laser ranging module are organically integrated and packaged in a black box. The smartphone is then connected to the sensor box using a magnet sheet, and the working personnel can determine key parameters in the forest stand by holding it. Finally, in order to verify the accuracy of the method, the measured values in this paper are compared with the reference values. The root mean square error (RMSE) of the tree position in the X and Y directions was 0.114 m and 0.147 m, the relative deviations (rBias) were 0.95% and 0.39%, and the average RMSE was 0.186 m. The RMSEs measured by tree height and diameter at breast height (DBH) were 0.98 m and 2.24 cm, the relative root mean square error (rRMSE) was 5.87% and 13.46%, and the relative deviations (rBias) were −1.40% and −1.06%, respectively. Therefore, the method of forest stand parameter measurement based on personal smart space fusion multitype sensors proposed in this paper can be effectively applied to forest resource data collection.

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