Measurement and evaluation method of farmland microtopography feature information based on 3D LiDAR and inertial measurement unit

Soil surface roughness (SSR) is an important indicator that characterizes the microtopography feature of farmland after tillage. It has a high practical value for sowing and seedling raising, farmland management, and drainage irrigation in agricultural production. The traditional method often is prone to damage the surface microstructure and results in low efficiency and accuracy. In this study, a new method was proposed to address the limitations of traditional measurement methods of SSR. The proposed measurement and evaluation method of farmland microtopography feature information based on 3D lidar and inertial measurement unit (IMU) could be used to quickly obtain the global point cloud map containing the height data of the test field. Taking three different tillage methods of farmland as the research object, the surface root mean square height (RMSH), correlation length (CL), and their ratio were selected as roughness parameters to explore the anisotropy of microtopography features in different directions. The measurement method was then used to study the effects of sampling processing methods (number, interval, and length) on the measurement accuracy in both OX and OY directions. The results indicate that under the same accuracy requirements, for the 2 × 2 m area, the farmland with different microtopography features needs to be processed with different sample numbers, sample intervals, and sample lengths. The optimal combination of sample parameters for Test field I is sample number of 50, sample interval of 120 mm, and sample interval of 1600 mm, and that in Test field II is sample number of 50, sample interval of 160 mm, and sample interval of 1800 mm. For Test field III, the optimal combination is sample number of 100, sample interval of 40 mm, and sample length of 1200 mm. The experimental results compared with the traditional method illustrate the high accuracy and good feasibility of the proposed method for measuring and evaluating the microtopography feature information of the farmland. The results of the study help to understand the microtopography features and its parameterization of the farmland after tillage, which could further reveal the role and significance of SSR parameters in objectively evaluating farmland tillage quality and optimizing farmland management.