基于无人机与激光测距技术的农田地形测绘

平整地技术是提高作物单产的重要措施，而获取高精度的农田地形测绘数据与农田数字地形模型，是进行精准平整地作业的必要条件。为了解决传统接触式地形测绘效率低、基于航拍摄影技术的遥感地形测绘精度差及作业成本高等问题，该研究提出了一种基于多旋翼无人机与激光测距技术的农田地形测绘方法。在多旋翼无人机测绘平台上搭载激光测距模块与后处理动态差分全球定位系统设备（Post-Processing Kinematic Global Positioning System，PPK-GPS），获取激光测距序列、PPK-GPS三维定位数据以及无人机的飞行姿态数据。首先使用均值滤波器处理原始激光测距序列，并将得到的激光测距序列与PPK-GPS定位数据进行同步处理，使二者建立空间对应关系。根据无人机倾斜状态时的测距激光方向与理论竖直方向的空间几何关系，使用从无人机的飞行控制器中提取的姿态信息校正激光测距序列，消除无人机平台在飞行过程中俯仰与横滚姿态变化对激光测距精度的影响。最后，然后根据PPK-GPS定位数据的海拔高度分量与激光测距序列计算试验地块内地面测量点的海拔高度，共获取1 417组地面测量点的有效测绘数据。利用手持PPK-GPS设备对地面测量点的海拔高度进行测绘精度检验。验证试验结果表明，本文提出的无人机农田地形测绘系统获取的海拔高度与手持PPK-GPS设备采集的海拔高度的均方根误差为5.2 cm，表明该无人机农田地形测绘系统具有较高的测绘精度。与利用手持GPS设备进行地形测绘作业的方法相比较，本文提出的无人机农田地形测绘系统具有自动化程度高、作业效率高等优点。该研究可为促进精准平整地技术的大规模应用提供数据支持。

Farmland topographic mapping based on UAV and LiDAR technology

Abstract: Precision Land Leveling (PLL) is the key technology to build high-standard farmland, and thereby improve unit yield of crop. However, the accurate terrain data of farmland is severely lacking for the massive application of PLL in China. Two means are mainly used to collect land terrain data, including the remote sensing and contact topographic mapping. In the contact topographic mapping, the high accuracy of each points can be achieved using the equipment, such as the total station, but the efficiency and accuracy of interpolating data are still far from satisfactory in the case of large areas. In the remote sensing topographic mapping, the aerial photogrammetric or Light Detecting and Ranging(LiDAR) technologies can be used to cover large areas during one flight mission, but the overall accuracy depends highly on the total number and spatial distribution of selected Ground Control Points(GCPs). Therefore, it is necessary to acquire high-precision land terrain data, and then to establish sophisticated terrain model of farmland for PLL operation in time and cost saving. In this study, an Unmanned Aerial Vehicle(UAV) equipped with the low-cost LiDAR and modules of light-weighted Post-Processing Kinematic Global Positioning System(PPK-GPS) was utilized to acquire the multiple remote sensing data in Kaifeng City, Henan Province, China. Firstly, a mean-filter was used to preprocess the data from LiDAR distance measurement, thereby to synchronize with the PPK-GPS data in an improved accuracy. Secondly, the time-varying attitude (pitch and roll) data in the UAV was considered to correct the preprocessed LiDAR distance measurements, in order to remove the impacts of constantly changing attitude of UAV platform. Then, the PPK-GPS data and the corrected LiDAR distance measurements were integrated to calculate the altitude of land surface, and finally 1 417 sets of effective discrete terrain surveying points were obtained in 3-dimensional coordinates (longitude, latitude, altitude). An accurate evaluation was also carried out in the PPK-GPS modules and LiDAR device still for 10 mins consecutively, where the vertical accuracy of positioning data from PPK-GPS and the distance measuring accuracy of LiDAR were 3 cm and 1 cm, respectively. Furthermore, the accuracy of 3-dimensional coordinates of discrete terrain surveying points was validated in the UAV-LiDAR topographic mapping system using a hand-hold PPK-GPS device, suitable for the centimeter-level accuracy. The Root Mean Square Error(RMSE) of terrain surveying method in between the UAV-LiDAR topographic mapping system and the hand-hold PPK-GPS was 5.2 cm, indicating a high accuracy in the terrain surveying domain. A Kriging interpolation model was used to establish a Digital Terrain Model(DTM), according to the 1 417 sets of 3-dimensional coordinates of effective discrete terrain surveying points. The DTM accuracy was slightly lower than that of UAV-LiDAR-based farmland topographic mapping system. This difference can be attributed to the measuring accuracy of individual points, and the spatial distribution of measured points in a ground survey. Therefore, the proposed approach can be expected to improve the efficiency and time/cost saving, while the accuracy of farmland terrain surveying, and thereby to promote high-standard farmland.