A method for soil roughness measurement based on UAV point cloud data
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摘要: 耕地土壤粗糙度是影响土壤水分、微波遥感观测和植物生长等农情信息监测方面的重要因子。土壤粗糙度通常是根据野外拍摄照片进行判读,但存在判读效率低、受人为因素影响等不足。无人机低空遥感对观测地表起伏状况具有良好的敏感性,因此基于摄影测量利用无人机对地表进行拍摄,将其结果与粗糙度测量板获取的数据进行对比,探讨无人机数据测量土壤粗糙度的精确性。研究结果表明: 近景摄影测量的平均绝对误差主要集中在0.4~1.2 cm之间,平均相对误差为6.16%,均方根误差为0.40 cm。表明无人机点云摄影测量可有效运用于地表粗糙度的测量,且当分块采样的面积越小时,获得粗糙度的值越精确。Abstract: The soil roughness of cultivated land is an important element affecting the monitoring of agricultural information, such as soil moisture, microwave remote sensing observation, and plant growth. Soil roughness is generally interpreted according to field photos. However, such interpretation suffers some shortcomings such as low efficiency and anthropogenic effects on processing results. UAV low-altitude remote sensing is sensitive to surface relief. To explore the precision of the soil roughness determined using UAV data, this study employed UAV photogrammetry to photograph the surface and then compared the photogrammetry results with the data obtained using a gauging plate for soil roughness. The results show that the close-range photogrammetry had mean absolute errors of mainly 0.4~1.2 cm, a mean relative error of 6.16%, and a root mean square error of 0.40 cm. Therefore, UAV-based point cloud photogrammetry could be effectively applied to the measurement of surface roughness, and a smaller sampling area is associated with more accurate soil roughness.
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