基于无人机点云数据土壤粗糙度测量方法

doi:10.6046/zrzyyg.2021461

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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。

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	张田
	周忠发
	王玲玉
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	张文辉
	张淑
	王宇

关键词 ：土壤粗糙度, 点云数据, 近景摄影测量, 三维建模

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.

Key words： soil roughness point cloud data close-range photogrammetry three-dimensional modeling

收稿日期: 2021-12-27 出版日期: 2023-03-20

ZTFLH:

P237

基金资助:国家自然科学基金项目“喀斯特石漠化地区生态资产与区域贫困耦合机制研究”(41661088);贵州省高层次创新型人才培养计划项目“贵州省高层次创新型人才培养计划——‘百’层次人才”(黔科合平台人才〔2016〕5674);贵州省科学技术基金资助项目“高原山区特色农作物超低空遥感特征构建与识别方法研究”(黔科合基础-ZK[2021]一般194);国家自然科学基金面上项目“地块作物生长的光学与SAR遥感同步观测响应机制研究”(42071316)

通讯作者: 周忠发(1969-),男,教授,博士生导师,研究方向为喀斯特生态环境、GIS与遥感。Email: fa6897@163.com。

作者简介: 张田(1997-),女,硕士研究生,研究方向为地理信息系统与遥感。Email: 20010090327@gznu.edu.cn。

引用本文:

张田, 周忠发, 王玲玉, 赵馨, 张文辉, 张淑, 王宇. 基于无人机点云数据土壤粗糙度测量方法[J]. 自然资源遥感, 2023, 35(1): 115-122.
ZHANG Tian, ZHOU Zhongfa, WANG Lingyu, ZHAO Xin, ZHANG Wenhui, ZHANG Shu, WANG Yu. A method for soil roughness measurement based on UAV point cloud data. Remote Sensing for Natural Resources, 2023, 35(1): 115-122.

链接本文:

https://www.gtzyyg.com/CN/10.6046/zrzyyg.2021461 或 https://www.gtzyyg.com/CN/Y2023/V35/I1/115

Fig.1 数据采样示意图

Tab.1 无人机、相机及飞行参数

Fig.2 技术路线

Fig.3 分块采样示意图

Tab.2 表面粗糙度参数测量结果对比

Fig.4 测量板法与近景摄影测量法结果对比

Fig.5 不同测量方法所取得的同一土壤样线比较

Fig.6 无人机摄影测量计算结果

Tab.3 不同采样面积下的土壤粗糙度参数测量结果

Fig.7 不同采样面积的土壤表面模型

Tab.4 2种方法所需时间及精度对比

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