无人机抛投式GNSS滑坡监测设备智能化部署选址方法

doi:10.11947/j.AGCS.2024.20230358

测绘学报 ›› 2024, Vol. 53 ›› Issue (6): 1140-1153.doi: 10.11947/j.AGCS.2024.20230358

无人机抛投式GNSS滑坡监测设备智能化部署选址方法

许豪¹^,²^,³(), 张勤¹^,²^,³(), 王利¹^,²^,³, 舒宝¹^,²^,³, 杜源¹^,²^,³, 黄观文¹^,²^,³

^1.长安大学地质工程与测绘学院，陕西　西安　710054
^2.地理信息工程国家重点实验室，陕西　西安　710054
^3.西部矿产资源与地质工程教育部重点实验室，陕西　西安　710054

收稿日期:2023-08-25 发布日期:2024-07-22
通讯作者: 张勤 E-mail:xuhao@chd.edu.cn;dczhangq@chd.edu.cn
作者简介:许豪（1996—），男，博士生，研究方向为滑坡灾害多源监测数据融合算法。　E-mail：xuhao@chd.edu.cn
基金资助:
国家自然科学基金(42127802);国家重点研发计划(2021YFC3000503);中央高校基本科研业务费专项(300102263202)

Intelligent site selection method for UAV-dropped GNSS landslide monitoring equipment

Hao XU¹^,²^,³(), Qin ZHANG¹^,²^,³(), Li WANG¹^,²^,³, Bao SHU¹^,²^,³, Yuan DU¹^,²^,³, Guanwen HUANG¹^,²^,³

^1.College of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China
^2.State Key Laboratory of Geographic Information Engineering, Xi'an 710054, China
^3.Key Laboratory of Western China's Mineral Resources and Geological Engineering, Ministry of Education, Xi'an 710054, China

Received:2023-08-25 Published:2024-07-22
Contact: Qin ZHANG E-mail:xuhao@chd.edu.cn;dczhangq@chd.edu.cn
About author:XU Hao (1996—), male, PhD candidate, majors in landslide multi-source monitoring data fusion algorithm.　E-mail: xuhao@chd.edu.cn
Supported by:
The National Natural Science Foundation of China(42127802);The National Key Research and Development Program of China(2021YFC3000503);The Fundamental Research Funds for the Central Universities, CHD(300102263202)

摘要/Abstract

摘要：

GNSS技术广泛应用于滑坡形变监测，而复杂艰险的高危滑坡往往人员难至，导致GNSS监测设备安装困难。无人机抛投部署技术为解决此问题提供了可能，然而其前提是为无人机抛投提供适宜的目标部署位置，传统的选址方法主要依赖专家现场踏勘评估，无法满足该场景应用需求。为此，本文首先利用无人机航测、InSAR-Stacking技术获取选址区域的DSM、DOM及地表历史形变速率图，然后基于深度学习、地形分析等方法提取历史形变、裂缝分布、坡度、地表粗糙度、植被指数、坡向等选址因子，最后基于层次分析法对多个选址因子进行决策融合，智能化评估滑坡区域内不同位置的选址适宜性并推荐无人机抛投式GNSS监测设备的目标部署位置。以甘肃黑方台滑坡区域为例开展选址试验，评估了该区域内的选址适宜性并推荐了4处GNSS监测设备部署位置，现场情况及历史站点形变序列验证了本文方法的有效性。本文方法综合考虑了形变监测、部署难度、观测条件及持续运行等需求，可高效评估选址区域内设备部署的适宜程度，对于提升无人机抛投式GNSS监测设备的部署效率及监测效果具有重要参考价值。

关键词: GNSS, 无人机抛投, 滑坡监测, 监测站选址, 层次分析法

Abstract:

The GNSS technology is widely used in landslide deformation monitoring. However, in complex and hazardous landslide areas, it is difficult for personnel to access, and the installation of GNSS monitoring devices faces challenges. The UAV-dropped deployment technology offers a potential solution to this problem, but it requires appropriate target delivery locations for the UAVs. Traditional site selection methods mainly rely on expert field surveys, which fail to meet the requirements of such scenarios. To address this, this study first utilizes drone aerial photography and InSAR-Stacking technology to obtain digital surface models (DSM), digital orthophoto maps (DOM), and surface deformation rate maps of the target site. Then, based on deep learning, terrain analysis, and other methods, the key site selection factors such as historical deformation, crack distribution, slope, surface roughness, vegetation index, and slope direction are extracted. Finally, an analytic hierarchy process is employed to intelligently evaluate the suitability of different locations within the landslide area for UAV-dropped deployment of GNSS monitoring devices and recommend the coordinates of the target delivery locations. The site selection experiments were conducted in the Heifangtai landslide area in Gansu province, China. The suitability of the selected locations within this area was assessed, and four airdrop positions for GNSS monitoring devices were recommended. The effectiveness of the proposed method was validated through on-site observations and historical station deformation sequences. This method comprehensively considers the demands of deformation monitoring, deployment difficulty, observation conditions, and continuous operation, enabling efficient evaluation of the suitability of equipment deployment in the site selection area. It holds significant reference value for the unmanned and intelligent deployment of GNSS monitoring devices.

Key words: GNSS, UAV dropping, landslide monitoring, monitoring station site selection, analytic hierarchy process

中图分类号:

P227

许豪, 张勤, 王利, 舒宝, 杜源, 黄观文. 无人机抛投式GNSS滑坡监测设备智能化部署选址方法[J]. 测绘学报, 2024, 53(6): 1140-1153.

Hao XU, Qin ZHANG, Li WANG, Bao SHU, Yuan DU, Guanwen HUANG. Intelligent site selection method for UAV-dropped GNSS landslide monitoring equipment[J]. Acta Geodaetica et Cartographica Sinica, 2024, 53(6): 1140-1153.

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P_ij	含义
1	选址因子i和选址因子j同样重要
3	选址因子i比选址因子j稍微重要
5	选址因子i比选址因子j明显重要
7	选址因子i比选址因子j强烈重要
9	选址因子i比选址因子j极端重要
2、4、6、8	上述重要性的中间值

站点名	历史形变	裂缝分布	坡度	地表粗糙度	植被指数	坡向	适宜性值
P₁	0.47	0.97	0.57	0.66	0.71	0.8	0.69
P₂	0.39	0.82	0.24	0.70	0.64	0.8	0.56

无人机抛投式GNSS滑坡监测设备智能化部署选址方法

Intelligent site selection method for UAV-dropped GNSS landslide monitoring equipment

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