Slope failures are financially devastating natural hazards that contribute to land degradation in many areas throughout the world. The adaptation of civic technologies (Google Tango) in a field survey of landslides was examined. Data acquired from different resources and processed using different technologies were merged into a single model to concurrently demonstrate the interoperability and scalability of these data and the model quality. Reference control points were established using a survey‐grade Topcon Hiper SK global navigation satellite system receiver and a Topcon GPT 9003 M total station. An aerial survey was performed in an area of approximately 30,000 m² using airborne laser scanning (9 points/m²) and aerial photogrammetry using a remotely piloted aircraft system (500 points/m²). The models suffered from data gaps in less visible areas, and micro‐scale landforms reflecting landslide activity were poorly visible. The missing details were supplied using data obtained from close‐range photogrammetry (9,132 m²; 92,300 points/m²) and a Lenovo Phab 2 Pro running Google Tango, which acquired detailed point clouds in near real‐time conditions (1,847 m²; 109,000 points/m²). Scans using the phablet provided point clouds with homogeneously dispersed data gaps, but the spatial accuracy was lower. However, the ergonomics of its field use and its low cost made it competitive with other technologies. The results confirmed that models based on point clouds acquired using different technologies allow the identification and measurement of micro‐scale landforms that may indicate landslide activity.

中文翻译：

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市政技术在滑坡实地调查中的应用

边坡破坏在财政上破坏了自然灾害，导致了世界许多地区的土地退化。在滑坡的实地调查中，研究了民用技术（Google Tango）的适应性。从不同资源获取并使用不同技术处理的数据被合并到一个模型中，以同时展示这些数据的互操作性和可伸缩性以及模型质量。参考控制点是使用调查级Topcon Hiper SK全球导航卫星系统接收器和Topcon GPT 9003 M全站仪建立的。空中调查在大约30,000米的面积进行²使用机载激光扫描（9分/米²）和使用遥控飞机系统（500 points / m ²）的航空摄影测量。这些模型在可见性较差的地区存在数据缺口，并且反映滑坡活动的微观尺度地貌也较不明显。使用从近距离摄影测量法（9,132 m ² ; 92,300 points / m ²）和运行Google Tango的Lenovo Phab 2 Pro获得的数据提供了丢失的细节，该公司在接近实时的条件下（1,847 m ² ; 109,000点/ m ²）。使用平板手机进行的扫描为点云提供了均匀分散的数据间隙，但空间精度较低。但是，其现场使用的人机工程学原理和低廉的成本使其与其他技术具有竞争优势。结果证实，基于使用不同技术获得的点云的模型可以识别和测量可能表明滑坡活动的微观尺度地貌。