Ground Control Point-Free Unmanned Aerial Vehicle-Based Photogrammetry for Volume Estimation of Stockpiles Carried on Barges.

Haiqing He,Ting Chen,Huaien Zeng,Shengxiang Huang

doi:10.3390/s19163534

Abstract

In this study, an approach using ground control point-free unmanned aerial vehicle (UAV)-based photogrammetry is proposed to estimate the volume of stockpiles carried on barges in a dynamic environment. Compared with similar studies regarding UAVs, an indirect absolute orientation based on the geometry of the vessel is used to establish a custom-built framework that can provide a unified reference instead of prerequisite ground control points (GCPs). To ensure sufficient overlap and reduce manual intervention, the stereo images are extracted from a UAV video for aerial triangulation. The region of interest is defined to exclude the area of water in all UAV images using a simple linear iterative clustering algorithm, which segments the UAV images into superpixels and helps to improve the accuracy of image matching. Structure-from-motion is used to recover three-dimensional geometry from the overlapping images without assistance of exterior parameters obtained from the airborne global positioning system and inertial measurement unit. Then, the semi-global matching algorithm is used to generate stockpile-covered and stockpile-free surface models. These models are oriented into a custom-built framework established by the known distance, such as the length and width of the vessel, and they do not require GCPs for coordinate transformation. Lastly, the volume of a stockpile is estimated by multiplying the height difference between the stockpile-covered and stockpile-free surface models by the size of the grid that is defined using the resolution of these models. Results show that a relatively small deviation of approximately ±2% between the volume estimated by UAV photogrammetry and the volume calculated by traditional manual measurement was obtained. Therefore, the proposed approach can be considered the better solution for the volume measurement of stockpiles carried on barges in a dynamic environment because UAV-based photogrammetry not only attains superior density and spatial object accuracy but also remarkably reduces data collection time.

Highlights

Measurement of stockpile volumes, which comprise various materials, such as coal, gypsum, chip, gravel, dirt, rock, quarry, and mine tailings, is an essential task in the construction and mining industry [1,2,3,4]
The main contribution of this study is to propose an approach using ground control points (GCPs)-free unmanned aerial vehicle (UAV)-based photogrammetry that is suitable to estimate the volume of stockpiles carried on barges in a dynamic environment
The other point clouds collected from a different source, i.e., laser scanning, are used to compare and examine how close the numbers obtained from GCP-free UAV photogrammetry are

Summary

Introduction

Measurement of stockpile volumes, which comprise various materials, such as coal, gypsum, chip, gravel, dirt, rock, quarry, and mine tailings, is an essential task in the construction and mining industry [1,2,3,4]. Conventional methods of volume measurement include the trapezoidal and cross-sectioning methods [5]. These methods generally assume that the geometric shape is regular. Sensors 2019, 19, 3534; doi:10.3390/s19163534 www.mdpi.com/journal/sensors (e.g., rectangular, triangular prisms, and trapezoidal) and can be modeled using ideal mathematical models, such as trapezoidal, Simpson-based, cubic spline, and cubic Hermite formulas. These methods require the collection of three-dimensional (3D) points that appropriate distribution and density for volume calculation [6]. Various methods are available to estimate the volume of stockpiles with irregular geometry. On the basis of the density of 3D measured points, these methods are divided into two categories, i.e.,

Objectives

Methods

Results

Conclusion