Image-based surface reconstruction in geomorphometry - merits, limits and developments
Image-based surface reconstruction in geomorphometry - merits, limits and developments
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DOI：
10.5194/esurf-4-359-2016
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发表时间：
2016-01-01
影响因子：
3.4
通讯作者：
Abellan, Antonio
中科院分区：
文献类型：
--
作者：
Eltner, Anette;Kaiser, Andreas;Abellan, Antonio
自19世纪后期以来，由于获得了高质量的三维环境数据集，摄影测量和地球科学一直密切相关，但由于用于获得和处理机载图像的度量系统的相当大的成本，迄今为止，摄影测量和地球科学一直局限于有限范围的遥感专家。今天，各种商业和开放源码软件工具使地球科学家和其他非专家用户能够生成复杂地貌特征的3D和4D模型。此外，最近无人机技术的快速发展使得能够以相对较低的成本灵活地生成高质量的航空测量和正射摄影。过去十年中，随着计算能力的不断提高，以及高性能数字传感器的发展和基于计算机的视觉和视觉感知研究领域开发的重要软件创新，已经将立体图像数据的严格处理扩展到从一系列未校准图像生成3-D点云。运动恢复结构（SfM）工作流程基于无需进一步数据采集信息的大型图像集的高效和自动定向算法，示例包括稳健的特征检测器，如用于2-D图像的尺度不变特征变换。然而，进行完善的实地调查策略的重要性，使用适当的相机设置，地面控制点和地面真理的理解不同来源的错误，仍然需要适应在共同的科学practice.This审查的目的不仅是总结目前的艺术状态上使用SfM工作流程在地貌测量，但也给一个概述的条款和应用领域。此外，本文旨在使用不同的策略量化已经达到的准确性和使用的规模，以评估当前发展可能出现的停滞并确定未来的关键挑战。我们相信，从以前的文章，科学报告和书籍章节中吸取的一些经验教训，关于识别常见的错误或“不良做法”和其他一些有价值的信息，可能有助于指导未来使用SfM摄影测量在地球科学。
Photogrammetry and geosciences have been closely linked since the late 19th century due to the acquisition of high-quality 3-D data sets of the environment, but it has so far been restricted to a limited range of remote sensing specialists because of the considerable cost of metric systems for the acquisition and treatment of airborne imagery. Today, a wide range of commercial and open-source software tools enable the generation of 3-D and 4-D models of complex geomorphological features by geoscientists and other non-experts users. In addition, very recent rapid developments in unmanned aerial vehicle (UAV) technology allow for the flexible generation of high-quality aerial surveying and ortho-photography at a relatively low cost.The increasing computing capabilities during the last decade, together with the development of high-performance digital sensors and the important software innovations developed by computer-based vision and visual perception research fields, have extended the rigorous processing of stereoscopic image data to a 3-D point cloud generation from a series of non-calibrated images. Structure-from-motion (SfM) workflows are based upon algorithms for efficient and automatic orientation of large image sets without further data acquisition information, examples including robust feature detectors like the scale-invariant feature transform for 2-D imagery. Nevertheless, the importance of carrying out well-established fieldwork strategies, using proper camera settings, ground control points and ground truth for understanding the different sources of errors, still needs to be adapted in the common scientific practice.This review intends not only to summarise the current state of the art on using SfM workflows in geomorphometry but also to give an overview of terms and fields of application. Furthermore, this article aims to quantify already achieved accuracies and used scales, using different strategies in order to evaluate possible stagnations of current developments and to identify key future challenges. It is our belief that some lessons learned from former articles, scientific reports and book chapters concerning the identification of common errors or "bad practices" and some other valuable information may help in guiding the future use of SfM photogrammetry in geosciences.