Archaeological Ground Point Filtering of Airborne Laser Scan Derived Point-Clouds in a Difficult Mediterranean Environment

Q1 Social Sciences
M. Doneus, G. Mandlburger, Nives Doneus
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引用次数: 20

Abstract

Digital terrain models (DTM) based on airborne laser scanning (ALS) are an important source for identifying and monitoring archaeological sites and landscapes. However, a DTM is only one of many representations of a given surface. Its accuracy and quality must conform to its purpose and are a result of several considerations and decisions along the processing chain. One of the most important factors of ALS-based DTM generation is ground point filtering, i.e., the classification of the acquired point-cloud into terrain and off-terrain points. Filtering is not straightforward. The resulting DTM is usually a compromise that might show the surface below very dense vegetation while losing detail in other areas. In this paper, we show that in very complex situations (e.g., strongly varying vegetation cover), an optimal compromise is difficult to achieve, and more than one filter with different settings adapted to the varying degree of vegetation cover is necessary. For practical reasons, the results need to be combined into a single DTM. This is demonstrated using the case study of a Mediterranean landscape in Croatia, which consists of open areas (agricultural and grassland), olive plantations, as well as extremely dense and evergreen macchia vegetation. The results are the first step toward an adaptive ground point filtering strategy that might be useful far beyond the field of archaeology.
地中海恶劣环境下机载激光扫描衍生点云的考古地点滤波
基于机载激光扫描(ALS)的数字地形模型(DTM)是识别和监测考古遗址和景观的重要来源。然而,DTM只是给定曲面的许多表示形式之一。其准确性和质量必须符合其目的,并且是沿加工链进行若干考虑和决策的结果。基于als的DTM生成的最重要因素之一是地点滤波,即将获取的点云分为地形点和非地形点。过滤并不简单。所得到的DTM通常是一种折衷,可能会显示非常密集植被下的表面,而失去其他区域的细节。在本文中,我们表明,在非常复杂的情况下(例如,强烈变化的植被覆盖),一个最优的折衷是难以实现的,并且需要多个具有不同设置的过滤器来适应不同程度的植被覆盖。由于实际原因,需要将结果合并到单个DTM中。这是通过克罗地亚地中海景观的案例研究来证明的,该景观由开放区域(农业和草地)、橄榄种植园以及极其密集和常绿的马奇亚植被组成。这些结果是自适应地面点过滤策略的第一步,这种策略可能远远超出考古领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.50
自引率
0.00%
发文量
12
审稿时长
19 weeks
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