Bryson Mitch, Ferrari Renata, Figueira Will, Pizarro Oscar, Madin Josh, Williams Stefan, Byrne Maria
Australian Centre for Field Robotics University of Sydney Sydney NSW Australia.
School of Biological Sciences University of Sydney Sydney NSW Australia.
Ecol Evol. 2017 Jun 15;7(15):5669-5681. doi: 10.1002/ece3.3127. eCollection 2017 Aug.
Habitat structural complexity is one of the most important factors in determining the makeup of biological communities. Recent advances in structure-from-motion and photogrammetry have resulted in a proliferation of 3D digital representations of habitats from which structural complexity can be measured. Little attention has been paid to quantifying the measurement errors associated with these techniques, including the variability of results under different surveying and environmental conditions. Such errors have the potential to confound studies that compare habitat complexity over space and time. This study evaluated the accuracy, precision, and bias in measurements of marine habitat structural complexity derived from structure-from-motion and photogrammetric measurements using repeated surveys of artificial reefs (with known structure) as well as natural coral reefs. We quantified measurement errors as a function of survey image coverage, actual surface rugosity, and the morphological community composition of the habitat-forming organisms (reef corals). Our results indicated that measurements could be biased by up to 7.5% of the total observed ranges of structural complexity based on the environmental conditions present during any particular survey. Positive relationships were found between measurement errors and actual complexity, and the strength of these relationships was increased when coral morphology and abundance were also used as predictors. The numerous advantages of structure-from-motion and photogrammetry techniques for quantifying and investigating marine habitats will mean that they are likely to replace traditional measurement techniques (e.g., chain-and-tape). To this end, our results have important implications for data collection and the interpretation of measurements when examining changes in habitat complexity using structure-from-motion and photogrammetry.
栖息地结构复杂性是决定生物群落构成的最重要因素之一。基于运动恢复结构和摄影测量技术的最新进展,使得可以测量结构复杂性的三维数字栖息地模型大量涌现。但人们很少关注量化与这些技术相关的测量误差,包括在不同测量和环境条件下结果的变异性。这些误差可能会混淆比较不同时空栖息地复杂性的研究。本研究通过对人工礁(结构已知)以及天然珊瑚礁进行重复调查,评估了基于运动恢复结构和摄影测量得出的海洋栖息地结构复杂性测量的准确性、精密度和偏差。我们将测量误差量化为调查图像覆盖率、实际表面粗糙度以及构成栖息地的生物(珊瑚礁珊瑚)形态群落组成的函数。我们的结果表明,根据任何特定调查期间的环境条件,测量偏差可能高达观察到的结构复杂性总范围的7.5%。测量误差与实际复杂性之间呈正相关,当珊瑚形态和丰度也用作预测因子时,这些关系的强度会增加。基于运动恢复结构和摄影测量技术在量化和研究海洋栖息地方面的众多优势意味着它们可能会取代传统测量技术(如链测和卷尺测量)。为此,我们的结果对于使用基于运动恢复结构和摄影测量来研究栖息地复杂性变化时的数据收集和测量结果解释具有重要意义。