An improved method for edge detection based on neighbor distance for processing hemispheric photography in studying canopy structure and radiative transfer

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Yasi Liu, Dayong Fan, Han Sun, Xiangping Wang
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引用次数: 0

Abstract

Hemisphere photos are now widely applied to provide information about solar radiation dynamics, canopy structure and their contribution to biophysical processes, plant productivity and ecosystem properties. The present study aims to improve the original “edge detection” method for binary classification between sky and canopy, which works not well for closed canopies. We supposed such inaccuracy probably is due to the influence of sky pixels on their neighbor canopy pixels. Here we introduced a new term “neighbor distance”, defined as the distance between pixels participated in the calculation of contrast at the edges between classified canopy and sky, into the “edge detection” method. We showed that choosing a suitable neighbor distance for a photo with specific gap fraction can significantly improve the accuracy of the original “edge detection” method. Combining the modified “edge detection” method and an iterative selection method, with the aid of an empirical power function for the relationship between neighbor distance and manually verified gap fraction, we developed a ND-IS (Neighbor Distance-Iteration Selection) method that can automatically determine the threshold values of hemisphere photos with high accuracy and reproductivity. This procedure worked well throughout a broad range of gap fraction (0.019 to 0.945) with different canopy composition and structure, in five forest biomes along a broad gradient of latitude and longitude across Eastern China. Our results highlight the necessity of integrating neighbor distance into the original “edge detection” algorithm. The advantages and limitations of the method, and the application of the method in the field were also discussed.
基于邻距的边缘检测改进方法,用于处理半球摄影,研究冠层结构和辐射传递
半球照片目前被广泛应用于提供有关太阳辐射动态、树冠结构及其对生物物理过程、植物生产力和生态系统特性的贡献的信息。本研究旨在改进原有的 "边缘检测 "方法,对天空和树冠进行二元分类。我们认为这种不准确性可能是由于天空像素对其相邻冠层像素的影响。在此,我们在 "边缘检测 "方法中引入了一个新术语 "邻距",即参与计算已分类的树冠和天空边缘对比度的像素之间的距离。我们的研究表明,为具有特定间隙分数的照片选择合适的邻距可以显著提高原始 "边缘检测 "方法的准确性。我们将改进后的 "边缘检测 "方法与迭代选择方法相结合,并借助邻距与人工验证的间隙分数之间关系的经验幂函数,开发了一种 ND-IS(邻距-迭代选择)方法,该方法可自动确定半球照片的阈值,准确性和再现性都很高。该方法在华东地区经纬度梯度较大的五个森林生物群落中,在不同冠层组成和结构的较大间隙率范围(0.019 至 0.945)内都能很好地发挥作用。我们的结果凸显了将邻近距离纳入原始 "边缘检测 "算法的必要性。此外,还讨论了该方法的优势和局限性,以及该方法在野外的应用。
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
7.20
自引率
4.30%
发文量
567
期刊介绍: ACS Applied Electronic Materials is an interdisciplinary journal publishing original research covering all aspects of electronic materials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials science, engineering, optics, physics, and chemistry into important applications of electronic materials. Sample research topics that span the journal's scope are inorganic, organic, ionic and polymeric materials with properties that include conducting, semiconducting, superconducting, insulating, dielectric, magnetic, optoelectronic, piezoelectric, ferroelectric and thermoelectric. Indexed/​Abstracted: Web of Science SCIE Scopus CAS INSPEC Portico
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