An improved method for edge detection based on neighbor distance for processing hemispheric photography

Author:

Liu Yasi1,Fan Dayong2,Sun Han1,Wang Xiangping1

Affiliation:

1. State Key Laboratory of Efficient Production of Forest Resources, School of Ecology and Nature Conservation, Beijing Forestry University , Beijing 100083 , China

2. The Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University , Beijing 100083 , China

Abstract

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 a specific gap fraction can significantly improve the accuracy of the original ‘edge detection’ method. We developed an ND-IS (Neighbor Distance-Iteration Selection) method that can automatically determine the threshold values of hemisphere photos with high accuracy and reproductivity. It combines 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. This procedure worked well throughout a broad range of gap fractions (0.019–0.945) with different canopy compositions and structures, 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.

Funder

Fang Jingyun ecological study studio of Yunnan province

National Natural Science Foundation of China

Major Program for Basic Research Project of Yunnan Province

Publisher

Oxford University Press (OUP)

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