Improving Otsu Method Parameters for Accurate and Efficient in LAI Measurement Using Fisheye Lens

Author:

Tian Jiayuan123,Liu Xianglong4,Zheng Yili1235,Xu Liheng4,Huang Qingqing1235,Hu Xueyang123ORCID

Affiliation:

1. School of Technology, Beijing Forestry University, Beijing 100083, China

2. State Key Laboratory of Efficient Production of Forest, Beijing 100083, China

3. Institute of Intelligent Sensing for Ecological Carbon Neutrality in Forestry and Grassland, Beijing Forestry University, Beijing 100083, China

4. Qingyang Forestry Science Research Institute, Qingyang 745000, China

5. Key Laboratory of National Forestry and Grassland Administration on Forestry Equipment and Automation, Beijing 100083, China

Abstract

The leaf area index (LAI) is an essential indicator for assessing vegetation growth and understanding the dynamics of forest ecosystems and is defined as the ratio of the total leaf surface area in the plant canopy to the corresponding surface area below it. LAI has applications for obtaining information on plant health, carbon cycling, and forest ecosystems. Due to their price and portability, mobile devices are becoming an alternative to measuring LAI. In this research, a new method for estimating LAI using a smart device with a fisheye lens (SFL) is proposed. The traditional Otsu method was enhanced to improve the accuracy and efficiency of foreground segmentation. The experimental samples were located in Gansu Ziwuling National Forest Park in Qingyang. In the accuracy parameter improvement experiment, the variance of the average LAI value obtained by using both zenith angle segmentation and azimuth angle segmentation methods was reduced by 50%. The results show that the segmentation of the front and back scenes of the new Otsu method is more accurate, and the obtained LAI values are more reliable. In the efficiency parameter improvement experiment, the time spent is reduced by 17.85% when the enhanced Otsu method is used to ensure that the data anomaly rate does not exceed 10%, which improves the integration of the algorithm into mobile devices and the efficiency of obtaining LAI. This study provides a fast and effective method for the near-ground measurement of forest vegetation productivity and provides help for the calculation of forest carbon sequestration efficiency, oxygen release rate, and forest water and soil conservation ability.

Funder

Gansu Province Qingyang City Science and Technology Program Project

Publisher

MDPI AG

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