Inicio  /  Forests  /  Vol: 9 Núm: 1 Par: January (2018)  /  Artículo
ARTÍCULO
TITULO

A New Method for Characterizing Bark Microrelief Using 3D Vision Systems

Andrzej Sioma    
Jaroslaw Socha and Anna Klamerus-Iwan    

Resumen

Bark microrelief (BM), or the spatial patterning of bark texture, is an important bark characteristic shown to significantly affect the ecophysiological functioning of forest ecosystems. BM influences bark micrometeorological conditions and stemflow generation which, in turn, impacts epiphytic vegetation and microbial community patterns, as well as insect foraging behavior. Thus, an objective method to quantify BM is important to understand and model hydro-biogeochemical processes in forest canopy ecosystems. The aim of this study was to develop a method for fast and automated imaging of bark surface morphology. Three-dimensional imaging methods using laser triangulation were used to describe BM. An automated system was developed and applied to calculate three new BM indices for samples collected from five trees representing species common throughout Poland (and Northern Europe): common oak, European ash, trembling aspen, Scots pine, and black alder. These new BM indices may be useful for characterizing and quantitatively relating BM to forest canopy ecophysiological functions.

 Artículos similares

       
 
Jianlei Qiao, Yonglu Lv, Yucai Feng, Chang Liu, Yi Zhang, Jinying Li, Shuang Liu and Xiaohui Weng    
At present, the electronic nose has became a new technology for the rapid detection of pesticides. However, the technique may misidentify them for samples that have not been involved in training. Therefore, a hybrid model based on unsupervised and superv... ver más
Revista: Agronomy

 
Mengke Zhang, Xiaoguang Li, Ling Wang, Liujian Jin and Shubo Wang    
The application of intelligent mobile robots in agriculture has emerged as a new research frontier, with the integration of autonomous navigation technology and intelligent agricultural robots being the key to the widespread adoption of smart agricultura... ver más
Revista: Agronomy

 
Luigi Pari, Luca Cozzolino, Sylvain Marsac, Louise Hermet and Simone Bergonzoli    
Camelina is an interesting crop and producers must adopt cultural practices to achieve the highest yield and oil content possible. Considering the size of the seed, the harvesting phase is crucial to reduce losses and maximize income. Furthermore, in rec... ver más
Revista: Agronomy

 
Lexin Zhang, Kuiheng Chen, Liping Zheng, Xuwei Liao, Feiyu Lu, Yilun Li, Yuzhuo Cui, Yaze Wu, Yihong Song and Shuo Yan    
This study introduces a novel high-accuracy fruit fly detection model based on the Transformer structure, specifically aimed at addressing the unique challenges in fruit fly detection such as identification of small targets and accurate localization agai... ver más
Revista: Agriculture

 
Ping Dong, Kuo Li, Ming Wang, Feitao Li, Wei Guo and Haiping Si    
In addition to the conventional situation of detecting a single disease on a single leaf in corn leaves, there is a complex phenomenon of multiple diseases overlapping on a single leaf (compound diseases). Current research on corn leaf disease detection ... ver más
Revista: Agriculture