Automated Extracting Tree Crown from Quickbird Stand Image - Archive ouverte HAL Access content directly
Conference Papers Year : 2011

Automated Extracting Tree Crown from Quickbird Stand Image

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Guang Deng
  • Function : Author
  • PersonId : 1012365
Zengyuan Li
  • Function : Author
  • PersonId : 1012366
Honggan Wu
  • Function : Author
  • PersonId : 1012367
Xu Zhang
  • Function : Author
  • PersonId : 1012368

Abstract

Artificial intelligence technologies with spatial information technologies play more and more roles in precision agriculture and precision forestry. This paper puts up a new artificial intelligence algorithm which based on seeded based region growth method to extract tree crown on Quickbird forest stand image. It is a kind of object based canopy and gap information extracting method specially suited for high-resolution imagery to get meaningful tree crown object .The main processes to carry out the experiment and validation on the Quickbird satellite images in Populus×xiaohei plantation even stand at Xue JiaZhuang wood farm in Shanxi Province of China is described in detail in the paper. The average tree numbers identification error is 18.9%. The result shows that this algorithm is an effective way to get segmented crown in real stand image. This algorithm can be powerful tools for precision forestry. We suggest users to choose suitable features and parameter values try by try in forehand applying.
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Dates and versions

hal-01559554 , version 1 (10-07-2017)

Licence

Attribution - CC BY 4.0

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Guang Deng, Zengyuan Li, Honggan Wu, Xu Zhang. Automated Extracting Tree Crown from Quickbird Stand Image. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. pp.304-311, ⟨10.1007/978-3-642-18333-1_36⟩. ⟨hal-01559554⟩
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