Automated Extracting Tree Crown from Quickbird Stand Image
Artificial intelligence technologies with spatial information tech-nologies play more and more roles in precision agriculture and precision for-estry. 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 Populusxxiaohei 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.
Tree crown recognition algorithm Seeded based region growth segmentation Object based information extracting
Guang Deng Zengyuan Li Honggan Wu Xu Zhang
Institute of Forest Resource Information Techniques, Chinese Academy of Forestry,Beijing, 100091, China
国际会议
南昌
英文
304-311
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）