- Volume 19 Issue 2
This study used the multistage hierarchical clustering image classification to analyze the satellite images for the land-cover types of an area in the Korean peninsula. The multistage algorithm consists of two stages. The first stage performs region-growing segmentation by employing a hierarchical clustering procedure with the restriction that pixels in a cluster must be spatially contiguous, and finally the whole image space is segmented into sub-regions where adjacent regions have different physical properties. Without spatial constraints for merging, the second stage clusters the segments resulting from the previous stage. The image classification of hierarchical clustering, which merges step-by step two small groups into one large one based on the hierarchical structure of digital imagery, generates a hierarchical tree of the relation between the classified regions. The experimental results show that the hierarchical tree has the detailed information on the hierarchical structure of land-use and more detailed spectral information is required for the correct analysis of land-cover types.
- 대한원격탐사학회지 v.17 no.1 공간지역확장과 계층집단연결기법을 이용한 무감독 영상분류 이상훈
- Cluster Analysis for Application Anderberg,M.R.
- Ph.D.Thesis An unsupervised hierarchical clustering image segmentation and an adaptive image reconstruction system for remote sensing Lee.S
- Annal.Math.Statist. v.6 Estimation of the dimension of a model Schwartz,G.
- Remote Sensing of the Environment v.8 Red and photographic infrared linear combinations for monitoring vegetation Tucker,C.J.