Name
Title | ||
|---|---|---|
Spatial knowledge based complicated urban area classification from high-resolution remote sensing image |
Abstract | ||
|---|---|---|
Combining spectral and spatial information can improve land use classification of high-resolution data. However, the use of spatial information always focus on objects' spatial pattern, whereas not pay enough attention to spatial relationship, which is more convenient and effective in remote sensing classification. This letter proposes a spectral-spatial information method, which aims to exploit objects' spatial relationships in high resolution imagery, and then integrate it with spectral information in remote sensing classification. We experiment on urban mapping based on spectral-spatial information using Quickbird imagery, and compare its result with supervised classification methods like maximum likelihood classification, and support vector machine (SVM) classification. The results show that the proposed method yield better performance than the others in both precision and rationality. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICSDM.2011.5969075 | ICSDM |
Keywords | Field | DocType |
remote sensing,spectral information,high-resolution remote sensing image,image processing,land use classification,maximum likelihood estimation,complicated urban area classification,land use planning,spatial knowledge,urban area,spectral-spatial information method,image classification,support vector machine,geophysical image processing,maximum likelihood classification,classification,support vector machines,quickbird imagery,accuracy,high resolution,data mining,feature extraction,knowledge base | Spatial analysis,Data mining,Geographic information system,Computer science,Remote sensing,Image processing,Artificial intelligence,Contextual image classification,Iterative reconstruction,Pattern recognition,Support vector machine,Knowledge-based systems,Feature extraction | Conference |
ISBN | Citations | PageRank |
978-1-4244-8352-5 | 0 | 0.34 |
References | Authors | |
7 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cheng Qiao | 1 | 25 | 3.82 |
| Jian-Cheng Luo | 2 | 99 | 20.75 |
| Zhanfeng Shen | 3 | 68 | 12.60 |
| Zhiwen Zhu | 4 | 43 | 11.61 |
| Wei Wu | 5 | 5 | 1.86 |