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Unsupervised classification of remote multispectral sensing data
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Su, M. Y. |
| Copyright Year | 1972 |
| Description | The new unsupervised classification technique for classifying multispectral remote sensing data which can be either from the multispectral scanner or digitized color-separation aerial photographs consists of two parts: (a) a sequential statistical clustering which is a one-pass sequential variance analysis and (b) a generalized K-means clustering. In this composite clustering technique, the output of (a) is a set of initial clusters which are input to (b) for further improvement by an iterative scheme. Applications of the technique using an IBM-7094 computer on multispectral data sets over Purdue's Flight Line C-1 and the Yellowstone National Park test site have been accomplished. Comparisons between the classification maps by the unsupervised technique and the supervised maximum liklihood technique indicate that the classification accuracies are in agreement. |
| File Size | 7974064 |
| Page Count | 102 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_19720019554 |
| Archival Resource Key | ark:/13960/t4xh4c930 |
| Language | English |
| Publisher Date | 1972-04-15 |
| Access Restriction | Open |
| Subject Keyword | Remote Sensors Terrain Analysis Earth Resources Multispectral Photography Photointerpretation Data Processing Mapping Pattern Recognition Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Technical Report |
