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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Shingare, P.P. Hemane, P.M. Dandekar, D.S. |
| Copyright Year | 2014 |
| Description | Author affiliation: Electron. & Tele. Dept., Coll. of Eng., Pune, India (Shingare, P.P.; Hemane, P.M.; Dandekar, D.S.) |
| Abstract | In this paper, efforts are made to detect the areas such as vegetation, water, soil, built-up area etc. from the satellite images. Landsat 7 ETM+ satellite is used for data set of images. It gives multispectral image with low resolution and panchromatic image with high resolution. For detecting the features of the urban area we require both spatial and spectral information in image. Hence these both images are first fused using different methods. Resultant fused image is then used for classification in various areas. Decision tree algorithm is used to divide the image in various classes. Various indexes such as NDVI, NDWI, SAVI and NDBI are used as decision tree rules. Some modification is done in the NDBI formula. The final results of decision tree algorithm using original and modified NDBI are compared and it was found that the decision tree algorithm using modified NDBI gives more accurate results. |
| Starting Page | 598 |
| Ending Page | 603 |
| File Size | 5482566 |
| Page Count | 6 |
| File Format | |
| e-ISBN | 9781479931408 |
| DOI | 10.1109/ICSPCT.2014.6884944 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-07-12 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Correlation coefficient Image resolution Vegetation mapping Vegetation Bandwidth NDBI Classification algorithms Decision tree Image fusion Principal component analysis |
| Content Type | Text |
| Resource Type | Article |
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