CNN based change detection for urban imagery
Identification of changes in the green cover of urban settlements and keeping them in check has become obligatory because of the eminent dangers of climate change and pollution. The exact location, accurate identification of topographic features and the extraction of the required parameters for thei...
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| creator | Elaveni, P. Sindhuja, G. Sai Dickson, Samantha Leann |
| description | Identification of changes in the green cover of urban settlements and keeping them in check has become obligatory because of the eminent dangers of climate change and pollution. The exact location, accurate identification of topographic features and the extraction of the required parameters for their identification form a basis for change detection in the region of interest. In this project to support object-based classification, the required spectral band features are obtained. The extracted features are then used for computing the vegetation index based on which the images are labelled and are then used to train the CNN classifier. The percentage difference in vegetation index is then measured and the image is classified accordingly. |
| doi_str_mv | 10.1063/5.0047253 |
| format | Conference Proceeding |
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The percentage difference in vegetation index is then measured and the image is classified accordingly.</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/5.0047253</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>Change detection ; Feature extraction ; Parameter identification ; Vegetation ; Vegetation index</subject><ispartof>AIP conference proceedings, 2021, Vol.2336 (1)</ispartof><rights>Author(s)</rights><rights>2021 Author(s). 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Sai</creatorcontrib><creatorcontrib>Dickson, Samantha Leann</creatorcontrib><title>CNN based change detection for urban imagery</title><title>AIP conference proceedings</title><description>Identification of changes in the green cover of urban settlements and keeping them in check has become obligatory because of the eminent dangers of climate change and pollution. The exact location, accurate identification of topographic features and the extraction of the required parameters for their identification form a basis for change detection in the region of interest. In this project to support object-based classification, the required spectral band features are obtained. The extracted features are then used for computing the vegetation index based on which the images are labelled and are then used to train the CNN classifier. 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| fulltext | fulltext |
| identifier | ISSN: 0094-243X |
| ispartof | AIP conference proceedings, 2021, Vol.2336 (1) |
| issn | 0094-243X 1551-7616 |
| language | eng |
| recordid | cdi_scitation_primary_10_1063_5_0047253 |
| source | AIP Journals Complete |
| subjects | Change detection Feature extraction Parameter identification Vegetation Vegetation index |
| title | CNN based change detection for urban imagery |
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