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DC Field | Value | Language |
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dc.contributor.author | Kundu, Sananda | - |
dc.contributor.author | Khare, Deepak | - |
dc.contributor.author | Mondal, Arun | - |
dc.contributor.author | Mishra, P. K. | - |
dc.date.accessioned | 2020-02-14T06:15:58Z | - |
dc.date.available | 2020-02-14T06:15:58Z | - |
dc.date.issued | 2014 | - |
dc.identifier.citation | M. Pant et al. (eds.), Proceedings of the Third International Conference on Soft Computing for Problem Solving, Advances in Intelligent Systems and Computing 259, | en_US |
dc.identifier.uri | http://117.252.14.250:8080/jspui/handle/123456789/4096 | - |
dc.description.abstract | Information regarding spatial distribution of different crops in a region of multi-cropping system is required for management and planning. In the present study, multi dated LISS-III and AWiFS data were used for crop identification. The cultivable land area extracted from the landuse classification of LISS-III image was used to generate spectral-temporal profile of crops according to their growth stages with Normalised Difference Vegetation Index (NDVI) method. The reflectance from the crops on 9 different dates identified separate spectral behavior. This combined NDVI image was then classified by Fuzzy C-Mean (FCM) method again to get 5 crop types for around 12,000 km2 area on Narmada river basin of Madhya Pradesh. The accuracy assessment of the classification showed overall accuracy of 88 % and overall Kappa of 0.83. The crop identification was done for one entire Ravi season from 23 October 2011 to 10 March 2012. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Springer | en_US |
dc.subject | Crop identification | en_US |
dc.subject | NDVI | en_US |
dc.subject | Fuzzy C-Mean | en_US |
dc.subject | Narmada river basin | en_US |
dc.title | Crop Identification by Fuzzy C-Mean in Ravi Season Using Multi-Spectral Temporal Images | en_US |
dc.type | Other | en_US |
Appears in Collections: | Research papers in International Conferences |
Files in This Item:
File | Description | Size | Format | |
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IS 6. Kundu_Crop Identification by Fuzzy C-Mean_Soft computing (2014).pdf | 728.74 kB | Adobe PDF | View/Open |
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