Crop Identification Using Unsuperviesd ISODATA and K-Means from Multispectral Remote Sensing Imagery

Abstract

Agriculture is one of the oldest economic practice of human civilization is indeed undergoing a makeover. Remote sensing has played a significant role in crop classification, crop health and yield assessment. Hyper spectral remote sensing has also helped to enhance more detailed analysis of crop classification. This paper focuses the unsupervised classification methods i.e k-means and ISODATA for the crop identification from the remote sensing image.The experimental analysis is perfomed using ENVI tool. The color composite mappings associated with the image is also studied.

Authors and Affiliations

Namita M Kulkarni

Keywords

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  • EP ID EP390906
  • DOI 10.9790/9622-0704014549.
  • Views 103
  • Downloads 0

How To Cite

Namita M Kulkarni (2017). Crop Identification Using Unsuperviesd ISODATA and K-Means from Multispectral Remote Sensing Imagery. International Journal of engineering Research and Applications, 7(4), 45-49. https://europub.co.uk/articles/-A-390906