A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf
.
Crop Identification Using Unsuperviesd ISODATA and K-Means from Multispectral Remote Sensing Imagery
2017
International Journal of Engineering Research and Applications
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
doi:10.9790/9622-0704014549
fatcat:nfor6s5jyfganmu7rzl6f55tni