Crop identification by fuzzy C-mean in ravi season using multi-spectral temporal images

1Citations
Citations of this article
1Readers
Mendeley users who have this article in their library.
Get full text

Abstract

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.

Cite

CITATION STYLE

APA

Kundu, S., Khare, D., Mondal, A., & Mishra, P. K. (2014). Crop identification by fuzzy C-mean in ravi season using multi-spectral temporal images. In Advances in Intelligent Systems and Computing (Vol. 259, pp. 391–401). Springer Verlag. https://doi.org/10.1007/978-81-322-1768-8_35

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free