Senthilnath, J and Omkar, SN and Karnwal, Nitin and Mani, V (2011) Hierarchical artificial immune system for crop stage classification. In: 2011 Annual IEEE India Conference (INDICON), 16-18 Dec. 2011, Hyderabad.
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This paper presents a new hierarchical clustering algorithm for crop stage classification using hyperspectral satellite image. Amongst the multiple benefits and uses of remote sensing, one of the important application is to solve the problem of crop stage classification. Modern commercial imaging satellites, owing to their large volume of satellite imagery, offer greater opportunities for automated image analysis. Hence, we propose a unsupervised algorithm namely Hierarchical Artificial Immune System (HAIS) of two steps: splitting the cluster centers and merging them. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The classification results have been compared with K-means and Artificial Immune System algorithms. From the results obtained, we conclude that the proposed hierarchical clustering algorithm is accurate.
|Item Type:||Conference Proceedings|
|Additional Information:||Copyright of this article belongs to the IEEE.|
|Keywords:||Crop Stage Classification; Hierarchical Artificial Immune System; Principal Component Analysis|
|Department/Centre:||Division of Mechanical Sciences > Aerospace Engineering (Formerly, Aeronautical Engineering)|
|Date Deposited:||02 May 2013 10:12|
|Last Modified:||02 May 2013 10:12|
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