Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Call For Paper : Vol. 9, Issue 5 , 2022
Spatial Data Analysis for Knowledge Discovery Using Segmentation Based Clustering

Author : Ch. Mallikarjuna Rao 1

Date of Publication :7th March 2016

Abstract: Segmentation Based Clustering has been accepted widely as a novel method for analysing the Spatial Data. Many types of Modern Global Positioning Systems (GPS) and also other data acquisition mechanisms are widely used for collecting huge amount of geographical data , which is expected to grow exponentially. It is observed that Mining of such huge data can extractunknown and latent information from spatial datasets that are characterized by complexity, dimensionality and large size. However, it is challenging to do so.Geographical knowledge discovery through spatial data mining has emerged as an attractive field that provides methods to leverage useful applications. Remote sensing imagery is the rich source of geographical data. Analysing such data can provide actionable knowledge for making strategic decisions. This paper proposes a Novel methodology that is used to perform clustering on remote sensing data. Thesedata sets are collected and used World Wind application, provided by NASA. The images are with .TIF extension. The methodology includes feature extraction, training, building classifier and cluster analysis. We built a prototype application that demonstrates the proof of concept. The implementation has taken native method support from Fiji and Weka to realize the proposed methodology. The empirical results revealed that the spatial clustering is made with high accuracy.

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