• V.P.Muthukumar
• Dr.S.Subbaiah

Data Mining plays a vital role in research areas. Data mining is the process of extracting usable information from large amount of data. It is one of the most significant research areas in computer science. It is a calculation process of finding and determining valuable information from huge data set. Data Mining and Knowledge Discovery is a developing field of research that have been attracting many researchers to extract meaningful pieces of information from the dataset. In Remote Sensing Supervised classification of satellite images are commonly used. It is used to create the thematic maps based on a training set chosen by domain experts. These training set is called as ROI (Regions Of Interest) which is statistically characterize each class for e.g. coconut, sand of the satellite image. For each image, a set of ROI is manually created by domain expert. When we are using large number of images with high resolution will create difficulties of manual creation of ROI for each image. It is very time and money consuming process. In this paper, we proposed a method of semi-automatic approach based on clustering. It is to limit the number of ROI done by experts. After that, we use decision trees on a binary decomposition of RGB components for improving the classification. The Experiments have been done on 306 high resolution images of Tuamotu Archipelago.

CLASSIFICATION OF COCONUT FIELDS USING DATA MINING ON A LARGE DATABASE OF HIGH-RESOLUTION IKONOS IMAGES

"CLASSIFICATION OF COCONUT FIELDS USING DATA MINING ON A LARGE DATABASE OF HIGH-RESOLUTION IKONOS IMAGES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.50-58, March-2019, Available :http://www.jetir.org/papers/JETIRAQ06011.pdf

"CLASSIFICATION OF COCONUT FIELDS USING DATA MINING ON A LARGE DATABASE OF HIGH-RESOLUTION IKONOS IMAGES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp50-58, March-2019, Available at : http://www.jetir.org/papers/JETIRAQ06011.pdf