TITLE:
ART Based Reliable Method for Prediction of Agricultural Land Changes Using Remote Sensing
AUTHORS:
Muthu Pandian Malini, Madurai Chidambaram Sashi Kumar, N. Sakthieswaran
KEYWORDS:
ART2 Classification, Land Cover, Multi Temporal Analysis, Land Change Detection, Remote Sensing
JOURNAL NAME:
Circuits and Systems,
Vol.7 No.6,
May
27,
2016
ABSTRACT: This paper focuses on
prediction of change in agricultural lands by using ART2 algorithm. The
existing method used ENVI and ARCGIS software to predict the changes in land,
which showed less accuracy due to human errors. To overcome this user friendly
GUI based ART2 algorithm has been developed in java to obtain more accuracy in
prediction of changes in land. The input is satellite temporal images of the
years 1990 and 2014. By using the ART2 algorithm, the input images of the years
1990 and 2014 are classified, where the features are identified to form
cluster. The clustered image is given as input and pixel to pixel comparison
method in ART2 is implemented in java, for detecting the changes in
agricultural lands. The comparison results of ENVI and ARCGIS and GUI based
ART2 within situdata show that the prediction of
changes in agricultural land is more accurate in the case of GUI based ART2
implementation.