ART Based Reliable Method for Prediction of Agricultural Land Changes Using Remote Sensing

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 with in situ data show that the prediction of changes in agricultural land is more accurate in the case of GUI based ART2 implementation.

影像的空间信息变化探测

为了解决影像空间信息变化探测中自动化程度和正确率均较低的问题,采用实验的方法探讨了基于属性、基于区域和基于像元的探测方法的原理,并结合专业软件ArcGIS对上述方法进行实验,取得了较好的实验结果。实验结果表明在自动发现的基础上辅以GIS、影像处理技术以及交互的方式进行信息的探测可以取得较高的探测精度和较快的探测方法。