GUI Information System Based Flood Detection Using Gaussian Distance Support Vector Machine

In this paper an advanced satellite images and spectral coefficients are disusing with remote sensing. The multispectral images are analyzed through Normalized Support Vector Machine. The flood regions are analyzed through satellite devices with spectral coefficients. The earlier models are unable to get information; the following limitations are overcome through SVM model. The modified SVM is classifies the satellite images with good tracking. The measures like accuracy 93.43%, sensitivity 95.34%, and Recall 97.12% had been attained. The SVM and MSVM models are giving more accurate outcomes. The methodology is outperformance the experimental results. The remote sensing applications are more accurate compared to conventional models.