An effective technique to identify a river’s stage through satellite images by means of RBFNN

Abstract

Today, a significant role is played by satellite image processing in the research improvement of various subject of analysis such as Astronomy, Remote Sensing, GIS, Agriculture Monitoring and Disaster Management. Forecasting natural disasters so that necessary safety measures can be taken to safeguard the surroundings is the objective behind the utilisation of remote sensing images in most of the researches. A vital role is played by water resource analysis besides others, in these researches. Several methods are conventionally used for the analysis and computation of the level of water in water resources. In this paper, the stage of a river is predicted utilising satellite images of the river. Initially, in the pre-processing phase, the image is filtered and then converted to the LAB colour space for acute analysis. Subsequently, the segmentation process is carried out using the designed Radial Basis Function Neural Network (RBFNN) and then morphological operation is performed on the image. After that in the testing phase, the segmented image is analysed and the stage of the river is identified as either normal or flood or draught using the designed RBFNN.

Keywords:

• satellite image
• remote sensing image
• water stage
• Radial Basis Function Neural Network (RBFNN)
• river water level
• water region
• morphological operation