Research on Object-Oriented Classification Technology for Remote Sensing Imagery of Coastal Zone

Terrain identification of coastal is of great significance for coastal development activities and coastal terrain survey in overseas areas. However, due to the complex characteristics of coastal features, the use of remote sensing images for automatic feature classification and recognition has become a current research hotspot. Utilizing the homogeneous and homogeneous spectral characteristics of hyperspectral remote sensing images and the characteristics of coastal zone elements, an object-oriented shoreland classification technique is proposed after performing operations such as atmospheric correction and image enhancement preprocessing on hyperspectral remote sensing data, which enables automatic identification and extraction of feature types and geomorphological information in the coastal zone. This method overcomes the limitation of the traditional hyperspectral remote sensing classification method, which takes image element as the processing unit, and synthesizes the spatial characteristics and spectral characteristics of the features, which greatly reduces the classification spots and significantly improves the classification effect.