Sea Ice Detection From SAR Images of the Liaodong Bay Based on Texture Analysis
Texture analysis and study of ENVISAT ASAR sea ice imagery for the Liaodong Bay are carried out using gray level co-occurrence matrices(GLCM).In the analysis process,the effects given to the sea ice textural features by the parameters such as the GLCM orientation,the displacement,and the quantified gray level are studied in order to determine the values of the GLCM parameters and to represent the textu-ral features,which are suitable for the sea ice detection of the Liaodong Bay.Then the BP neural network classification method is used to derive an approach for sea ice detection from SAR images of the Liaodong Bay.Finally the results of this texture analysis are compared with those of the MODIS imagery and the TM imagery to verify the reliability of this method.
This text collects ten saliva wells' water of Muchengyi area in Dalian,mainly analyzing the wells of the area's water in the content of the chlorine ion,explaining that the area has already taken place the sea water invade the phenomenon.To use the kind of the groundwater of sea water invade to irrigate farmland,result in affect to the farmland soil and cause soil salinization.