KEYWORDS: Geographic information systems, Oceanography, Data modeling, Water, Analytical research, Physical oceanography, Data analysis, Data acquisition, Data processing, Satellites
With rapid development of GIS techniques, GIS techniques have come into applied period in the field of natural science and other application fields. Because of complex marine structure with many dynamic changes, tight relationship among factors in body of water, fuzzy boundary and unintuitive structure character, it is especially difficult to apply GIS to the field of ocean science. Beginning with the ocean current GIS analysis, this paper tries to develop GIS application study of oceanography. It is evident that the first problem needing to be solved is GIS expression of current field. Therefore, main information types of ocean current data that many physical oceanography scientists are using are collected. Firstly, five expression of current field commonly used in physical oceanography are: section vector expression of average current speed, component expression of current field in large area, time series expression of fixed point and expression of current path. The main work of this paper is to give corresponding GIS expression respectively according to the above expressions of ocean current. Based on the above work, corresponding GIS operational cases are given to further prove the feasibility of GIS expressions of current field. Finally, the conclusions and further work are suggested.
Remote sensing is an indispensable means for coastal band monitoring. Using satellite remote sensing data to monitor coastline variation and to analysis the eroding, depositing features and evolution process will be of great significance for the river mouth regulation, river course planning, coastal protective project program and trend prediction of coastal evolution. So, it is necessary to establish a coastline dynamic monitoring system. The system is mainly based on remote sensing and spatial information analysis techniques. In this paper, the system framework, design methodology and system functions are described in detail. The key techniques and methods involved in the system construction are particularly discussed, and they include the data preprocessing techniques, such as cloud identification and geometry fine correction, multi-scale coast edge extracting algorithm based on MRF model and coastline tide correction model with measured data or numerical simulation result as input, and coastline dynamic analysis method based on time series analysis and spatial topological analysis. Finally, an example to apply the system to the Yellow River mouth delta is given and the process flow diagram and procedures are described. The comparison of monitoring results with manually interpreted results has verified the favorable effect of the system.
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