Study On The Land Use Change Of The City Coastal Zone In Lianyungang Based On The Remote Sensing Technique

Supported by a State Oceanic Administration project, to meet the demand of China's updating the datum and information of coastal zone's exploitation, the paper carries out a study on the land use change of the city coastal zone in Lianyungang, based on the remote sensing technique, which possessing the superiorities for monitoring the changes in a big scale speedily. Main work in this paper includes:1. A new rule or judge function is brought forward to improve the image classification result, in view of the conception of separating layers. Provided by the non-remote sensing information, such as terrain factor and expert knowledge, NDVI, named as a Normalized Difference Vegetation Index, and TC transform, named as Tasseled Cap transform, are respectively used to formulate rules for the image classification.2. A transition matrix is obtained, from which we can get the grip of the land use change process. Further, a series of land use change models are performed to acquire the quantity and the degree of land use change. The result manifested that the land use is in the process of developing for the city coastal zone in Lianyungang during 2000-2005, and that the soils of the farmland , residence and traffic changes acutely. The increases of the area for residence and traffic mostly root in the transition of the farmland. The other lands also change frequently during 2000-2005.3. By utilizing relevant statistical data of the Lianyungang during 2000-2005, an analysis is made to assess the drive factors for land use change. The method of Principal Component Analysis is explored to help assess the socioeconomic drive factor. It shows that nature conditions, for not a long time, contribute to the formulation of landscape pattern in local regions. But for the effects to land use change, a large number of socioeconomic factors, such as population, urbanization and industrialization process, lay a heavy stress.In the end, some research work that needs to be carried out in the future is pointed out as regards to the perfection of the image classification model and the land use change analysis model.