Relational Database Extension Oriented, Self-adaptive Imagery Pyramid Model

doi:10.11947/j.AGCS.2015.20140279

Abstract

Abstract:

With the development of remote sensing technology, especially the improvement of sensor resolution, the amount of image data is increasing. This puts forward higher requirements to manage huge amount of data efficiently and intelligently. And how to access massive remote sensing data with efficiency and smartness becomes an increasingly popular topic. In this paper, against current development status of Spatial Data Management System, we proposed a self-adaptive strategy for image blocking and a method for LoD(level of detail)model construction that adapts, with the combination of database storage, network transmission and the hardware of the client. Confirmed by experiments, this imagery management mechanism can achieve intelligent and efficient storage and access in a variety of different conditions of database, network and client. This study provides a feasible idea and method for efficient image data management, contributing to the efficient access and management for remote sensing image data which are based on database technology under network environment of C/S architecture.

Key words: pyramid model, self-adaptive blocking, database storage, network transmission

CLC Number:

P237

HU Zhenghua, MENG Lingkui, ZHANG Wen. Relational Database Extension Oriented, Self-adaptive Imagery Pyramid Model[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(6): 678-685.

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