Research On Remote Sensing Image Pyramid Model For Big Data

With the advent of the era of big data,big data has a great impact on the data processing related processes of management information systems.Information management systems have increasingly refined the management of data,and management projects driven by big data have fully exploded.Remote sensing technology has been widely applied to all aspects of social work.How to effectively manage it under the influence of remote sensing big data is the most important issue we need to solve.Image pyramid technology and distributed technology are key technologies for managing large image data.It can realize efficient reading of large image data and is of great significance to the application of remote sensing images.This paper mainly studies the management of image pyramid data driven by remote sensing big data,including the study of image pyramid construction methods and image pyramid management optimization.For the study of image pyramid construction methods,multi-resolution image layering strategies are proposed for multi-source and overlapping area images,and irregular block images are proposed for irregular images;then,a template image pyramid model is constructed and Hilbert curve coding is performed.The use of the parent encoding + sub-encoding method to improve the index,so as to achieve fast image loading and display;finally through the incremental update of the image pyramid research to achieve the replacement of the image.In terms of image pyramid management optimization,an image data storage structure based on HBase was established,and its row key Row Key was improved,and a quick read process of the image was designed to implement the parallel storage of image blocks.The Pyramid block cache area based on GeoWebCache cache middleware is set to shorten the retrieval time of images and improve the query loading efficiency of images.Finally,error correction technology not only ensures the reliability of the pyramid image data,but also improves the storage utilization.Finally,realizing the Management of Remote Sensing Image Data Driven by Big Data Based on HDFS and HBase Cluster Environment.The advantage of irregular image blocking strategy for irregular images is verified through experimental analysis.The improved index structure is superior to the improvement in the reading speed.The parallelization architecture speeds up the storage of data.The HBase database is superior to relational databases in the management of unstructured data.The setting of the buffer area improves the loading efficiency of images,and the research results can meet the demand for efficient management of massive remote sensing images and have important practical value.