Research On Online Classification Of High Resolution Remote Sensing Images Based On Web Service

High resolution satellite remote sensing images make the remote sensing application more and more widely and have played an important role in agriculture,forestry,animal husbandry,land,water conservancy,environment,transportation,mapping,meteorological disasters,urban and rural construction and other industries.The traditional remote sensing image processing and analysis is realized by a single computer.With the rapid development of network technology,how to provide users with remote sensing data by Web is a research hotspot.In this paper,the framework of high resolution remote sensing image online classification and visualization of information analysis results are studied.Through the integration of remote sensing data processing algorithms and processing tools for system integration,and the use of Web Service technology to provide standard services,we propose a solution based on Web services for online image classification.The main research work of this paper is as follows:(1)This paper introduces the technical basis and service development model of remote sensing image online service,the use of ENVI Services Engine custom remote sensing image analysis and calculation algorithm model released into standard REST services for client calls,a high resolution remote sensing image online classification system is designed and implemented,which provides an online,real-time and convenient professional service resource.(2)This paper presents a solution for large data vector online fast loading.The lightweight vector storage and transmission combined with Geo JSON technology,through the grid vector display area,the vector data according to the display,greatly reducing the vector data loading and rendering time,effectively solve the large amount of data and vector drawing may lead to browser crashes,and use asynchronous loading strategy to enhance the user experience.(3)A remote sensing image classification algorithm based on multi classifier combination model is proposed.According to the sequence of cascading sample to adjust the optimal classifier performance category in the overall optimal classifier,constructed adaptive cascade model for cascade model;rejection samples,using the improved Bayesian averaging fusion rule for the two decision,output the final classification result.Experimental results show that the proposed method can effectively identify the features of high resolution remote sensing images.