EGI OpenIR
基于 Django 的多源遥感数据共享系统的设计与实现
Alternative TitleDesign and Implementation of Multi-source Remote Sensing Data Sharing System Based on Django
杨筠慧
Subtype硕士
Thesis Advisor陈曦
2020-06-30
Degree Grantor中国科学院大学
Place of Conferral北京
Degree Discipline工程硕士
Keyword遥感数据集成 元数据 Django 框架 数据库 Remote sensing data integration Metadata Django framework and Database
Abstract随着现代卫星遥感技术和航空摄影技术的不断发展与进步, 遥感卫星的传感器种类、遥感数据类型不断增加, 遥感数据体量也呈爆发式增长。海量、多源和异构的遥感影像数据给影像数据的管理和共享工作带来了巨大的挑战。 目前大多数从事遥感研究的单位仍采用文件方式管理影像数据, 但当数据量过大时, 这种管理方式就容易出现数据假丢失、数据重复存储、数据查找困难等一系列问题。因此针对以上问题, 本文利用 Python 主流的 Django 作为 Web 开发框架,设计了一个基于 B/S(浏览器/服务器) 架构的多源遥感影像数据管理与共享系统, 有效的集成与管理部门收集的海量多源遥感数据,并为用户提供一站式的多源遥感元数据查询服务。首先分析国内外常用的几种地理空间元数据标准和不同类型遥感数据的元数据特点, 结合系统的需求,针对不同遥感影像数据制定相应的遥感核心元数据规范,并基于制定的遥感核心元数据规范设计了一个元数据自动化提取程序。其次基于关系型数据库 PostgreSQL 的空间扩展插件 PostGIS, 建立海量多源遥感影像数据库, 并采用元数据表的形式来存储和管理遥感影像元数据信息, 实现了对海量多源遥感影像的快速存取与访问。最后采用当前流行的 Bootstrap 框架设计系统前端架构,运用 jQuery、PyEcharts、 OpenLayers 等技术实现了各个功能模块界面的可视化及影像数据云覆盖率柱状图。
Other AbstractAt present, the uninterrupted development and progress of modern satelliteremote sensing technology and aerial photography technology have not only resultedin a constant increase in the types of remote sensing satellite sensors and remotesensing data, but also led to explosive growth in the volume of remote sensing data.The massy, multi-source, and diversified remote sensing image data challenge themanagement and sharing of image data greatly. Currently, most remote sensingresearch units still store image data in files. But this data management method causesdata loss easily, repetitive data, hard-to-find data, etc., when there are excessive data.So in order to solve this, one B/S (browser/ server) framework-based managementand sharing system of multi-source remote-sensing image data is designed using thepython mainstream Django as the web development framework to effectivelyintegrate and manage the massy multi-source remote sensing data and provide userswith a one-stop inquiry service of multi-source remote sensing metadata.First of all, several kinds of common geospatial metadata standards at home andabroad and the metadata features of different types of remote sensing data wereanalyzed. In addition, the corresponding remote sensing core metadata specificationwas developed for different remote sensing image data in combination with the system'sdemands where one automatic extraction procedure of metadata was designed.Furthermore, the massy multi-source remote sensing image database was designedby the spatial extensive plugin PostGIS of relational database PostgreSQL. The remotesensing image metadata information was stored and managed in a Metadata Table inorder to obtain quick access to a massy multi-source remote sensing image.In conclusion, the current popular Bootstrap framework design system front-endframework and the jQuery, PyEcharts, OpenLayers, etc., were adopted to visualize eachfunctional module interface and display the histogram of the image data cloud coverageratio.
Subject Area测绘工程
Language中文
Document Type学位论文
Identifierhttp://ir.xjlas.org/handle/365004/15425
Collection中国科学院新疆生态与地理研究所
研究系统
Affiliation中国科学院新疆生态与地理研究所
First Author Affilication中国科学院新疆生态与地理研究所
Recommended Citation
GB/T 7714
杨筠慧. 基于 Django 的多源遥感数据共享系统的设计与实现[D]. 北京. 中国科学院大学,2020.
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