文章基本信息

标题：Architecture and prototypical implementation of a semantic querying system for big Earth observation image bases
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作者：Dirk Tiede ; Andrea Baraldi ; Martin Sudmanns 等
期刊名称：European Journal of Remote Sensing
电子版ISSN：2279-7254
出版年度：2017
卷号：50
期号：In Progress
页码：452-463
DOI：10.1080/22797254.2017.1357432
摘要：ABSTRACT Spatiotemporal analytics of multi-source Earth observation (EO) big data is a pre-condition for semantic content-based image retrieval (SCBIR). As a proof of concept, an innovative EO semantic querying (EO-SQ) subsystem was designed and prototypically implemented in series with an EO image understanding (EO-IU) subsystem. The EO-IU subsystem is automatically generating ESA Level 2 products (scene classification map, up to basic land cover units) from optical satellite data. The EO-SQ subsystem comprises a graphical user interface (GUI) and an array database embedded in a client server model. In the array database, all EO images are stored as a space-time data cube together with their Level 2 products generated by the EO-IU subsystem. The GUI allows users to (a) develop a conceptual world model based on a graphically supported query pipeline as a combination of spatial and temporal operators and/or standard algorithms and (b) create, save and share within the client-server architecture complex semantic queries/decision rules, suitable for SCBIR and/or spatiotemporal EO image analytics, consistent with the conceptual world model.
关键词：Big data ; Earth observation ; Level 2 product ; spatiotemporal objects and events ; array database ; semantic content; based image retrieval