A Generic Framework for Using Multi-Dimensional Earth Observation Data in GIS
A Generic Framework for Using Multi-Dimensional Earth Observation Data in GIS
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DOI：
10.3390/rs8050382
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发表时间：
2016-05
期刊：
影响因子：
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通讯作者：
Yunfeng Jiang;Min Sun;C. Yang
中科院分区：
文献类型：
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作者：
Yunfeng Jiang;Min Sun;C. Yang
对地观测数据是许多基于地理信息系统（GIS）的决策支持系统提供真实信息的关键。然而，GIS理解传统的EO数据格式（例如，分层数据格式（HDF）），因为这两个域中的内容和格式不同。为了解决这一差距之间的EO数据和GIS，各种类型的EO数据与GIS集成的障碍和策略进行了探讨，特别是与流行的地理空间数据抽象库（GDAL），许多GIS使用访问EO数据。该研究调查了四个关键技术方面：（i）设计一个通用的插件框架，用于消费不同类型的EO数据;（ii）实施该框架，以修复使用GDAL理解EO数据时GIS中的错误;以及（iii）开发商业和开源GIS的扩展（即，ArcGIS和QGIS），以展示所提出的框架及其在GDAL中的实现的可用性。利用NASA大气科学数据中心（ASDC）收集的一系列EO数据产品进行了测试，结果表明，该框架能够有效地解决EO数据解释中的各种问题，而不影响其原始内容。
Earth Observation (EO) data are critical for many Geographic Information System (GIS)-based decision support systems to provide factual information. However, it is challenging for GIS to understand traditional EO data formats (e.g., Hierarchical Data Format (HDF)) given the different contents and formats in the two domains. To address this gap between EO data and GIS, the barriers and strategies of integrating various types of EO data with GIS are explored, especially with the popular Geospatial Data Abstraction Library (GDAL) that is used by many GISs to access EO data. The research investigates four key technical aspects: (i) designing a generic plug-in framework for consuming different types of EO data; (ii) implementing the framework to fix the errors in GIS when using GDAL to understand EO data; and (iii) developing extension for commercial and open source GIS (i.e., ArcGIS and QGIS) to demonstrate the usability of the proposed framework and its implementation in GDAL. A series of EO data products collected from NASA’s Atmospheric Scientific Data Center (ASDC) are used in the tests and the results prove the proposed framework is efficient to solve different problems in interpreting EO data without compromising their original content.