首页    期刊浏览 2024年12月04日 星期三
登录注册

文章基本信息

  • 标题:On-Demand Processing of Data Cubes from Satellite Image Collections with the gdalcubes Library
  • 本地全文:下载
  • 作者:Marius Appel ; Edzer Pebesma
  • 期刊名称:Data
  • 印刷版ISSN:2306-5729
  • 出版年度:2019
  • 卷号:4
  • 期号:3
  • 页码:92-107
  • DOI:10.3390/data4030092
  • 出版社:MDPI Publishing
  • 摘要:Earth observation data cubes are increasingly used as a data structure to make large collections of satellite images easily accessible to scientists. They hide complexities in the data such that data users can concentrate on the analysis rather than on data management. However, the construction of data cubes is not trivial and involves decisions that must be taken with regard to any particular analyses. This paper proposes on-demand data cubes, which are constructed on the fly when data users process the data. We introduce the open-source C++ library and R package gdalcubes for the construction and processing of on-demand data cubes from satellite image collections, and show how it supports interactive method development workflows where data users can initially try methods on small subsamples before running analyses on high resolution and/or large areas. Two study cases, one on processing Sentinel-2 time series and the other on combining vegetation, land surface temperature, and precipitation data, demonstrate and evaluate this implementation. While results suggest that on-demand data cubes implemented in gdalcubes support interactivity and allow for combining multiple data products, the speed-up effect also strongly depends on how original data products are organized. The potential for cloud deployment is discussed.
  • 关键词:earth observations; satellite imagery; R; data cubes; Sentinel-2 earth observations ; satellite imagery ; R ; data cubes ; Sentinel-2
国家哲学社会科学文献中心版权所有