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Springer Science and Business Media LLC

  1865-0473

  1865-0481

 

Cơ quản chủ quản:  Springer Heidelberg , Springer Verlag

Lĩnh vực:
Earth and Planetary Sciences (miscellaneous)

Các bài báo tiêu biểu

DrinC: a software for drought analysis based on drought indices
- 2015
Dimitris Tigkas, Harris Vangelis, George Tsakiris
On the utility of identification schemes for digital earth science data: an assessment and recommendations
Tập 4 - Trang 139-160 - 2011
Ruth E. Duerr, Robert R. Downs, Curt Tilmes, Bruce Barkstrom, W. Christopher Lenhardt, Joseph Glassy, Luis E. Bermudez, Peter Slaughter
In recent years, a number of data identification technologies have been developed which purport to permanently identify digital objects. In this paper, nine technologies and systems for assigning persistent identifiers are assessed for their applicability to Earth science data (ARKs, DOIs, XRIs, Handles, LSIDs, OIDs, PURLs, URIs/URNs/URLs, and UUIDs). The evaluation used four use cases that focused on the suitability of each scheme to provide Unique Identifiers for Earth science data objects, to provide Unique Locators for the objects, to serve as Citable Locators, and to uniquely identify the scientific contents of data objects if the data were reformatted. Of all the identifier schemes assessed, the one that most closely meets all of the requirements for an Unique Identifier is the UUID scheme. Any of the URL/URI/IRI-based identifier schemes assessed could be used for Unique Locators. Since there are currently no strong market leaders to help make the choice among them, the decision must be based on secondary criteria. While most publications now allow the use of URLs in citations, so that all of the URL/URI/IRI based identification schemes discussed in this paper could potentially be used as a Citable Locator, DOIs are the identification scheme currently adopted by most commercial publishers. None of the identifier schemes assessed here even minimally address identification of scientifically identical numerical data sets under reformatting.
SAR image analysis techniques for flood area mapping - literature survey
Tập 10 Số 1 - Trang 1-14 - 2017
R. Manavalan
Predicting and mapping land cover/land use changes in Erbil /Iraq using CA-Markov synergy model
Tập 14 Số 1 - Trang 393-406 - 2021
Nabaz R. Khwarahm, Sarchil Qader, Korsh Ararat, Ayad M. Fadhil Al-Quraishi
Successive-station monthly streamflow prediction using neuro-wavelet technique
Tập 7 Số 4 - Trang 217-229 - 2014
Ali Danandeh Mehr, Ercan Kahya, Farzaneh Bagheri, Ekin Deliktas-Ozdemir
A geologic timescale ontology and service
- 2015
Simon J. Cox, S.M. Richard
OpenAltimetry - rapid analysis and visualization of Spaceborne altimeter data
- 2022
S. S. Khalsa, A. A. Borsa, Viswanath Nandigam, Minh Q. Phan, Kai Lin, C. J. Crosby, H. A. Fricker, Chaitan Baru, Luis Alberto Lopez
Abstract

NASA’s Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) carries a laser altimeter that fires 10,000 pulses per second towards Earth and records the travel time of individual photons to measure the elevation of the surface below. The volume of data produced by ICESat-2, nearly a TB per day, presents significant challenges for users wishing to efficiently explore the dataset. NASA’s National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC), which is responsible for archiving and distributing ICESat-2 data, provides search and subsetting services on mission data products, but providing interactive data discovery and visualization tools needed to assess data coverage and quality in a given area of interest is outside of NSIDC’s mandate. The OpenAltimetry project, a NASA-funded collaboration between NSIDC, UNAVCO and the University of California San Diego, has developed a web-based cyberinfrastructure platform that allows users to locate, visualize, and download ICESat-2 surface elevation data and photon clouds for any location on Earth, on demand. OpenAltimetry also provides access to elevations and waveforms for ICESat (the predecessor mission to ICESat-2). In addition, OpenAltimetry enables data access via APIs, opening opportunities for rapid access, experimentation, and computation via third party applications like Jupyter notebooks. OpenAltimetry emphasizes ease-of-use for new users and rapid access to entire altimetry datasets for experts and has been successful in meeting the needs of different user groups. In this paper we describe the principles that guided the design and development of the OpenAltimetry platform and provide a high-level overview of the cyberinfrastructure components of the system.