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爱体育

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@aitiyupro • Joined Oct 2024 • Active 3 months ago

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First Name	爱
Last Name	体育
Nickname	aitiyupro
Short Description	欢迎来到爱体育！我们为您提供全面的在线体育博彩服务，覆盖足球、篮球、网球等多个热门赛事。平台安全可靠，实时动态赔率，用户友好的界面，以及丰厚的注册奖金和促销活动，为您带来无与伦比的体育竞猜体验。加入爱体育，享受每一场比赛的激情与乐趣！ #爱体育 Email: aitiyu.pro@gmail.com Website: https://aitiyu.pro/ Social: https://www.facebook.com/aitiyupro/ https://x.com/aitiyupro https://www.youtube.com/@aitiyupro https://www.pinterest.com/aitiyupro/ https://vimeo.com/aitiyupro https://bit.ly/m/aitiyupro https://www.blogger.com/profile/15084376411094399143 https://gravatar.com/aitiyupro https://www.reddit.com/user/aitiyupro/ https://www.openstreetmap.org/user/aitiyupro https://www.behance.net/aitiyupro https://aitiyupro.wordpress.com/ https://ameblo.jp/aitiyupro/ https://b.hatena.ne.jp/aitiyupro/bookmark https://issuu.com/aitiyupro https://profile.hatena.ne.jp/aitiyupro/ https://sites.google.com/view/aitiyupro/ https://disqus.com/by/aitiyupro/about/ https://groups.google.com/g/aitiyupro/c/kfdzd-LIdbE https://jakle.sakura.ne.jp/pukiwiki/?aitiyupro https://500px.com/p/aitiyupro https://fliphtml5.com/homepage/gqsab/aitiyu.pro/ https://www.mixcloud.com/aitiyupro/ https://www.producthunt.com/@aitiyupro https://aitiyupro.amebaownd.com/posts/55546452 https://connect.garmin.com/modern/profile/0a88aff6-b7f3-4d52-9b3f-7a96e1f38a55 https://onlyfans.com/aitiyupro https://profile.ameba.jp/ameba/aitiyupro https://public.tableau.com/app/profile/.21675686/vizzes https://readthedocs.org/projects/aitiyupro/

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111

References and Further Reading

1.1 What is a Platform

Further reading

Earth Observation Cloud Platform Concept Development Study Report: https://docs.ogc.org/per/21-023.html
Big Earth data: disruptive changes in Earth observation data management and analysis? https://www.tandfonline.com/doi/full/10.1080/17538947.2019.1585976
Enabling the Big Earth Observation Data via Cloud Computing and DGGS: Opportunities and Challenges: https://www.mdpi.com/2072-4292/12/1/62
An Overview of Platforms for Big Earth Observation Data Management and Analysis: https://www.mdpi.com/2072-4292/12/8/1253
The openEO API–Harmonising the Use of Earth Observation Cloud Services Using Virtual Data Cube Functionalities: https://www.mdpi.com/2072-4292/13/6/1125
ESA Earth Observation Exploitation Platform Common Architecture (EOEPCA): https://eoepca.org

1.2 What is a Data Cube?

Further Reading

David Montero Loaiza et al (2023). Data Cubes for Earth System Research: Challenges Ahead. Earth ArXiv (Preprint). https://doi.org/10.31223/X58M2V
Popular Data Cube Management Systems:

References

openeo.org (2022). What are Data Cubes.
ESA (2018). Earth System Data Lab.
Maximilian Söchting (2022). LexCube – Leipzig Explorer of Earth Data Cubes

1.3 Open Science, Open Data and the FAIR Principles

Further Reading

Help for understanding licenses and choosing the right Open Source license

Legal (FOSSA) (2023). Software Licencses In Plain English.
GitHub Inc. (2023) Choose an open source license.

And plentiful resources on open source projects, how to contribute and incorporate them into your work

opensource.com (2023). Open Source resources.

References

European Commission (2022). What is open data?. https://data.europa.eu/elearning/en/module1/#/id/co-01 –
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Open Knowledge Foundation (2022). Open Data Handbook.
Fürst, Elena, Gänsdorfer, Nikos, Kalová, Tereza, Macher, Therese, Schranzhofer, Hermann, Stork, Christiane, & Thöricht, Heike (2022). Open Educational Resources Research Data Management. DOI: 10.5281/zenodo.6923397
ARDC Ltd. (2022). How to Make Your Data FAIR. DOI: 10.5281/zenodo.7426145.
GO FAIR (2022). The FAIRification Process.
Mapscaping Podcast with Paul Ramsey (2021). GDAL – Geospatial Data Abstraction Library
CEOS (2022). CEOS Analysis Ready Data.

2.1 Data Discovery

Further Reading

STAC tutorials
Echoes in space course

References

STAC
OWSLib
STAC Python Client (pystac_client)
radiantearth.github.io/stac-browser
OpenSearch specification

2.2 Data Properties

Further Reading

Standartized data management with STAC
STAC sessions from FOSS4G 2023

2.3 Data Access

References

openeo.org – About OpenEO
Edzer Pebesma, Wolfgang Wagner, Jan Verbesselt, Erwin Goor, Christian Briese, Markus Neteler (2016). OpenEO: a GDAL for Earth Observation Analytics. https://r-spatial.org/2016/11/29/openeo.html
openeo.org – Project Deliverable 22
openeo.org (2022). Processes on Datacubes

3.2 Result Validation

Further Reading

Video: Meyer, Hanna: Machine learning-based maps of the environment: challenges of extrapolation and overfitting. OpenGeoHub Summer School 2022 – KISTE project workshop, OpenGeoHub Foundation, 2022. https://doi.org/10.5446/59412

References

Meyer, H., Pebesma, E. Machine learning-based global maps of ecological variables and the challenge of assessing them. Nat Commun 13, 2208 (2022). https://doi.org/10.1038/s41467-022-29838-9
Meyer, H., & Pebesma, E. (2021). Predicting into unknown space? Estimating the area of applicability of spatial prediction models. Methods in Ecology and Evolution, 12, 1620–1633. https://doi.org/10.1111/2041-210X.13650
Loew et al. (2017): https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1002/2017RG000562
Brenning et al. (2012): https://doi.org/10.1109/IGARSS.2012.6352393
Valavi et al. (2019): https://doi.org/10.1111/2041-210X.13107
Roberts et al. (2017): https://doi.org/10.1111/ecog.02881
Ploton et al. (2020): https://doi.org/10.1038/s41467-020-18321-y
Milà et al. (2022): https://doi.org/https://doi.org/10.1111/2041-210X.13851
Linnenbrink et al. (2023): https://doi.org/10.5194/egusphere-2023-1308
Sabatini et al. (2022): https://doi.org/10.1038/s41467-022-32063-z