[Geo4All] Hydrography90m + Course Info

[SERGIO ACOSTAYLARA]

Thank you. Looks very interesting..


Sergio Acosta y Lara
Departamento de Geomática
Dirección Nacional de Topografía
Ministerio de Transporte y Obras Públicas
URUGUAY
(598)29157933 ints. 20329
http://geoportal.mtop.gub.uy/
________________________________
De: GeoForAll <geoforall-bounces at lists.osgeo.org> en nombre de Giuseppe Amatulli <giuseppe.amatulli at gmail.com>
Enviado: viernes, 4 de marzo de 2022 14:06:27
Para: geoforall at lists.osgeo.org
Asunto: [Geo4All] Hydrography90m + Course Info

Dear Colleagues
I want to point to your attention to a new global dataset that we have just released:

Hydrography90m: a new hydrographic network that accurately delineates streams and rivers, along with their topographic and topological properties.
Preprint Article: https://essd.copernicus.org/preprints/essd-2022-9/
Dissemination Video: https://doi.org/10.5446/56343   (slow connection https://www.youtube.com/watch?v=iw5auVoPXf8&t=107s)

This work is the effort of 3 years of intensive coding using only open source software:
GDAL: for tiling, cropping, mosaicking, merging, image compression.
Pktools: for masking, histogram, re-classification.
GRASS GIS for computing the hydrographies.

The overall computation accounted for a total of 52 scripts containing over 4000 code lines, took 12,418 core-hours at the High Performance Computing (HPC) facility of the Center for Research Computing, Yale University.

This is only one example of massive geo-computation that we perform using skills and knowledge that we teach at our training course: Geocomputation and Machine Learning for Environmental Applications<http://spatial-ecology.net/geocomp_ml_2022-announcement/>.
A Few spots are still available, please follow the link (http://spatial-ecology.net/geocomp_ml_2022-announcement/)  to know more about the course.

Enjoy clever computation
Best regards

--
Giuseppe Amatulli, Ph.D.

Research scientist at
School of the Environment
Yale University
New Haven, CT, USA - 06511
Twitter: @BigDataEcology<https://twitter.com/BigDataEcology>
Teaching: http://spatial-ecology.net<http://spatial-ecology.net/>
Work:  https://environment.yale.edu/profile/giuseppe-amatulli/





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