{"id":473,"date":"2021-08-12T00:15:49","date_gmt":"2021-08-12T00:15:49","guid":{"rendered":"https:\/\/eodatahub.com\/?page_id=473"},"modified":"2021-09-24T09:00:29","modified_gmt":"2021-09-24T09:00:29","slug":"eo-knowledge-mine","status":"publish","type":"page","link":"https:\/\/eodatahub.com\/index.php\/eo-knowledge-mine\/","title":{"rendered":"EO Repository"},"content":{"rendered":"
<\/div> \"\"<\/div> <\/div>

Tutorial<\/h2>

How to use SNAP? Click below to learn step-by-step process of downloading images from Sentinel-2 (as an example) and basic image processing created by Sean O\u2019Kane.<\/a><\/p> SNAP TUTORIAL<\/a><\/div> <\/div><\/div> <\/div>

Video Tutorials<\/h2>

See below for a series of tutorials delivered via YouTube from Copernicus, RUS Copernicus, ESA and NASA. <\/p><\/div> <\/div>

<\/div>
<\/div>
See here<\/a><\/div> <\/div><\/div> <\/div>
Crop mapping with Sentinel-2\n
\n<\/h5>

RUS Webinar: Crop mapping with Sentinel-2 focusing on classification algorithms\n

\n<\/p> <\/div> <\/div><\/div> <\/div>

<\/div>
<\/div>
See here<\/a><\/div> <\/div><\/div> <\/div>
SNAP \u2013 Calculate Normalized Difference Vegetation Index (NDVI)<\/h5>

SNAP tool tutorial for calculating Normalized Difference Vegetation Index (NDVI)<\/p><\/div> <\/div><\/div> <\/div>

<\/div>
<\/div>
See here<\/a><\/div> <\/div><\/div> <\/div>
Crop monitoring using Sentiel-1\n\n\n<\/h5>

ESA led advanced course on cropping monitoring with dual-pol S1<\/p><\/div> <\/div><\/div> <\/div>

<\/div>
<\/div>
See here<\/a><\/div> <\/div><\/div> <\/div>
Introducing TROPOMI(Sentinel-5P) \u2013 High Resolution NO2 Observations from Space<\/h5>

ARSET Webinar: NASA led advance training on introduction to TROPOMI, available data products for NO2, information about products detecting AI, CO, SO2, and HCHO, an overview of accessing TROPOMI data, and an exercise for downloading the data. >><\/a><\/span><\/p> <\/div> <\/div><\/div> <\/div>

<\/div>
<\/div>
See here<\/a><\/div> <\/div><\/div> <\/div>
Python Tools for Analyzing NO2\n<\/h5>

NASA ARSET Webinar: This will primarily consist of going through an exercise on using updated python codes to work with TROPOMI data. This will include reading, mapping, extracting over a point location, gridding the data, and dumping the data to a CSV file. >><\/span><\/a>\n

\n<\/p> <\/div> <\/div><\/div> <\/div><\/div>

<\/div> <\/div><\/div> <\/div>

Lectures<\/h2>

Access lectures below on various EO topics for your purpose.<\/p><\/div> <\/div>

<\/div>
<\/div>
Read More<\/a><\/div> <\/div><\/div> <\/div>
The Use of Earth Observation in
\nAgriculture<\/h5>

by Stuart Green<\/a><\/p><\/div> <\/div><\/div> <\/div>

<\/div>
<\/div>
Read More<\/a><\/div> <\/div><\/div> <\/div>
Monitoring & Modelling of Land Surface Processes<\/h5>

by  Jochem Verrelst\ufeff<\/a><\/a><\/p><\/div> <\/div><\/div> <\/div>

<\/div>
<\/div>
Read More<\/a><\/div> <\/div><\/div> <\/div>
Basic GIS knowledge vector and raster data\n<\/h5>

by Marijan Grgic\n
University of Zagreb, Faculty of Geodesy<\/p><\/div> <\/div><\/div> <\/div><\/div>

<\/div> <\/div><\/div> <\/div>

Case Studies<\/h2>

Access interesting case studies on Copernicus data published by EARSC\ufeff<\/a> and others.<\/p><\/div> <\/div>

<\/div>
<\/div>
Read More<\/a><\/div> <\/div><\/div> <\/div>
Flood Management in Ireland\n\n\n<\/h5>

A study of  social, economical and environmental impact of floods in Ireland during the winter of 2015-2016 published in 2018 using Copernicus Emergency Management Service data.\n<\/p><\/div> <\/div><\/div> <\/div>

<\/div>
<\/div>
Read More<\/a><\/div> <\/div><\/div> <\/div>
Water Quality Management in Germany<\/h5>

A study to detect the presence of Harmful Algal Bloom to determine the water quality of the lakes in Germany using Sentinel 2 and 3 data.\n<\/p><\/div> <\/div><\/div> <\/div>

<\/div>
<\/div>
Read More<\/a><\/div> <\/div><\/div> <\/div>
Peatland Management in the UK<\/h5>

A study conducted by the water utilities in the UK using Sentinel 1 data to improve
\nthe management of peatlands, leading
\nto better water quality for local citizens,
\nreduced costs of purification for the water
\ncompanies and strong environmental benefits.<\/p><\/div> <\/div><\/div> <\/div>

<\/div>
<\/div>
Read More<\/a><\/div> <\/div><\/div> <\/div>
Forest Monitoring in Portugal\n<\/h5>

Copernicus Sentinel data and AI are being
\nused to provide continuous forest inventories
\nin Portugal, identify land use (changes) as well
\nas check upon the health status of trees in
\nsupport of forest managers and the pulp
\n& paper industry.<\/p><\/div> <\/div><\/div> <\/div>

<\/div>
<\/div>
Read More<\/a><\/div> <\/div><\/div> <\/div>
Grassland Monitoring in Estonia<\/h5>

In this case we study an innovative system, empowered by Sentinel data, which is used to ensure farmers in Estonia are abiding by CAP regulation and maintaining permanent grassland in the interest of biodiversity.\n<\/p><\/div> <\/div><\/div> <\/div>

<\/div>
<\/div>
Read More<\/a><\/div> <\/div><\/div> <\/div>
Forestry Management in Sweden<\/h5>

This case is all about the use of satellite imagery to monitor the Swedish forests for \u201cclear-cuts\u201d.\n\n

\n<\/p><\/div> <\/div><\/div> <\/div><\/div>

<\/div> <\/div><\/div> <\/div>

Upcoming Trainings<\/h2>