Vertical AtlasVertical Atlas

Presentation website with Andrei Bocin Dumitriu's toolkit

1. GIS: QGIS, ArcGIS: <https://www.qgis.org/en/site/ Free light version for Mac: <https://researchguides.dartmouth.edu/gis/mac 2. Database: PostgreSQL (pgAdmin III/OSGeo)
3. EO: SNAP, PolSARpro v6.0 (Biomass Edition) Toolbox

The Copernicus Open Access Hub (previously known as Sentinels Scientific Data Hub) provides complete, free and open access to Sentinel-1, Sentinel-2, Sentinel-3 and Sentinel-5P user products, starting from the In-Orbit Commissioning Review (IOCR).

Sentinel Hub services currently support all of the following data sources, which include freely available and commercial satellites, digital elevation models and an option to bring your own data. Visit the Custom Script Repository to explore the available data visualisations (bands, composites, indices and more complex custom scripts). If you are interested in how custom visualisations are made and how you can make them yourself, you can use custom processing scripts.

1. Sentinel Hub Data
2. Application for showing historical and future orbits
3. Database of remote sensing indexes

Cloud computing environments such as AWS and DIAS facilitate the high scale processing of Earth observation (EO) data, but considerable effort and advanced technical knowledge are still required for users to take advantage of these cloud computing environments. In addition to analytical tasks, the EO community scientists and users face challenges regarding the management of these environment computational resources. Thus there is a need for user-friendly solutions that provide high-level analytical tools for EO community researchers and users, abstracting the technical issues of these cloud computing environments.

The Sentinel Hub or GEE platforms are just some examples of this kind of solution. These platforms use cloud computing services to access and process Copernicus EO or Nasa data sets and provide a high-level programming interface that allows users to deal with them without worrying about technical details.
Moreover, in recent years a number of commercial platforms and services have been developed and are ready to use. These commercial solutions are one-stop applications with reach interface, custom algorithms developed for many domains (including agriculture, forestry and infrastructure) or friendly UX, but they come at a cost.

Cloud computing environments, platforms and applications:

1. AWS - cloud computing environment which allows scaling up solutions with a large data repository, powerful AI; pre-configured proto-platform exists as AIM (cloud image/docker), for example for processing ESA Sentinel-1 data and production of interferograms
2. Google Earth Engine - is a free platform for big EO Data Management and Analysis (note: pre-registration is required at least one week in advance in order to run applications during the workshop series)
3. Sentinel Hub
4. EO Browser & Sentinel Playground
5. TEP - ESA's Thematic Platforms

Virtual computers & cloud software and infrastructure systems:

1. ESA's demo virtual machine (only available to EU users)
2. Jupyteo - demo using Jupyter, EO data processing, cloud-based IDE

1. European Data Cube: Free demo account (limited data and period), fair rates
2. Copernicus/DIAS: Mundi, Creodias, Sobloo, WekEO, Onda: ESA commercial platforms for cloud infrastructure that also provide tools, applications and API.

Basic level
For an introduction to geographic information systems, check out this tutorial by Esri Academy to introduce yourself to the main GIS concepts and applications.

Intermediate level
For those already accustomed to mapping and who want to go deeper to explore its visualisation possibilities, take a look at Pennsylvania State University's online course.

Advanced level
If you are already working with GIS and coding, this course, also from Pennsylvania State University, explores how to use Python in an advance way in geographic information systems.

The Digital Methods Initiative is a group of media researchers who design methods and tools for repurposing online devices and platforms (social media and other data) for research into social and political issues. You can read more about them here.

Some of their projects include Climaps, a mapping and storytelling virtual atlas of actions, policies and adaptation efforts to fight climate change, and Odycceus, studying opinion dynamics and conflict in the EU.

They also provide tools that might be useful in the context of satellite data:

Issue Geographer: Geo-locates the organisations on an Issue Crawler map, using whois information, and visualises the organisations' registered locations on a geographical map (it's related to the Issuecrawler tool).

Colors For Data Scientists: Generate and refine palettes of optimally distinct colours.

Google Earth Engine combines a catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities and makes it available for scientists, researchers, and developers to detect changes, map trends, and quantify differences on the Earth's surface. It's a great way to get acquainted with satellite data and explore its possibilites. Some datasets include:

Global Human Settlement Layers
Nighttime Lights Time Series
New York City Taxi and Limousine Commission (TLC) Trip Record Data
Global Forest Cover Change