Illustrative: satellite orbits, their ground swaths or the lines of sight a receiver keeps
Risk Academy, led by the Nexus Consortium · Earth and Environmental Sciences · Department of Climate and Ocean Sciences
Satellites, observing networks, reanalyses and Earth system twins
Earth observation and Earth system data
Every risk layer on the stage started as an observation: a satellite overpass, a gauge, a buoy or a reanalysis that joins them with a model.
- Department
- Department of Climate and Ocean Sciences
- Courses
- In preparation
- Levels
- In development
- Labs
- In development
- Satellite missions and sensors (optical, radar, thermal, altimetry, gravimetry)
- In situ observing networks
- Reanalysis datasets such as ERA5
- GCOS Essential Climate Variables
- Earth system digital twins and Destination Earth
- Geospatial foundation models and satellite embeddings
- Analysis-ready data and cloud-native formats
- Product validation and uncertainty
- Copernicus and open data policies
Build a twin of any place
Search any place or open the world; the layers and generators follow earth observation and Earth system data on the planet map, the globe and in 3D.
Earth and Environmental SciencesAny placeTwin builder
- Terrain 63 to 471 m
- River 435 km
- Canal 2,280 km
- River discharge, GloFAS via Open-Meteo: read live when the 3D twin opens
- Vegetation index, MODIS Terra NDVI 8-day: read live when the 3D twin opens
- Soil moisture, SMAP L3 (daily): read live when the 3D twin opens
- Precipitation rate, GPM IMERG (30 minutes): read live when the 3D twin opens
- Surface water extent, OPERA DSWx (HLS): read live when the 3D twin opens
- True colour at 30 m, HLS Sentinel-2 (daily granules): read live when the 3D twin opens
Drag to move, right drag or Shift with a drag to turn and tilt, Ctrl with the wheel to zoom. Keyboard: arrows move, Shift with arrows turn and tilt, + and – zoom, 0 resets, V steps through the views, Escape clears.
Places4
Layers8
iCredits
- Terrain Surface height in whole metres on the plan's grid of cells about three hundred by four hundred metres; the Monferrato hills reach about five hundred metres Produced using Copernicus WorldDEM-30 © DLR e.V. 2010–2014 and © Airbus Defence and Space GmbH 2014–2018 provided under COPERNICUS by the European Union and ESA; all rights reserved. read 2026-10-17. Estimate: A digital surface model: trees and roofs are in the heights. Relief exaggeration is printed on the stage.
- Rivers and named canals The Po, its tributaries and the longest named irrigation canals of the plain as centrelines, with their length by class. © OpenStreetMap contributors, ODbL 1.0. data as of 2026-07-15. Estimate: Centrelines as mapped, simplified to 25 m and capped at the 700 longest ways; no discharge or width is implied by the line.
- River discharge, GloFAS via Open-Meteo Daily river discharge with the member range for the next 30 days at the plan's cell, and on click anywhere in the box. Weather data by Open-Meteo.com (CC BY 4.0); river discharge: contains modified Copernicus Emergency Management Service information 2026 (GloFAS); never a flood warning. Live: this page requests flood-api.open-meteo.com when the layer is opened; the data date is printed with it. Estimate: Model output (forecast or reanalysis), shown with the member range where the API gives one; never a warning. The flow-duration percentile instrument adds one request to the same endpoint with start_date=1984-01-01 and end_date=today for the chosen cell (not separately probed).
- Vegetation index, MODIS Terra NDVI 8-day Vegetation greenness over the plain and hills; scrubbing the season steps the time dimension through the 8-day periods of the current and previous year. MODIS Terra NDVI 8-day, NASA LP DAAC / LANCE, via NASA GIBS, with the product date. Live: this page requests gibs.earthdata.nasa.gov when the layer is opened; the data date is printed with it. We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Estimate: An indicator of vegetation condition, never yield, production or a biodiversity measure.
- Soil moisture, SMAP L3 (daily) Surface soil moisture from the SMAP radiometer as a drought indicator for the plain. SMAP L3 passive enhanced soil moisture (day), NASA, via NASA GIBS, with the product date. Live: this page requests gibs.earthdata.nasa.gov when the layer is opened; the data date is printed with it. We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Estimate: A satellite retrieval of the top few centimetres, not root-zone or field measurement.
- Precipitation rate, GPM IMERG (30 minutes) Satellite precipitation estimate for the half hour shown. GPM IMERG precipitation (30 min), NASA GES DISC, via NASA GIBS, with the product time. Live: this page requests gibs.earthdata.nasa.gov when the layer is opened; the data date is printed with it. We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Estimate: Satellite estimate, near real time; not a gauge reading or a forecast.
- Surface water extent, OPERA DSWx (HLS) Open and partial surface water classes on the date shown, as the flood and low-water indicator of the reach. OPERA Dynamic Surface Water Extent from HLS, NASA JPL OPERA (Copernicus Sentinel-2 and Landsat input: contains modified Copernicus Sentinel data), via NASA GIBS, with the product date. Live: this page requests gibs.earthdata.nasa.gov when the layer is opened; the data date is printed with it. We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Estimate: A classification from optical imagery; clouds leave gaps; never a flood warning or a risk rating.
- True colour at 30 m, HLS Sentinel-2 (daily granules) The newest Harmonized Landsat and Sentinel-2 granules over the plain in true colour at 30 metres: fields, rice paddies, the river bed and the towns. NASA HLS S30 Nadir BRDF-Adjusted Reflectance, NASA LP DAAC (contains modified Copernicus Sentinel data 2026), via NASA GIBS, with the product date. Live: this page requests gibs.earthdata.nasa.gov when the layer is opened; the data date is printed with it. We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Estimate: Surface reflectance shown as published; clouds and gaps between granules stay visible; never a classification.
Why this place: One box of about seventy by fifty kilometres holds a main-stem reach of the Po with the Sesia and Dora Baltea confluences, the Monferrato hills on its right bank and the irrigated rice plain of Vercelli on its left, fed by the Canale Cavour, so catchment hydrology, water allocation to food, floods (1994, 2000, 2016) and the 2022 drought can all be read at one scale. Data quality: Copernicus DEM GLO-30 covers the relief in one 1-degree tile, OpenStreetMap maps the rivers and named canals, the disciplines of GloFAS grid reaches the reach through Open-Meteo, MODIS and Sentinel-2 revisit the plain every few days and the box sits in Sentinel-2 tile 32TMQ. It connects to the Water security and hydrology, Food systems and agriculture and Climate science, variability and change of the atlas and to the water and food nexus field maps of the ecosystem sites, which draw on the same sources.
Flat plan of the same data: relief as contours from the inline grid, rivers and canals, and the numbers below. The 3D twin opens on devices that can draw it, once its data and code have been checked.
The boundaries, names and designations shown do not imply any judgement on the legal status of any territory, or any endorsement or acceptance of such boundaries. Countries: Natural Earth (public domain).
Earth observation in Italy
True-colour imagery, land cover, vegetation, snow and sea ice, over Italy.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 1
Earth observation
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Earth observation, framed on Italy.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONETSources and licences
- We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- GHRSST Level 4 MUR analyses, NASA Jet Propulsion Laboratory; distributed by the NASA Physical Oceanography DAAC (PO.DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Live: NASA EONET Events are indicative, not authority warnings.
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
- Past year, daily temperature and sunshine (NASA POWER): These data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program..
- Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
- Optional layers (10 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
Layers and dates
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE · 13 Oct 2026
- Snow cover: VIIRS NOAA-20 NDSI, NASA LANCE · 13 Oct 2026
- Sea ice concentration: GHRSST MUR, NASA JPL PO.DAAC · 12 Oct 2026
The subject, methods and measures and debates and bodies
The field and its scope
For data scientists, GIS analysts, remote-sensing practitioners and risk modellers who need to choose an Earth observation product, read its resolution and error, and know when a reanalysis or a satellite field can be trusted.
Quantities and units
Methods and their limits
Each method is listed with what it assumes and where it fails.
What the field debates
Bodies that set practice, and the data they publish
Bodies and standards are named so learners can find and apply their published work; the Academy teaches their use and links to the publisher, and no affiliation is implied.
From a pixel to an area with error bars: how revisit, cloud and accuracy decide what a change map can claim
Revisit interval and cloud cover set how many clear looks a sensor gets in a season; the classifier's user's and producer's accuracy set how far the mapped area of change is from the true area; a reference sample of stated size gives the adjusted area and its confidence interval, and only that interval supports a decision.
Sources: Olofsson et al., Good practices for estimating area and assessing accuracy of land change (2014); Drusch et al., Sentinel-2: ESA's optical high-resolution mission for GMES operational services (2012); Stehman, Estimating area and map accuracy for stratified random sampling when the strata are different from the map classes (2014); Gorelick et al., Google Earth Engine: planetary-scale geospatial analysis for everyone (2017); Dwyer et al., Analysis ready data: enabling analysis of the Landsat archive (2018).
At a glance, hub and courses
Earth observation and Earth system data at a glance
risksacademy.comearth-environmentdiscipline
- Open, 0
- In preparation, 0
- Subtopics, 9
Research and tools
Research and preprints as they are published, by discipline, with the faculty's other tools.
The hub lists the newest research and preprints for Earth observation and Earth system data, each with its source and date. Open the research hub
Courses in this discipline
Courses for this discipline are in development; until they open, study it through the connected courses and open lessons below.
The course catalogue lists every open course of the Academy.
How Earth observation and Earth system data is taught, as a process you can run
Press Play to run this process from this page's own data.
Practice, learning and connections
How technology helps and what risk it brings
Achievements in this discipline
Course achievements
One for each course with this as its primary discipline, earned when you pass the course's assessed activities.
Department: Climate and Ocean Sciences
Earn two discipline achievements in the Department of Climate and Ocean Sciences. In development.
An achievement is a record of the learning completed and assessed here. How recognition works.
Where the subject is practised
A field platform page on this subject is in development.
The two Foundry systems where it is practised
- FoundryNXS-EOP systemEarth observation is acquired, processed and comparedAcquisition room, Change room
- NXS-OPS systemObservations rest on calibrated instrumentsMetrology room
Foundry system pages describe what each system and its rooms are designed to do; the courses teach the methods these systems apply.
Across the ecosystem
Take part in Earth and Environmental Sciences
Start from who you are.
Core references and where to begin
Start with Bojinski, then Hersbach, then Olofsson.
Questions, answers and key terms
Is study here free?
What does completing a course give me?
Where do the data and the places come from?
How do I take part beyond the courses in earth observation and Earth system data?
Key terms
Essential Climate Variable
A physical, chemical or biological variable that GCOS defines as critical to characterising the Earth's climate.
Reanalysis
A consistent reconstruction of past weather and climate that combines observations with a fixed model and data assimilation.
Data assimilation
The combination of observations with a model to give the best estimate of the state of a system.
Digital twin of the Earth
A system that combines observations and high-resolution models to simulate and explore the Earth system interactively.
Contribute evidence from this page.
Reports is the Consortium's quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
Around Earth observation and Earth system data
Prepare with a related course
Open courses in connected disciplines teach the methods this discipline will build on.
