Earth observation guideApplications
Applications
What people do with Earth observation data, sector by sector, and which kinds of data each kind of work relies on.
The basics
The earlier pages of this guide describe the data. These pages describe what people do with it. A farmer checks which part of a field is struggling, an insurer sees which streets flooded, a bank checks that a farm it lent to is really planted, and a coastguard finds a ship that has switched off its radio. Each sector below has its own page. Every page starts with a short plain introduction, like this one, and then goes into depth on the specific tasks, the data they need, how often, what can go wrong and who does the work. Several pages include a small demonstration on real satellite images that you can try.
Why it matters
Most buyers come to Earth observation with a question about their own work rather than about sensors. Starting from the work, and then finding the data it needs, is the quickest way to the right product.
Agriculture
Crop types, crop condition, yield forecasts, water use and crop insurance.
Forestry
Forest loss and alerts, biomass and carbon, inventory and fire.
Floods and disasters
Flood extent and depth, floods in towns and earthquake damage.
Insurance
Exposure, loss assessment, wildfire, parametric cover and subsidence.
Financial services
Economic activity, poverty mapping, deforestation rules and asset monitoring.
Energy
Solar parks, offshore wind, methane leaks, power lines and pipelines.
Mining and commodities
Mine footprints, tailings dam stability, mineral mapping and supply.
Urban areas and infrastructure
Settlement mapping, ground and building movement, bridges and heat.
Climate and environment
Climate variables, surface water, ice, coastlines and the atmosphere.
Maritime
Ship detection, vessels that do not broadcast, oil spills and night fishing.
Defence and security
Image detail, change detection, coherence, maritime awareness and terrain.
In depth
The sectors are those in which Data Sphere's buyers most often work. Insurance and financial services have separate pages because they use the data differently. Insurers map hazards and losses at the sites they cover, while lenders and investors measure economic activity, assets and supply chains. Energy and urban infrastructure are also separate. Energy work centres on generating assets and emissions, and urban work on buildings and the ground beneath them, although both use radar interferometry to watch for ground movement.
Which data serve which work
Figure 1 summarises the data types that the sector pages discuss. A filled circle marks a data type that is central to at least one of the tasks on that sector's page, and an open circle a data type used in a supporting role, for example to confirm a finding or to fill a gap. It is a summary of the cases discussed on those pages, with the sources cited there, and not a measurement or a complete list. The column headings link to the pages that explain each data type.
| Sector | Optical | Multispectral | Hyperspectral | Thermal | Radar | Interferometry | Night lights | Elevation |
|---|---|---|---|---|---|---|---|---|
| Agriculture | Supporting | Central | Not discussed | Central | Supporting | Not discussed | Not discussed | Supporting |
| Forestry | Supporting | Central | Supporting | Supporting | Central | Not discussed | Not discussed | Central |
| Floods and disasters | Supporting | Supporting | Not discussed | Not discussed | Central | Central | Not discussed | Central |
| Insurance | Central | Central | Not discussed | Not discussed | Central | Central | Not discussed | Supporting |
| Financial services | Central | Central | Not discussed | Not discussed | Supporting | Not discussed | Central | Not discussed |
| Energy | Supporting | Central | Supporting | Not discussed | Central | Central | Not discussed | Supporting |
| Mining and commodities | Supporting | Central | Central | Supporting | Supporting | Central | Not discussed | Supporting |
| Urban areas and infrastructure | Supporting | Supporting | Not discussed | Central | Central | Central | Not discussed | Supporting |
| Climate and environment | Supporting | Central | Supporting | Not discussed | Central | Central | Not discussed | Not discussed |
| Maritime | Supporting | Not discussed | Not discussed | Not discussed | Central | Not discussed | Central | Not discussed |
| Defence and security | Central | Supporting | Not discussed | Not discussed | Central | Central | Not discussed | Central |
Choosing data for a task
Three questions narrow the choice in every sector. The first is how small the thing to be seen is, which sets the spatial resolution. The second is how often it changes, which sets the revisit. The third is whether cloud or darkness will get in the way, which decides between optical and radar. Open missions cover a great deal. Sentinel-2 records 13 bands, four of them at 10 m, and its two satellites were designed to revisit a place every five days at the equator [1]. Sentinel-1 provides radar images by day and night in all weather at typically 10 m [2]. Finer detail, more frequent visits and data types that open missions do not provide, such as very high resolution optical imagery, come from commercial providers. The resolutions page explains the trade-offs between them.
References
- Drusch, M., Del Bello, U., Carlier, S. et al. (2012) Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services. Remote Sensing of Environment, 120, 25-36. https://doi.org/10.1016/j.rse.2011.11.026
- Torres, R., Snoeij, P., Geudtner, D. et al. (2012) GMES Sentinel-1 mission. Remote Sensing of Environment, 120, 9-24. https://doi.org/10.1016/j.rse.2011.05.028