Satellites can collect data from particular places, and at particular wavelengths. The areas the satellite can see depend on the orbit, and the field-of-view of the instrument. Geostationary satellites can collect data from the same parts of the world on a continuing basis - for example Meteosat collects a new picture of the world every 15 minutes from above the equator.

However, these geostationary satellites do not see the globe in fine detail, and don’t see Polar Regions at all due to the Earth’s curvature. Polar or nearly-polar orbiting satellites travel around the world roughly every 90-100 minutes, depending on altitude. With the Earth rotating underneath their orbit, they are able to ‘see’ every point on the Earth’s surface at some stage during their orbital repeat cycle. Satellites with wide ‘swath’ imagers can see most parts of the planet at least once a day, often several times. Higher resolution satellites have narrower swaths, and typically only see a given point on the surface every few days, or even weeks. And of course in the optical domain, one of the biggest limitations we have in terms of seeing the surface is the presence of clouds. If a sensor only sees a point every few days or weeks at best, like the US Landsat mission (every 16 days), or the ESA Sentinel 2 mission (every 5-7 days), then clouds can push this up to weeks or even months, particularly in areas like the tropics where persistent cloud cover is a real issue for optical sensors. One solution to this is to launch multiple satellites (like the ESA Sentinel programme), or even a constellation of much lower cost, lower tech sensors such as PlanetLabs, with more than 50 sensors. The more you have, the more likely you are to be able to see through gaps in cloud cover.

The particular spectral data the satellite collects depends on its mission and capabilities. Some early satellite photographs have been used for different purposes than they were originally intended - for example, short term weather pictures being reanalysed for climate data; images of the poles being repurposed for ice studies, military reconnaissance data being used for environmental applications – such as this study of vegetation and topography in Vietnam based on military images from the mid 1960s. However, usually a satellite is built with a particular data set in mind and concentrates on collecting it. Optical data sets are often used in conjunction with other information from radar, microwave, or ground sources, particularly because optical instruments can’t penetrate cloud. But optical data have a wide range of uses.

Overview of modern uses of EO:

Optical Earth Observation is used particularly for mapping, and for observing the processes of life. In some cases, these two purposes overlap very clearly - for example in the amount of land visibly covered by trees, crops, or buildings, as well as more importantly, the status or condition of the living Earth – forest and crop stress, forest loss, crop yield, terrestrial and ocean carbon cycle. It can show the productivity of plants on land and phytoplankton in the ocean.

Mapping helps us to understand land use, and particularly land use change. This can be caused by natural processes, but is more often caused by human activity both in the short term, and in response to longer-term climate change. Land use change can have implications for local water availability, food security, and long-term effects including sustainability of agriculture and biodiversity. Optical EO can also be used for sudden changes - identifying changes in the landscape following wildfires, storms, or other natural disasters, and showing changes in human habitats such as damage to structures, or sudden creation of new structures such as refugee camps.

Optical Earth Observation is still a key part of meteorology - geostationary satellites for example can pick up and track the motion of sudden convective storms as they develop and can be particularly useful for air traffic control in areas where there are not many ground observations available.

Optical EO also has a wide range of commercial applications including providing data for energy companies, making agriculture more precise - combining imagery with satellite navigation to work out where crops are most/least productive and to help prioritise and optimise irrigation, fertilisation, enabling fisheries to be managed more effectively, crop yields to be predicted and measuring how many people visit certain places - by counting parked cars, or even areas covered by people – such as this inauguration day image from Washington DC. Satellite images of city lights at night have been widely-used as a proxy for, among other things, population density, level of economic development and fossil fuel consumption. The contrast between North and South Korea is stark.

Featured Educators:

• Dr Mathias Disney

View featured satellites on the satellite tracking app

• Sentinel-2

• Meteosat-10

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