Satellite imagery

Satellite images (also Earth observation imagery, spaceborne photography, or simply satellite photo) are images of Earth collected by imaging satellites operated by governments and businesses around the world. Satellite imaging companies sell images by licensing them to governments and businesses such as Apple Maps and Google Maps.

: They guide meteorologists in forecasting patterns, tracking storms, and understanding climate change.

Weather

: By measuring sea temperatures and monitoring ecosystems, satellite images unlock insights into our oceans' health and global climate.

Oceanography

and Fishing: Satellite data helps locate fish populations, assess crop health, and optimize resource use for a thriving agricultural and fishing industry.

Agriculture

: Conservation efforts leverage satellite technology to map habitats, monitor ecosystem changes, and protect endangered species.

Biodiversity

: Satellite data empowers sustainable forestry by tracking deforestation, assessing fire risks, and managing resources effectively.

forestry

: Analyzing land use patterns with satellite images supports urban planning and facilitates sustainable development initiatives.

landscape

Satellite images have many applications in various fields.

Less mainstream uses include anomaly hunting, a criticized investigation technique involving the search of satellite images for unexplained phenomena.^[5]

The spectrum of satellite images is diverse, such as visible light, near-infrared light, infrared light spectrum and radar, etc. These spectra can provide scientists with a lot of rich information. In addition to the satellite applications mentioned above, these data can serve as powerful educational tools, advance scientific research and promote a deeper understanding of our environment. This shows that satellite imagery provides rich information and can promote global development.

spatial resolution is defined as the pixel size of an image representing the size of the surface area (i.e. m²) being measured on the ground, determined by the sensors' instantaneous field of view (IFOV);

spectral resolution is defined by the wavelength interval size (discrete segment of the Electromagnetic Spectrum) and number of intervals that the sensor is measuring;

temporal resolution is defined by the amount of time (e.g. days) that passes between imagery collection periods for a given surface location

Radiometric resolution is defined as the ability of an imaging system to record many levels of brightness (contrast for example) and to the effective bit-depth of the sensor (number of grayscale levels) and is typically expressed as 8-bit (0–255), 11-bit (0–2047), 12-bit (0–4095) or 16-bit (0–65,535).

Geometric resolution refers to the satellite sensor's ability to effectively image a portion of the Earth's surface in a single pixel and is typically expressed in terms of , or GSD. GSD is a term containing the overall optical and systemic noise sources and is useful for comparing how well one sensor can "see" an object on the ground within a single pixel. For example, the GSD of Landsat is ≈30m, which means the smallest unit that maps to a single pixel within an image is ≈30m x 30m. The latest commercial satellite (GeoEye 1) has a GSD of 0.41 m. This compares to a 0.3 m resolution obtained by some early military film based Reconnaissance satellite such as Corona.

Ground sample distance

There are five types of resolution when discussing satellite imagery in remote sensing: spatial, spectral, temporal, radiometric and geometric. Campbell (2002)^[6] defines these as follows:

The resolution of satellite images varies depending on the instrument used and the altitude of the satellite's orbit. For example, the Landsat archive offers repeated imagery at 30 meter resolution for the planet, but most of it has not been processed from the raw data. Landsat 7 has an average return period of 16 days. For many smaller areas, images with resolution as fine as 41 cm can be available.^[7]

Satellite imagery is sometimes supplemented with aerial photography, which has higher resolution, but is more expensive per square meter. Satellite imagery can be combined with vector or raster data in a GIS provided that the imagery has been spatially rectified so that it will properly align with other data sets.

Land surface climatology—investigation of land surface parameters, , etc., to understand land-surface interaction and energy and moisture fluxes

surface temperature

Vegetation and ecosystem dynamics—investigations of vegetation and soil distribution and their changes to estimate biological productivity, understand land-atmosphere interactions, and detect ecosystem change

Volcano monitoring—monitoring of eruptions and precursor events, such as gas emissions, eruption plumes, development of lava lakes, eruptive history and eruptive potential

Hazard monitoring—observation of the extent and effects of wildfires, flooding, , earthquake damage, and tsunami damage

coastal erosion

Hydrology—understanding global energy and hydrologic processes and their relationship to global change; included is evapotranspiration from plants

Geology and soils—the detailed composition and geomorphologic mapping of surface soils and bedrocks to study land surface processes and Earth's history

Land surface and land cover change—monitoring , deforestation, and urbanization; providing data for conservation managers to monitor protected areas, national parks, and wilderness areas

desertification

Aerial photography

Earth observation satellite

Moderate-resolution imaging spectroradiometer

Reconnaissance satellite

Remote sensing

Shuttle Radar Topography Mission

Stratellite

Timeline of first images of Earth from space

Virtual globe

NASA World Wind

Weather satellite

– the most detailed image of the entire Earth to date, made by the European Space Agency's Envisat Meris.

ESA Envisat Meris – 300m

– a detailed true-color image of the entire Earth.

Blue Marble: Next Generation

– an open source 3D Earth-viewing software developed by NASA that accesses NASA JPL database