Satellite Imagery

Images taken from an artificial satellite

The inaugural images captured from the fringes of space were obtained during a sub-orbital V-2 rocket flight, a venture initiated by the US on the 24th of October, 1946. These early glimpses were rudimentary, yet they marked the genesis of our ability to perceive our planet from a vantage point entirely removed from its surface.

Satellite image of Fortaleza

Satellite imagery, a term encompassing Earth observation imagery, spaceborne photography, or simply satellite photos, refers to the visual data collected by specialized imaging satellites. These sophisticated instruments, operated by governmental agencies and private enterprises across the globe, provide a continuous stream of information about our planet's surface. The companies that pioneer this technology often license these invaluable images to entities such as Apple Maps and Google Maps, integrating them into the digital maps that guide so much of our daily lives.

History

For those with an insatiable curiosity about the very first visual records of our home from the cosmos, the journey begins with a deeper dive into the First images of Earth from space.

The initial, rather crude, image transmitted by the satellite Explorer 6 offered a glimpse of a sunlit expanse of the central Pacific Ocean, complete with its swirling cloud cover. This photograph, taken on August 14, 1959, when the satellite was approximately 17,000 miles (27,000 kilometers) above the Earth's surface, captured a moment as the satellite traversed the skies over Mexico.

However, the true genesis of space-based imaging lies not with orbital missions, but with sub-orbital flights. The aforementioned V-2 rocket, launched by the US on October 24, 1946, was programmed to capture images at a rapid pace, one every 1.5 seconds. Reaching an apogee of 65 miles (105 kilometers), these photographs dwarfed previous records, surpassing the 13.7 miles (22 kilometers) achieved by the Explorer II balloon mission in 1935 by a factor of five.[1] The distinction of capturing the first satellite (orbital) photographs of Earth belongs to the U.S. Explorer 6 on August 14, 1959.[2][3] The celestial body that next became the subject of satellite photography was our own Moon. It is believed that the Soviet satellite Luna 3, on its ambitious mission to photograph the lunar far side, may have captured the first satellite images of the Moon on October 6, 1959. Fast forward to 1972, and the iconic The Blue Marble photograph was taken from space, an image that has since achieved profound popularity, resonating deeply within media and public consciousness. Also in 1972, the United States embarked on the ambitious Landsat program, a sustained effort to acquire imagery of Earth from orbit, becoming the most extensive program of its kind. The dawn of real-time satellite imagery arrived in 1977 with the United States' KH-11 satellite system. As of September 27, 2021, the latest iteration, Landsat 9, continues this legacy.[4]

The first television image of Earth from space transmitted by the TIROS-1 weather satellite in 1960

All satellite imagery produced by NASA is made publicly accessible through the NASA Earth Observatory. Beyond NASA's contributions, numerous other nations maintain their own satellite imaging programs. A notable collaborative European endeavor includes the launch of the ERS and Envisat satellites, equipped with a diverse array of sensors. The landscape of satellite imagery has also been significantly shaped by the emergence of private companies offering commercial satellite imagery services. In the early 21st century, the widespread availability of affordable and user-friendly software, coupled with access to extensive satellite imagery databases, democratized the use of this technology for businesses and individuals alike.

Satellite image applications

The utility of satellite images extends across a vast spectrum of applications, permeating numerous fields of endeavor.

Weather: These images serve as indispensable tools for meteorologists, providing critical data for forecasting weather patterns, tracking the trajectory of storms, and gaining a deeper understanding of the complex dynamics of climate change.
Oceanography: By meticulously measuring sea surface temperatures and diligently monitoring marine ecosystems, satellite images unlock profound insights into the health of our oceans and their intricate role in the global climate system.
Agriculture and fishing: Satellite data plays a pivotal role in identifying productive fish populations, assessing the health and vitality of crops, and optimizing the allocation of resources essential for a flourishing agricultural and fishing industry.
Biodiversity: Conservation initiatives increasingly rely on satellite technology to meticulously map critical habitats, monitor the subtle shifts within ecosystems, and identify and protect endangered species from the brink of extinction.
Forestry: Satellite data empowers the practice of sustainable forestry by providing vital information for tracking deforestation, assessing the risks posed by wildfires, and implementing effective resource management strategies.
Landscape: The analysis of land use patterns, facilitated by satellite images, is instrumental in guiding urban planning and fostering initiatives aimed at sustainable development.

Among the less conventional applications is anomaly hunting, a methodology that, while criticized, involves the meticulous search of satellite images for unexplained phenomena.[5]

The electromagnetic spectrum captured by satellite images is remarkably diverse, encompassing visible light, near-infrared, infrared, and radar, among other ranges. This broad spectrum of light frequencies furnishes researchers with an immense volume of valuable and intricate information. Beyond the aforementioned applications, this data serves as a potent educational resource, propelling scientific research forward and fostering a more profound comprehension of our environment. Ultimately, satellite imagery offers a rich tapestry of data, capable of driving global development.

Data characteristics

This section duplicates the scope of other articles, specifically Remote sensing#Data characteristics. Please discuss this issue and help introduce a summary style to the section by replacing the section with a link and a summary or by splitting the content into a new article. (February 2019)

When scrutinizing satellite imagery within the realm of remote sensing, five fundamental types of resolution come into play: spatial, spectral, temporal, radiometric, and geometric. As defined by Campbell (2002),[6] these are:

Spatial resolution: This refers to the size of a pixel within an image, representing the physical area on the ground (measured in square meters) that the pixel corresponds to. It is directly determined by the sensor's instantaneous field of view (IFOV).
Spectral resolution: This characteristic is defined by the size of the wavelength intervals, representing discrete segments of the electromagnetic spectrum, and the number of such intervals the sensor is capable of measuring.
Temporal resolution: This denotes the time elapsed between successive image collection periods for a specific location on the Earth's surface, often expressed in days.
Radiometric resolution: This describes the imaging system's capacity to record subtle variations in brightness, often referred to as contrast. It is intrinsically linked to the sensor's effective bit-depth, which dictates the number of grayscale levels it can distinguish. This is typically quantified in terms of bit depth, such as 8-bit (0–255), 11-bit (0–2047), 12-bit (0–4095), or 16-bit (0–65,535).
Geometric resolution: This pertains to the satellite sensor's capability to accurately render a portion of the Earth's surface within a single pixel. It is commonly expressed as ground sample distance (GSD). GSD incorporates the cumulative effects of optical and systemic noise, providing a measure of how effectively a sensor can resolve an object on the ground within a single pixel. For instance, Landsat satellites typically have a GSD of approximately 30 meters, meaning the smallest discernible unit mapped to a single pixel is roughly 30m x 30m. In contrast, the advanced GeoEye 1 satellite achieves a GSD of 0.41 meters, a significant leap from the 0.3-meter resolution capabilities of early military film-based reconnaissance satellites like Corona.[citation needed]

The resolution attainable by satellite images is a variable factor, contingent upon the specific instrument employed and the orbital altitude of the satellite. For example, the Landsat archive provides recurring imagery of the entire planet at a 30-meter resolution, though much of this data requires further processing from its raw state. Landsat 7, for instance, has an average revisit period of 16 days. For more localized areas, images with resolutions as fine as 41 centimeters can be procured.[7]

Satellite imagery is often complemented by aerial photography, which can offer higher resolutions but at a greater cost per unit area. When integrated into a Geographic Information System (GIS), satellite imagery must be spatially rectified to ensure precise alignment with other datasets, whether they be vector or raster data.

Imaging satellites

Further information: Earth observing satellites

Public domain

The utility of satellite imaging for observing Earth's surface is so profound that many nations maintain dedicated satellite imaging programs. The United States has been a trailblazer in making this data freely accessible for scientific research. Among the most prominent programs are those listed below, recently joined by the European Union's Sentinel constellation.

CORONA

The CORONA program represented a series of American strategic reconnaissance satellites developed and operated by the Central Intelligence Agency (CIA), with significant support from the U.S. Air Force. The imagery produced was wet film based and panoramic in nature, utilizing two cameras (AFT & FWD) to capture stereographic views.

Landsat

Landsat proudly holds the distinction of being the longest-running continuous Earth-observing satellite imaging program. Since the early 1980s, it has consistently collected optical Landsat imagery at a 30-meter resolution. Starting with Landsat 5, the program also began acquiring thermal infrared imagery, albeit at a coarser spatial resolution than its optical counterparts. Currently, the Landsat 7, Landsat 8, and Landsat 9 satellites are operational in orbit.

MODIS

Since the year 2000, the MODIS instrument has been diligently collecting near-daily satellite imagery of Earth across an impressive 36 spectral bands. MODIS is carried aboard NASA's Terra and Aqua satellites, providing a continuous stream of global data.

Sentinel

The European Space Agency (ESA) is actively developing the Sentinel constellation, a series of satellites designed for various Earth observation missions. Seven missions are currently planned, each tailored to a specific application. Among these, Sentinel-1 (focused on SAR imaging), Sentinel-2 (providing decameter optical imaging for land surfaces), and Sentinel-3 (offering hectometer optical and thermal imaging for land and water) have already been successfully launched.

ASTER

The ASTER instrument, a sophisticated imaging sensor, is a key component of NASA's Earth Observing System (EOS) flagship satellite, Terra, which was launched in December 1999. ASTER is the product of a collaborative effort involving NASA, Japan's Ministry of Economy, Trade and Industry (METI), and Japan Space Systems (J-spacesystems). The data generated by ASTER is instrumental in the creation of detailed maps depicting land surface temperature, reflectance, and elevation. The interconnected system of EOS satellites, including Terra, forms a critical pillar of NASA's Science Mission Directorate and its Earth Science Division. The overarching objective of NASA's Earth Science endeavors is to cultivate a comprehensive scientific understanding of Earth as an integrated system, to analyze its responses to change, and to enhance our ability to predict variations and trends in climate, weather, and natural hazards.[8]

Land surface climatology: This involves the investigation of land surface parameters, such as surface temperature, to elucidate land-surface interactions and the exchange of energy and moisture.
Vegetation and ecosystem dynamics: Research in this area focuses on the distribution of vegetation and soil, and their temporal changes, to estimate biological productivity, understand interactions between land and atmosphere, and detect shifts in ecosystems.
Volcano monitoring: This application includes monitoring volcanic eruptions and their precursor events, including gas emissions, eruption plumes, the formation of lava lakes, and the analysis of eruptive history and potential.
Hazard monitoring: This involves observing the extent and impact of natural disasters such as wildfires, floods, coastal erosion, earthquake damage, and tsunami devastation.
Hydrology: This field aims to comprehend global energy and hydrologic processes and their relationship to global change, including the crucial aspect of evapotranspiration from plants.
Geology and soils: Detailed mapping of the composition and geomorphology of surface soils and bedrock contributes to the study of land surface processes and Earth's historical evolution.
Land surface and land cover change: Monitoring phenomena such as desertification, deforestation, and urbanization is vital. This data provides conservation managers with essential information for overseeing protected areas, national parks, and wilderness regions.

Meteosat

Model of a first generation Meteosat geostationary satellite

The Meteosat-2 geostationary weather satellite commenced its operational service, delivering imagery data on August 16, 1981. Since 1987, Eumetsat has been responsible for the operation of the Meteosat satellites.

The Meteosat visible and infrared imager (MVIRI), a three-channel imager, captures data in the visible, infrared, and water vapor spectrums. It operates on the first-generation Meteosat platform, with Meteosat-7 still actively transmitting.
The Spinning Enhanced Visible and Infrared Imager (SEVIRI), equipped with 12 channels, includes spectral bands similar to those of MVIRI, ensuring continuity in climate data spanning over three decades. This instrument is part of the Meteosat Second Generation (MSG) series.
The Flexible Combined Imager (FCI) aboard the Meteosat Third Generation (MTG) satellites will also feature similar channels, promising an unbroken record of climate data across all three generations, exceeding 60 years in duration.

Himawari

The Himawari satellite series represents a significant advancement in meteorological observation and environmental monitoring. Equipped with sophisticated imaging technology and providing frequent data updates, Himawari-8 and Himawari-9 have become indispensable assets for weather forecasting, disaster management, and climate research, extending their benefits far beyond Japan to the entire Asia-Pacific region.

Frequent Updates: These satellites are capable of delivering full-disk images of the Asia-Pacific region every 10 minutes. For specific areas, such as Japan, the imaging frequency can be even higher, with updates every 2.5 minutes, ensuring meteorologists have the most current information for precise weather forecasting.
Spectral Bands:
- Visible Light Bands (0.47 μm, 0.51 μm, 0.64 μm): These bands are utilized for daytime observations of clouds, land, and ocean surfaces. They produce high-resolution images crucial for tracking cloud movements and assessing atmospheric conditions.
- Near-Infrared Bands (0.86 μm, 1.6 μm, 2.3 μm, 6.9 μm, 7.3 μm, 8.6 μm, 9.6 μm, 11.2 μm, 13.3 μm): These bands are instrumental in differentiating between various cloud types, vegetation cover, and surface features. They are particularly effective in detecting fog, ice, and snow.
- Infrared Bands (3.9 μm, 6.2 μm, 10.4 μm, 12.4 μm): The remaining bands encompass the thermal infrared spectrum. These are vital for measuring cloud-top temperatures, sea surface temperatures, and atmospheric water vapor content, enabling continuous monitoring of weather patterns.
Advanced Imaging Technology: Himawari-8 and Himawari-9 are equipped with the Advanced Himawari Imager (AHI), a sophisticated instrument capable of capturing high-resolution images of Earth. The AHI can acquire imagery across 16 distinct spectral bands, allowing for detailed observation of weather phenomena, cloud formations, and environmental events.

Private domain

A growing number of satellites are developed and maintained by private companies, catering to a diverse range of commercial and specialized needs.

GeoEye

The GeoEye-1 satellite, operated by GeoEye, was launched on September 6, 2008.[9] This satellite boasts a high-resolution imaging system, enabling it to capture images with a ground resolution of 0.41 meters (16 inches) in panchromatic, or black and white, mode. For multispectral, or color, imagery, it achieves a resolution of 1.65 meters, approximately 64 inches.

WorldView-2 image of Weston-super-Mare

Maxar

Maxar's WorldView-2 satellite delivers high-resolution commercial satellite imagery, offering a spatial resolution of 0.46 meters (panchromatic only).[10] This 0.46-meter resolution permits WorldView-2's panchromatic images to distinguish between objects on the ground separated by at least 46 centimeters. Maxar's QuickBird satellite similarly provides panchromatic images with a resolution of 0.6 meters when viewed at nadir.

Maxar's WorldView-3 satellite further enhances this capability, providing high-resolution commercial satellite imagery with an impressive spatial resolution of 0.31 meters. WorldView-3 is also equipped with a short-wave infrared sensor and an atmospheric sensor, expanding its analytical potential.[11]

Airbus Intelligence

Pleiades image of Central Park in New York City

The Pléiades constellation comprises two very-high-resolution optical Earth-imaging satellites, offering 50-centimeter resolution in panchromatic mode and 2.1-meter resolution in spectral bands. Pléiades-HR 1A and Pléiades-HR 1B provide comprehensive coverage of Earth's surface with a repeat cycle of 26 days. Designed as a dual civil/military system, Pléiades aims to fulfill the space imagery requirements of European defense forces, as well as civilian and commercial needs. The Pléiades Neo [fr][12] represents an advanced optical constellation, featuring four identical satellites with a 30-cm resolution and rapid reactivity capabilities.

Spot Image

SPOT image of Bratislava Satellite view of Southern Luzon taken by the ISS

The three SPOT satellites currently in orbit—Spot 5, 6, and 7—deliver very high-resolution imagery. They offer a resolution of 1.5 meters for the Panchromatic channel and 6 meters for the Multi-spectral bands (Red, Green, Blue, Near-Infrared). Spot Image also distributes multiresolution data from other optical satellites, notably from Formosat-2 (Taiwan) and Kompsat-2 (South Korea), as well as data from radar satellites such as TerraSar-X, ERS, Envisat, and Radarsat. Spot Image holds exclusive distribution rights for data from the high-resolution Pleiades satellites, which provide a resolution of 0.50 meters, or approximately 20 inches. The launches for these satellites occurred in 2011 and 2012, respectively. The company further provides infrastructure for data reception and processing, alongside value-added services.

Planet Labs

Planet Labs operates three distinct satellite imagery constellations: RapidEye, Dove, and SkySat.

In 2015, Planet acquired BlackBridge, along with its constellation of five RapidEye satellites, which were launched in August 2008.[13] The RapidEye constellation features identical, equally calibrated multispectral sensors. This uniformity ensures that imagery from any one satellite is equivalent to that from the others, enabling the collection of a vast amount of data (4 million square kilometers per day) and daily revisits to specific areas. Orbiting at an altitude of 630 kilometers on the same orbital plane, these satellites deliver images with a 5-meter pixel size. RapidEye satellite imagery is particularly well-suited for applications in agriculture, environmental monitoring, cartography, and disaster management. Planet Labs not only offers its imagery but also provides consultation services to clients, assisting them in developing solutions based on the analysis of this data. The RapidEye constellation was retired by Planet in April 2020.

Planet's Dove satellites are CubeSats, compact satellites weighing approximately 4 kilograms (8.8 pounds) and measuring 10 by 10 by 30 centimeters (3.9 by 3.9 by 11.8 inches) in length, width, and height.[14] They orbit at an altitude of about 400 kilometers (250 miles) and provide imagery with a resolution of 3–5 meters (9.8–16.4 feet), finding application in environmental, humanitarian, and business contexts.[15][16]

SkySat image of São Paulo, the largest city in Brazil

SkySat represents a constellation of sub-meter resolution Earth observation satellites that deliver imagery, high-definition video, and analytics services.[17] Planet acquired these satellites through its purchase of Terra Bella (formerly Skybox Imaging), a company founded in 2009 by Dan Berkenstock, Julian Mann, John Fenwick, and Ching-Yu Hu, based in Mountain View, California.[18] Google had previously acquired Terra Bella in 2017.[19]

The SkySat satellites are engineered using cost-effective automotive-grade electronics and readily available high-performance processors,[20] albeit scaled up to approximately the size of a minifridge.[21] These satellites measure approximately 80 centimeters (31 inches) in length, a notable increase compared to the roughly 30 centimeters (12 inches) of a 3U CubeSat, and weigh around 100 kilograms (220 pounds).[21]

ImageSat International

Earth Resource Observation Satellites, commonly known as "EROS" satellites, are lightweight, low Earth orbit satellites designed for high-resolution imaging and rapid maneuvering between targets. Within the commercial high-resolution satellite market, EROS satellites are among the smallest very high-resolution platforms, distinguished by their agility and consequently, their superior performance. These satellites are deployed in a circular, Sun-synchronous, near-polar orbit at an altitude of 510 kilometers (± 40 kilometers).

The applications of EROS satellite imagery primarily serve intelligence, homeland security, and national development objectives. However, they are also employed across a broad spectrum of civilian uses, including mapping, border control, infrastructure planning, agricultural monitoring, environmental monitoring, disaster response, and the creation of training and simulation materials.

EROS A: A high-resolution satellite with a panchromatic resolution of 1.9–1.2 meters, launched on December 5, 2000.
EROS B: Representing the second generation of Very High Resolution satellites, it offers a 70-centimeter panchromatic resolution and was launched on April 25, 2006.
EROS C2: The third generation of Very High Resolution satellites, boasting a 30-centimeter panchromatic resolution, was launched in 2021.
EROS C3: Also part of the third generation, this satellite offers a 30-centimeter panchromatic and multispectral resolution, launched in 2023.

China Siwei

The GaoJing-1 / SuperView-1 constellation, comprising satellites 01, 02, 03, and 04, is a commercial network of Chinese remote sensing satellites managed by China Siwei Surveying and Mapping Technology Co. Ltd. Operating from an altitude of 530 kilometers, these four satellites are phased 90 degrees apart on the same orbit. They provide a panchromatic resolution of 0.5 meters and a multispectral resolution of 2 meters, covering a swath width of 12 kilometers.[22][23]

Disadvantages

Composite image of Earth at night, as only half of Earth is at night at any given moment

The sheer vastness of Earth's landmass, coupled with the increasingly high resolution of satellite imagery, results in database sizes that are immense. Consequently, the process of image processing—transforming raw data into usable visuals—is inherently time-consuming.[citation needed] Preprocessing steps, such as image destriping, are frequently necessary. Furthermore, depending on the specific sensor utilized, atmospheric conditions like cloud cover can significantly impact image quality. This poses a particular challenge for acquiring clear imagery of regions prone to persistent cloud cover, such as mountainous areas. For these reasons, publicly accessible satellite image datasets often undergo processing by third-party entities for visual or scientific commercial applications.

Commercial satellite companies maintain strict control over their imagery, declining to place it into the public domain or sell it outright. Instead, users must acquire a license to utilize their imagery, which inherently limits the legal ability to create derivative works from this commercial satellite data.

Concerns regarding privacy have been raised by individuals who object to their properties being visible from above. Google Maps addresses these concerns in its FAQ by stating: "We understand your privacy concerns... The images that Google Maps displays are no different from what can be seen by anyone who flies over or drives by a specific geographic location."[24]

Using

Satellite images find application across a multitude of disciplines, including agriculture, geological and hydrological research, forestry, environmental protection, territorial planning, and for educational, intelligence, and military purposes. These images can be captured across the visible spectrum, as well as in the ultraviolet, infrared, and other segments of the electromagnetic range. Additionally, various terrain maps are generated through radar surveys.

Currently, the decryption and analysis of satellite images are increasingly performed using automated software systems such as ERDAS Imagine or ENVI. In the nascent stages of this industry, certain types of image enhancements commissioned by the U.S. government were executed by contractor firms. For instance, ESL Incorporated developed one of the earliest two-dimensional Fourier transforms specifically for digital image processing.

The analysis of satellite imagery is actively employed in environmental protection efforts. For example, the method of "Visual satellite search for illegal landfills" has successfully identified over 200 unauthorized municipal solid and household waste disposal sites within the territory of five regions in the Russian Federation.[25][26] In France, satellite imagery has been instrumental in detecting private swimming pools, thereby mitigating tax evasion related to these structures.[27]

The acquisition of private imagery is also a common practice within the open-source intelligence (or OSINT) community. This practice, for instance, enables the estimation of the remaining Soviet military hardware in storage that could potentially be refitted in the context of the ongoing War in Ukraine.[28]