The UCS Satellite Database is a listing of active satellites currently in orbit around the Earth. It is available as both a downloadable Excel file and in a tab-delimited text format, and in a version (tab-delimited text) in which the "Name" column contains only the official name of the satellite in the case of government and military satellites, and the most commonly used name in the case of commercial and civil satellites. The database is updated roughly quarterly. Our intent in producing the Database is to create a research tool by collecting open-source information on active satellites and presenting it in a format that can be easily manipulated for research and analysis. The Database includes basic information about the satellites and their orbits, but does not contain the detailed information necessary to locate individual satellites. The UCS Satellite Database can be accessed at www.ucsusa.org/satellite_database.

Citation: If using this dataset please cite the following in your work: @misc{VotDasNemSri2010 , author = "Petr Votava and Kamalika Das and Rama Nemani and Ashok N. Srivastava", year = "2010", title = "MODIS surface reflectance data repository", url = "https://c3.ndc.nasa.gov/dashlink/resources/331/", institution = "NASA Ames Research Center" } Petr Votava, Kamalika Das, Rama Nemani, Ashok N. Srivastava. (2010). MODIS surface reflectance data repository. NASA Ames Research Center. Data Description: The California satellite dataset using the MODerate-resolution Imaging Spectroradiometer (MODIS) product MCD43A4 provides reflectance data adjusted using a bidirectional reflectance distribution function (BRDF) to model the values as if they were taken from nadir view. Both Terra and Aqua data are used in the generation of this product, providing the highest probability for quality input data. More information at: https://lpdaac.usgs.gov/lpdaac/products/modis_products_table/nadir_brdf_adjusted_reflectance/16_day_l3_global_500m/v5/combined Data Organization: The nine data folders correspond to three years of data.Under this top level directory structure are separate files for each band (1 - 7) and each 8-day period of the particular year. Within the period the best observations were selected for each location. File Naming Conventions: Each of the files represent a 2D dataset with the naming conventions as follows: MCD43A4.CA_1KM.005.. .flt32 where is the beginning year-day of the period that where YYYY = year and DDD = day of year (001 - 366) represents the observations in particular (spectral) band (band 1 - band 7) - since the indexing is 0-based, the range of indexes on the files is from 0 - 6 (where 0 = band 1, and 6 = band 7) The spectral band frequencies for the MODIS acquisitions are as follows: BAND1 620 - 670 nm BAND2 841 - 876 nm BAND3 459 - 479 nm BAND4 545 - 565 nm BAND5 1230 - 1250 nm BAND6 1628 - 1652 nm BAND7 2105 - 2155 nm File Specifications: Each file is a single 2D dataset. DATA TYPE: 32-bit floating point (IEEE754) with little-Endian byte ordering NUMBER OF ROWS: 1203 NUMBER OF COLUMNS: 738 FILL VALUES (observations that are either not valid or not on land, such as ocean etc.): -999.0 Overview: DATASET: MODIS 8-day Surface Reflectance BRDF-adjusted from Terra and Aqua COLLECTION: 5 DATA TYPE: IEEE754 float (32-bit float) BYTE ORDER: LITTLE ENDIAN (Intel) DIMS: 1203 rows x 738 columns FILL VALUE: -999.0 SPATIAL RESOLUTION: 1km PROJECTION: Lambert Azimuthal Equal Area

GEOSatDB is a semantic representation of Earth observation satellites and sensors that can be used to easily discover available Earth observation resources for specific research objectives.BackgroundThe widespread availability of coordinated and publicly accessible Earth observation (EO) data empowers decision-makers worldwide to comprehend global challenges and develop more effective policies. Space-based satellite remote sensing, which serves as the primary tool for EO, provides essential information about the Earth and its environment by measuring various geophysical variables. This contributes significantly to our understanding of the fundamental Earth system and the impact of human activities.Over the past few decades, many countries and organizations have markedly improved their regional and global EO capabilities by deploying a variety of advanced remote sensing satellites. The rapid growth of EO satellites and advances in on-board sensors have significantly enhanced remote sensing data quality by expanding spectral bands and increasing spatio-temporal resolutions. However, users face challenges in accessing available EO resources, which are often maintained independently by various nations, organizations, or companies. As a result, a substantial portion of archived EO satellite resources remains underutilized. Enhancing the discoverability of EO satellites and sensors can effectively utilize the vast amount of EO resources that continue to accumulate at a rapid pace, thereby better supporting data for global change research.MethodologyThis study introduces GEOSatDB, a comprehensive semantic database specifically tailored for civil Earth observation satellites. The foundation of the database is an ontology model conforming to standards set by the International Organization for Standardization (ISO) and the World Wide Web Consortium (W3C). This conformity enables data integration and promotes the reuse of accumulated knowledge. Our approach advocates a novel method for integrating Earth observation satellite information from diverse sources. It notably incorporates a structured prompt strategy utilizing a large language model to derive detailed sensor information from vast volumes of unstructured text.Dataset InformationThe GEOSatDB portal(https://www.geosatdb.cn) has been developed to provide an interactive interface that facilitates the efficient retrieval of information on Earth observation satellites and sensors.The downloadable files in RDF Turtle format are located in the data directory and contain a total of 132,681 statements:- GEOSatDB_ontology.ttl: Ontology modeling of concepts, relations, and properties.- satellite.ttl: 2,453 Earth observation satellites and their associated entities.- sensor.ttl: 1,035 Earth observation sensors and their associated entities.- sensor2satellite.ttl: relations between Earth observation satellites and sensors.GEOSatDB undergoes quarterly updates, involving the addition of new satellites and sensors, revisions based on expert feedback, and the implementation of additional enhancements.

TRACE-A_Satellite_Data is the supplementary satellite data collected during the Transport and Atmospheric Chemistry near the Equator - Atlantic (TRACE-A) suborbital campaign. Data from the NOAA 10, 11, and 12 satellites and the Total Ozone Mapping Spectrometer (TOMS) satellite instrument are featured in this collection. Data collection for this product is complete.The TRACE-A mission was a part of NASA’s Global Tropospheric Experiment (GTE) – an assemblage of missions conducted from 1983-2001 with various research goals and objectives. TRACE-A was conducted in the Atlantic from September 21 to October 24, 1992. TRACE-A had the objective of determining the cause and source of the high concentrations of ozone that accumulated over the Atlantic Ocean between southern Africa and South America from August to October. NASA partnered with the Brazilian Space Agency (INPE) to accomplish this goal.  The NASA DC-8 aircraft and ozonesondes were utilized during TRACE-A to collect the necessary data. The DC-8 was equipped with 19 instruments. A few instruments on the DC-8 include the Differential Absorption Lidar (DIAL), the Laser-Induced Fluorescence, the O3-NO Ethylene/Forward Scattering Spectrometer, the Modified Licor, and the DACOM IR Laser Spectrometer. The DIAL was responsible for a variety of measurements, which include Nadir IR aerosols, Nadir UV aerosols, Zenith IR aerosols, Zenith VS aerosols, ozone, and ozone column. The Laser-Induced Fluorescence instrument collected measurements on NxOy in the atmosphere. Measurements of ozone were recorded by the O3-NO Ethylene/Forward Scattering Spectrometer while the Modified Licor recorded CO2. Finally, the DACOM IR Laser Spectrometer gathered an assortment of data points, including CO, O3, N2O, CH4, and CO2. Ozonesondes played a role in data collection for TRACE-A along with the DC-8 aircraft. The sondes were dropped from the DC-8 aircraft in order to gather data on ozone, temperature, and atmospheric pressure.

The global satellite data services market size is projected to grow from USD 14.20 billion in 2025 to USD 100.44 billion by 2033, exhibiting a CAGR of 27.7%.
Report Scope:

Satellite images archived in KuDA are derived from either the NOAA or the Dept of Defense polar orbiting weather satellites. This dataset contains images that are derived from the Department of Defense's polar orbiting weather satellites. The Department of Defense's DMSP (Defense Meteorological Satellite Program) had three satellites transmitting during 1991 (F8, F9, & F10). These satellites carry a sensor called the Operational Line Scanner (OLS) which is the one source of images for KuDA (the other source of images is NOAA's AVHRR). The OLS is a two-channel sensor with a broadband visible channel and an IR channel. Data are in TDF and .TAR format.

Dataset

This dataset was created by Datastuffplus

Contents

TRACE-P_Satellite_Data is the supplementary satellite data collected during the Transport and Chemical Evolution over the Pacific (TRACE-P) suborbital campaign. Data from the Multi-Angle Imaging SpectroRadiometer (MISR) and the Measurements of Pollution in the Troposphere (MOPITT) satellite instruments are featured in this collection. Data collection for this product is complete.The NASA TRACE-P mission was a part of NASA’s Global Tropospheric Experiment (GTE) – an assemblage of missions conducted from 1983-2001 with various research goals and objectives. TRACE-P was a multi-organizational campaign with NASA, the National Center for Atmospheric Research (NCAR), and several US universities. TRACE-P deployed its payloads in the Pacific between the months of March and April 2001 with the goal of studying the air chemistry emerging from Asia to the western Pacific. Along with this, TRACE-P had the objective studying the chemical evolution of the air as it moved away from Asia.  In order to accomplish its goals, the NASA DC-8 aircraft and NASA P-3B aircraft were deployed, each equipped with various instrumentation. TRACE-P also relied on ground sites, and satellites to collect data. The DC-8 aircraft was equipped with 19 instruments in total while the P-3B boasted 21 total instruments. Some instruments on the DC-8 include the Nephelometer, the GCMS, the Nitric Oxide Chemiluminescence, the Differential Absorption Lidar (DIAL), and the Dual Channel Collectors and Fluorometers, HPLC. The Nephelometer was utilized to gather data on various wavelengths including aerosol scattering (450, 550, 700nm), aerosol absorption (565nm), equivalent BC mass, and air density ratio. The GCMS was responsible for capturing a multitude of compounds in the atmosphere, some of which include CH4, CH3CHO, CH3Br, CH3Cl, CHBr3, and C2H6O. DIAL was used for a variety of measurements, some of which include aerosol wavelength dependence (1064/587nm), IR aerosol scattering ratio (1064nm), tropopause heights and ozone columns, visible aerosol scattering ratio, composite tropospheric ozone cross-sections, and visible aerosol depolarization. Finally, the Dual Channel Collectors and Fluorometers, HPLC collected data on H2O2, CH3OOH, and CH2O in the atmosphere. The P-3B aircraft was equipped with various instruments for TRACE-P, some of which include the MSA/CIMS, the Non-dispersive IR Spectrometer, the PILS-Ion Chromatograph, and the Condensation particle counter and Pulse Height Analysis (PHA). The MSA/CIMS measured OH, H2SO4, MSA, and HNO3. The Non-dispersive IR Spectrometer took measurements on CO2 in the atmosphere. The PILS-Ion Chromatograph recorded measurements of compounds and elements in the atmosphere, including sodium, calcium, potassium, magnesium, chloride, NH4, NO3, and SO4. Finally, the Condensation particle counter and PHA was used to gather data on total UCN, UCN 3-8nm, and UCN 3-4nm. Along with the aircrafts, ground stations measured air quality from China along with C2H2, C2H6, CO, and HCN. Finally, satellites imagery was used to collect a multitude of data, some of the uses were to observe the history of lightning flashes, SeaWiFS cloud imagery, 8-day exposure to TOMS aerosols, and SeaWiFS aerosol optical thickness. The imagery was used to best aid in planning for the aircraft deployment.

PEM-Tropics-A_Satellite_Data is the satellite data collected during the Pacific Exploratory Mission (PEM) Tropics A suborbital campaign. Data from the Advanced Very High Resolution Radiometer (AVHRR), Geostationary Operational Environmental Satellite (GOES) - 8 and 9, TIROS Operational Vertical Sounder, Special Sensor Microwave Imager/Sounder (SSMIS), and NOAA-14 satellites are featuredin this collection. Data collection for this product is complete.From 1983-2001, NASA conducted a collection of field campaigns as part of the Global Tropospheric Experiment (GTE). Among those was PEM, which intended to improve the scientific understanding of human influence on tropospheric chemistry. Part of the PEM field campaigns were focused on the tropical Pacific region (PEM-Tropics) which was recognized as a “very large chemical vessel.” The overarching science objective was to assess the anthropogenic impact on tropospheric oxidizing power. A secondary objective was to investigate the impact of atmospheric sulfur chemistry, including oxidation of marine biogenic emission of dimethyl sulfide (DMS) on aerosol loading and radiative effect, which is of critical importance in the assessment of global climate change. The PEM-Tropics mission was conducted in two phases to contrast the influence of biomass burning in the dry season and the “relatively clean” wet season. The first, PEM-Tropics A, was carried out during the end of the dry season (August-September 1996), and the second, PEM-Topics B, was conducted during the wet season (March-April 1999). To accomplish its objectives, PEM-Tropics enlisted the NASA DC-8 and P-3B aircrafts to carry out longitudinal and latitudinal surveys at various altitudes as well as vertical profile sampling across the Pacific basin. Both aircrafts were equipped with in-situ instruments measuring hydroperoxyl radicals (HOx), ozone (O3), photochemical precursors (including, reactive nitrogen species and non-methane hydrocarbon species), and intermediate products (e.g., hydrogen peroxide (H2O2), formaldehyde (CH2O), and acetic acid (CH3OOH). The P3-B in-situ instrument payload also included a direct measurement of hydroxyl (OH) for both missions, while the OH and hydroperoxyl radical (HO2) measurements were added to DC-8 aircraft for PEM-Tropics B. Taking advantage of its excellent low altitude capability, the P-3B was instrumented with a comprehensive sulfur measurement package and conducted pseudo-Lagragian sampling for evaluating DMS oxidation chemistry, including measurements of DMS, sulfur dioxide (SO2), sulfuric acid (H2SO4), and methylsulfonic acid (MSA) as well as the first airborne measurement of dimethyl sulfoxide (DMSO) during PEM-Tropics B. More importantly, it was the first time that DMS (the source), OH and O3 (primary oxidants), and products (DMSO, MSA, H2SO4, SO2) were measured simultaneously aboard an aircraft in the tropical pacific. These observations, specifically DMSO, presented a substantial challenge to the DMS oxidation kinetics to this day. The DC-8 aircraft was equipped with the Differential Absoprtion Lidar (DIAL) during PEM-Tropics A, and the differential absorption lidars DIAL and LASE during PEM-Tropics B. These lidars provided real-time information for fine tuning the flight tracks to capture sampling opportunities. The lidar data products themselves provide valuable information of vertical profiles of ozone as well as aerosol and water vapor in tropical Pacific Furthermore, both aircrafts were fitted with instruments for aerosol composition and microphysical property measurements. Detailed description related to the motivation, implementation, and instrument payloads are available in the PEM-Tropics A overview paper and the PEM-Tropics B overview paper. Most of the publications based on PEM-Tropics A and B observations are available in the Journal of Geophysical Research special issues: Pacific Exploratory Mission-Tropics A and NASA Global Tropospheric Experiment Pacific Exploratory Mission in the Tropics Phase B: Measurement and Analyses (PEM-Tropics B), while other publications such as Nowak et al. (2001) were published prior to the special issues.

NEW GOES-19 Data!! On April 4, 2025 at 1500 UTC, the GOES-19 satellite will be declared the Operational GOES-East satellite. All products and services, including NODD, for GOES-East will transition to GOES-19 data at that time. GOES-19 will operate out of the GOES-East location of 75.2°W starting on April 1, 2025 and through the operational transition. Until the transition time and during the final stretch of Post Launch Product Testing (PLPT), GOES-19 products are considered non-operational regardless of their validation maturity level. Shortly following the transition of GOES-19 to GOES-East, all data distribution from GOES-16 will be turned off. GOES-16 will drift to the storage location at 104.7°W. GOES-19 data should begin flowing again on April 4th once this maneuver is complete.

NEW GOES 16 Reprocess Data!! The reprocessed GOES-16 ABI L1b data mitigates systematic data issues (including data gaps and image artifacts) seen in the Operational products, and improves the stability of both the radiometric and geometric calibration over the course of the entire mission life. These data were produced by recomputing the L1b radiance products from input raw L0 data using improved calibration algorithms and look-up tables, derived from data analysis of the NIST-traceable, on-board sources. In addition, the reprocessed data products contain enhancements to the L1b file format, including limb pixels and pixel timestamps, while maintaining compatibility with the operational products. The datasets currently available span the operational life of GOES-16 ABI, from early 2018 through the end of 2024. The Reprocessed L1b dataset shows improvement over the Operational L1b products but may still contain data gaps or discrepancies. Please provide feedback to Dan Lindsey (dan.lindsey@noaa.gov) and Gary Lin (guoqing.lin-1@nasa.gov). More information can be found in the GOES-R ABI Reprocess User Guide.


NOTICE: As of January 10th 2023, GOES-18 assumed the GOES-West position and all data files are deemed both operational and provisional, so no ‘preliminary, non-operational’ caveat is needed. GOES-17 is now offline, shifted approximately 105 degree West, where it will be in on-orbit storage. GOES-17 data will no longer flow into the GOES-17 bucket. Operational GOES-West products can be found in the GOES-18 bucket.

GOES satellites (GOES-16, GOES-17, GOES-18 & GOES-19) provide continuous weather imagery and monitoring of meteorological and space environment data across North America. GOES satellites provide the kind of continuous monitoring necessary for intensive data analysis. They hover continuously over one position on the surface. The satellites orbit high enough to allow for a full-disc view of the Earth. Because they stay above a fixed spot on the surface, they provide a constant vigil for the atmospheric "triggers" for severe weather conditions such as tornadoes, flash floods, hailstorms, and hurricanes. When these conditions develop, the GOES satellites are able to monitor storm development and track their movements. SUVI products available in both NetCDF and FITS.

The NOAA Geostationary Operational Environmental Satellite (GOES) series provides continuous measurements of the atmosphere and surface over the Western Hemisphere. The GOES satellites circle the Earth in a geosynchronous orbit, which means they orbit the equatorial plane of the Earth at a speed matching the Earth's rotation. This orbit allows them to hover continuously over one position on the surface of the Earth. The geosynchronous plane is about 35,800 km (22,300 miles) above the Earth, high enough to allow the satellites a full-disc view of the Earth. The GOES-East satellite is positioned over the equator at 75 degrees West longitude, and the GOES-West satellite is positioned at 135 degrees West longitude. The GOES Imager is a five-channel (one visible, four infrared) imaging radiometer designed to sense radiant and solar reflected energy from sampled areas of the earth. GOES data are used by researchers for understanding interactions between land, ocean, atmosphere, and climate. GOES Variable (GVAR) format is the data transmission format used to broadcast environmental data measured by the independent GOES Imager and Sounder instruments, beginning with GOES-8 launched in 1994. Data distribution formats available to users are raw, AREA, NetCDF, GIF, and JPEG.

Database including cloud-free Sentinel-2 optical imagery cropped for the Tatra Transboundary Biosphere Reserve area. The data was obtained from the Copernicus Data Space Ecosystem - CDSE service, which provides data for the Earth observation programme Copernicus managed by the European Commission and the European Space Agency. Data acquired by the MSI optical multispectral instrument. Data were preprocessed at the L2A processing level, i.e. including atmospheric and geometric correction.The area included two Sentinel-2 scenes (granules): 34UCV and 34UDV, located on orbits 079, 036. Spectral channels (12 bands) were resampled to a common resolution of 10m and the scenes mosaicked with each other. The raster data were then cropped to the extent of the Tatra Transboundary Biosphere Reserve. For each year, one image from the September-October period was selected to allow spectral coherence of the images for analysis. The open-source library GDAL, rasterio and the Python language were used for data processing.Raster data characteristics:Compression: LZW EPSG code: 32634Number of channels: 12Channels order:'B01' - Coastal aerosol (443 nm, 60m resolution) 'B02' - Blue (490 nm, 10m resolution) 'B03' - Green (560 nm, 10m resolution) 'B04' - Red (665 nm, 10m resolution) 'B05' - Vegetation red edge (705 nm, 20m resolution) 'B06' - Vegetation red edge (740 nm, 20m resolution) 'B07' - Vegetation red edge (783 nm, 20m resolution) 'B08' - Near-infrared (NIR) (842 nm, 10m resolution) 'B8A' - Narrow NIR (865 nm, 20m resolution) 'B09' - Water vapor (945 nm, 60m resolution) 'B11' - Shortwave infrared (SWIR) (1610 nm, 20m resolution) 'B12' - Shortwave infrared (SWIR) (2190 nm, 20m resolution) Research funded by the National Science Centre (NCN), under the project Preludium 22, grant no. 2023/49/N/ST10/00517, entitled: ‘Spruce Forest Damage Assessment Using Machine Learning on Sentinel-2 Time Series in the Tatra Mountains’.

Satellite images are essentially the eyes in the sky. Some of the recent satellites, such as WorldView-3, provide images with a spatial resolution of *** meters. This satellite with a revisit time of under ** hours can scan a new image of the exact location with every revisit.

Spatial resolution explained Spatial resolution is the size of the physical dimension that can be represented on a pixel of the image. Or in other words, spatial resolution is a measure of the smallest object that the sensor can resolve measured in meters. Generally, spatial resolution can be divided into three categories:

– Low resolution: over 60m/pixel. (useful for regional perspectives such as monitoring larger forest areas)

– Medium resolution: 10‒30m/pixel. (Useful for monitoring crop fields or smaller forest patches)

– High to very high resolution: ****‒5m/pixel. (Useful for monitoring smaller objects like buildings, narrow streets, or vehicles)

Based on the application of the imagery for the final product, a choice can be made on the resolution, as labor intensity from person-hours to computing power required increases with the resolution of the imagery.

The cost of acquiring a satellite data was highest for the images from the GeoEye-1 satellite, at ** U.S. dollars per square kilometer of the image. Most of the satellite data have a minimum order quantities based on the company and the cost depends mostly on the spatial resolution of the satellite image. Most of the satellites are commercially owned and provide users with data as an end product based on the requirement. Processing smaller patches of the raw images obtained from a satellite to an end product are not profitable. Hence, there is a minimum order limit of ** to ** square kilometers based on the requested product.

Satellite Data Services Market Outlook

As per our latest research, the global satellite data services market size reached USD 8.7 billion in 2024, driven by increasing demand for real-time geospatial intelligence and advanced analytics across multiple industries. The market is poised for robust expansion, registering a CAGR of 18.2% from 2025 to 2033. By 2033, the satellite data services market is forecasted to attain a value of USD 44.1 billion, propelled by technological advancements, the proliferation of small satellite constellations, and growing integration of satellite data into commercial applications. This growth trajectory underscores the transformative impact of satellite data on decision-making processes and operational efficiency across global sectors.

One of the principal growth factors for the satellite data services market is the surge in demand for high-resolution imagery and geospatial analytics across sectors such as agriculture, energy, defense, and environmental monitoring. The rapid digitization of industries and the need for precise, real-time data to support critical operations have fueled investments in satellite data services. Additionally, the increasing frequency of natural disasters and the growing importance of climate change monitoring have necessitated the use of satellite-based solutions for timely and accurate information. The integration of artificial intelligence and machine learning with satellite data analytics has further amplified the value proposition of these services, enabling predictive insights and automated anomaly detection for enhanced decision-making.

Another significant driver is the expansion of small satellite constellations and the decreasing cost of satellite launches, which have democratized access to satellite data. The advent of low Earth orbit (LEO) satellites has revolutionized data acquisition, offering improved revisit rates and cost-effective solutions for commercial and governmental clients. The proliferation of private players and public-private partnerships has accelerated innovation in satellite data services, resulting in enhanced data quality, faster delivery times, and a wider range of value-added services. This democratization has opened new avenues for start-ups and SMEs, fostering a competitive environment that stimulates continuous technological advancement and market expansion.

The satellite data services market is also benefiting from increased government initiatives and policy support for space-based infrastructure and data utilization. Governments worldwide are investing in satellite programs to bolster national security, disaster management, and socio-economic development. These initiatives have led to greater collaboration between governmental agencies and private enterprises, promoting the adoption of satellite data for urban planning, resource management, and infrastructure development. Moreover, international efforts to standardize satellite data formats and improve interoperability are facilitating cross-border data sharing, thereby expanding the global reach and utility of satellite data services.

In the rapidly evolving landscape of satellite data services, Space Data Replay and Reprocessing Services are emerging as crucial components for enhancing data utility and accessibility. These services facilitate the retrieval and reprocessing of archived satellite data, enabling users to extract new insights and revisit past events with enhanced analytical capabilities. By leveraging advanced algorithms and cloud-based platforms, Space Data Replay and Reprocessing Services allow for the refinement of historical data, providing a more comprehensive understanding of temporal changes and trends. This capability is particularly valuable for sectors such as environmental monitoring and disaster management, where historical data can inform future strategies and improve response times. As the demand for historical data analysis grows, these services are becoming integral to maximizing the value of satellite data investments.

Regionally, North America remains the largest market for satellite data services, accounting for over 37% of global revenue in 2024, driven by the presence of leading satellite operators, advanced technological infrastructure, and substantial government funding. Eu

STRAT_Satellite_Data is the supplementary satellite data collected during the Stratospheric Tracers of Atmospheric Transport (STRAT) campaign. Satellite images from the GOES-7 and GOES-9 satellites are featured in this collection. Data collection for this product is complete.The STRAT campaign was a field campaign conducted by NASA from May 1995 to February 1996. The primary goal of STRAT was to collect measurements of the change of long-lived tracers and functions of altitude, latitude, and season. These measurements were taken to aid with determining rates for global-scale transport and future distributions of high-speed civil transport (HSCT) exhaust that was emitted into the lower atmosphere. STRAT had four main objectives: defining the rate of transport of trace gases from the stratosphere and troposphere (i.e., HSCT exhaust emissions), improving the understanding of dynamical coupling rates for transport of trace gases between tropical regions and higher latitudes and lower altitudes (between tropical regions, higher latitudes, and lower altitudes are where most ozone resides), improving understanding of chemistry in the upper troposphere and lower stratosphere, and finally, providing data sets for testing two-dimensional and three-dimensional models used in assessments of impacts from stratospheric aviation. To accomplish these objectives, the STRAT Science Team conducted various surface-based remote sensing and in-situ measurements. NASA flew the ER-2 aircraft along with balloons such as ozonesondes and radiosondes just below the tropopause in the Northern Hemisphere to collect data. Along with the ER-2 and balloons, NASA also utilized satellite imagery, theoretical models, and ground sites. The ER-2 collected data on HOx, NOy, CO2, ozone, water vapor, and temperature. The ER-2 also collected in-situ stratospheric measurements of N2O, CH4, CO, HCL, and NO using the Aircraft Laser Infrared Absorption Spectrometer (ALIAS). Ozonesondes and radiosondes were also deployed to collect data on CO2, NO/NOy, air temperature, pressure, and 3D wind. These balloons also took in-situ measurements of N2O, CFC-11, CH4, CO, HCL, and NO2 using the ALIAS. Ground stations were responsible for taking measurements of O3, ozone mixing ratio, pressure, and temperature. Satellites took infrared images of the atmosphere with the goal of aiding in completing STRAT objectives. Pressure and temperature models were created to help plan the mission.

Explore insights from Market Research Intellect's Satellite Data Services Market Report, valued at USD 5.2 billion in 2024, expected to reach USD 15.8 billion by 2033 with a CAGR of 13.5% during 2026-2033.Uncover opportunities across demand patterns, technological innovations, and market leaders.

Satellite Data Services Market is projected to reach USD 67.02 billion by 2033, growing at a CAGR of 22.69% from 2025-2033.

EarthCARE data products encompass essential supporting auxiliary (AUX) and orbit data critical for accurate sensor data processing and analysis. Orbit data consists of on-board satellite data and orbital information predicted or determined by the Flight Operations Segment (FOS). For EarthCARE, this includes Reconstructed Orbit and Attitude Files, which provide detailed satellite positioning and orientation information. The integration of AUX and orbit data into EarthCARE's data processing workflow ensures the production of high-quality, scientifically valuable datasets for atmospheric research, climate modelling, and environmental monitoring.

Introduction

The Satellite Data Service Market is projected to grow from USD 11.5 billion in 2024 to approximately USD 62.3 billion by 2034, exhibiting a robust CAGR of 18.4%. North America led the market in 2024 with a 39.0% share, generating revenues close to USD 4.4 billion. The U.S. segment alone, valued at USD 3.4 billion, is expected to grow at a CAGR of 19.1%. Increasing demand for high-resolution satellite imagery, advancements in satellite technology, and expanding applications across sectors such as agriculture, defense, and telecommunications are driving this rapid growth.