Remote Sensing Technology Market Projected to Garner USD 16.35 Billion by 2030, Growing at 11.5% CAGR - Report by Market Research Future (MRFR)
Rising Deployments of Commercial Remote Sensing Satellites Drive this Market
/EIN News/ -- New York, US, July 04, 2022 (GLOBE NEWSWIRE) -- According to a comprehensive research report by Market Research Future (MRFR), “Remote Sensing Technology Market Analysis by Technology (Active Remote Sensing Passive Remote Sensing), By Application (Landscape Assessment, Geology and Mineral Exploration) - Global Forecast 2030” valuation is poised to reach USD 16.35 Billion by 2030, registering an 11.5% CAGR throughout the forecast period (2021–2030).
Remote Sensing Technology Market Overview
With satellites' proven capability and other remote sensing data collection solutions expanding rapidly, the market is projected to witness significant traction, states Market Research Future (MRFR).
Remote Sensing Technology Market Report Scope:
| Report Metric | Details |
| Market Size | USD 16.35 Billion by 2030 |
| CAGR | 11.5% (2021-2030) |
| Base Year | 2020 |
| Forecast Period | 2021-2030 |
| Historical Data | 2019 |
| Forecast Units | Value (USD Billion) |
| Report Coverage | Revenue Forecast, Competitive Landscape, Growth Factors, and Trends |
| Segments Covered | Technology, Application and Region |
| Geographies Covered | North America, Europe, Asia-Pacific, and Rest of the World (RoW) |
| Key Vendors | Raytheon Corporation (US), Northrop Grumman Corporation (US), General Dynamics Corp. (US), Honeywell Technology Solutions Inc. (US), ITT Corp. (US), Lockheed Martin Corporation (US), Lumasense Technologies, Inc. (US), Leica Geosystems Holdings AG (Switzerland), and Thales Group (France) |
| Key Market Opportunities | Rising Deployments of Commercial Remote Sensing Satellites Drive this Market |
| Key Market Drivers | Increasing the adoption of the technology |
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The global remote sensing technology market is expected to increase rapidly in the next few years. The rising governmental focus on developing earth observation solutions to extract information from aerial and satellite imaging systems creates a vast demand for remote sensing technology. Also, the growing emphasis on solving end-to-end remote sensing problems, using a science and engineering approach influences market dynamics.
Remote sensing technology has evolved significantly in recent years, offering impressive surveying techniques with many different advantages. This technology can survey large and inaccessible areas, and the data gathered from remote sensing can be used and analyzed in a wide range of applications multiple times.
For example, data collected by remote sensors used to survey a construction site can also be used to analyze and plan new roads. The data collected from forests to identify the risk of natural calamities, such as wildfires, could also be used to monitor biodiversity.
Some specific uses of remote sensing imagery in the planet/earth monitoring include mapping large forest fires from the space, helping track clouds to predict the weather, and watching erupting volcanoes & dust storms, tracking the city growth & changes in farmland or forests, and discovering & mapping of the rugged topography of the ocean floor.
There are many researches ongoing currently to improve remote sensing functionality. For instance, researchers at the Resilient Infrastructure and Disaster Response (RIDER) Center of the FAMU-FSU College of Engineering are investigating better ways to predict the probable areas where road-clogging debris will be most severe after tropical cyclones. This research is especially relevant as remote sensing research improves hurricane response.
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Remote sensing, IoT, and AI/ML have huge applications in agriculture, making the technology agri-specific and easy to use. Advances in new-age technologies like remote sensing, drone surveillance, and artificial intelligence (AI)-driven solutions provide unique agritech platforms to strengthen the digital infrastructure of agribusinesses.
Also, remote sensing allows agri-businesses to monitor, measure, and manage their farms, farmers, and the entire agri value chain, offering a suite of modules including farm management, remote sensing, pest management, ecommerce, etc.
Remote Sensing Technology Market Segments
The remote sensing technology market forecast is segmented into technologies, applications, and regions. The technology segment is sub-segmented into active remote sensing and passive remote sensing. The application segment is sub-segmented into air quality, landscape assessment, water quality, emergency management, floodplain mapping, healthcare, mineral exploration, geology, oceanography, agriculture, and others. The region segment is sub-segmented into Europe, the Middle East & Africa, Asia Pacific, Americas, and rest-of-the-world.
Remote Sensing Technology Market Regional Analysis
North America is the largest market for remote sensing technologies globally. The region houses well-established development centers and remote sensing technology-providing companies, which alongside growing advancements in remote sensing technology, drive the market growth. Besides, the rising use of sensors in land assessment techniques and mineral exploration activities led by the rapid growth in mining sectors boost the region's market shares.
The rising demand for applications, such as environment monitoring, floodplain mapping & water quality, and emergency management, surges the adoption of sensing technology in North America. Additionally, the rising applications of sensing technologies in the healthcare industry benefit the regional market to a great extent. The North American remote sensing technology market is projected to retain its dominance throughout the assessment period.
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Industry Trends
The remote sensing technology market witnessed a constant uptick over recent years. Industry players are also seen fostering R&D investments to advance these technologies. With the market penetration of commercial remote sensing data services for satellite data customer industries, market sales are estimated to grow constantly, remaining the most common commercial remote sensing imagery.
Commercial remote sensing data services witness augmenting demand from natural resources, surveying & mapping, and marine & environmental protection sectors, as well as emerging applications, such as digital rural development, urban security, smart agriculture, and transport. Further, the rising use of these technologies in healthcare devices would support the market growth throughout the assessment period.
Remote Sensing Technology Market Competitive Analysis
Dominant Key Players on Remote Sensing Technology Market Covered are:
- Raytheon Corporation (US)
- Northrop Grumman Corporation (US)
- General Dynamics Corp. (US)
- Honeywell Technology Solutions Inc. (US)
- ITT Corp. (US)
- Lockheed Martin Corporation (US)
- Lumasense Technologies Inc. (US)
- Leica Geosystems Holdings AG (Switzerland)
- Thales Group (France)
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The remote sensing technology market is likely to witness significant product launches and implementation of several strategic approaches, such as mergers & acquisitions, collaboration, expansion, and product/technology launches. Key market players make significant investments to drive research and development activities and expansion plans.
For instance, on April 22, 2022, Rendered.ai, a leading physics-based synthetic data platform, announced that the Digital Imaging & Remote Sensing (DIRS) Laboratory of the Rochester Institute of Technology (RIT) has collaborated with it to leverage its cloud-based platform to power synthetic data with high accuracy sensor simulation. The trio will develop a high-volume synthetic data generation solution, combining the physics-driven accuracy of the DIRSIG synthetic imagery model.
The collaboration with Rendered.ai enables DIRS & RIT to bring their proven capability to a wider user base while satellite and other forms of remote sensing data collection are rapidly expanding. The effort will enable customers in the US to use the DIRSIG model with Rendered.ai's cloud capabilities to garner earth observation datasets for AI training.
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