The Global Remote Sensing Technology Market size was valued at USD 15,560 million in 2021 and expected to grow at a CAGR of 12.5%, generating USD 44,900 million during the forecast period (2022–2030). Remote sensing is a geospatial technology that emits and reflects electromagnetic (EM) radiation from the Earth's terrestrial, atmospheric, and aquatic ecosystems to detect and monitor the physical characteristics of an area without physical contact. This data collection method typically employs passive and active sensor technologies based on aircraft and satellites. Passive sensors collect radiation reflected or emitted by an object or the surrounding environment in response to external stimuli. Reflected sunlight is the most common source of radiation measured by passive remote sensing. Active sensors rely on internal stimuli to collect data, emitting energy that scans objects and areas before measuring the energy reflected from the target.
IoT in agriculture displays crops on a screen and provides information to farmers for efficient farm management by utilizing remote sensors, robots, drones, and PC imaging. Data is collected and then transmitted for analysis using Internet of Things (IoT) sensors. Using a standardized dashboard, farmers can display the quality of their crops.
A revolutionary new sensor design is transforming remote sensing and GIS technologies. It is used for spatial data analysis, mapping, and distribution. Using satellite or aircraft images, distance-based remote sensing extracts spatially precise characteristics of the Earth's water and land surfaces. The GIS data and parameters are subsequently analyzed, managed, stored, and displayed. Using remote sensing data with varying spatial and temporal resolutions, environmental variables can be measured. Using GIS, integrated strategies and solutions are developed by combining geospatial data from remote sensing and other sources, demographics, and socioeconomics. Advanced image processing methods and algorithms enable the creation of a global environment database more quickly. Environmental risks caused by humans or natural disasters pose a growing threat to local, regional, and international communities. The functions and health of modern civilization depend on timely and effective ecological risk assessment and management. These technologies enable the creation of geo-referenced reports and maps, which can be utilized to create comprehensive environmental solutions. Systeme d'information géospatiale et techniques de télédétection permettent aux décideurs et aux scientifiques de mieux gérer les dangers environnementaux As global industrialization and population growth increase pressure on the planet's environment, remote sensing and GIS will become increasingly vital for managing and assessing environmental risks.
Modern food production and agriculture systems are under pressure from shrinking land and water resources, climate change, and rising production costs. Furthermore, the COVID-19 crisis threatens to disrupt food supply and production systems. These factors jeopardize the economic and environmental sustainability of current and future food supply systems. Technological and scientific advances are required to feed a rapidly expanding global population. Science has improved our understanding of how components of the agricultural system interact, from the cell to the field.
Nonetheless, recent advances in AI and remote sensing have made it possible to precisely measure field-scale phenotypic information and integrate big data into prescriptive and predictive management tools. While agriculture is constantly evolving, substantial changes are required to keep up with climate change. Agricultural firms and researchers have been investigating ways to integrate cutting-edge technologies like remote sensing into agriculture systems to address concerns about producing enough food for a rapidly growing global population.
Remote sensing and geospatial information & mapping have advanced rapidly in recent decades. Remote sensing has many applications. The demand for geospatial data has led to the development of various remote sensing technologies.
As a result, many government agencies, research institutions, and private companies use remote sensing to collect data. While remote sensing offers improved utilization and accessibility to complicated problems, it also involves numerous challenges. Large data volumes and complex data formats with detailed processing are significant issues. As a result, users will likely turn to open GIS data formats and real-time data processing to utilize spatial data better.
Also, the current satellite data coverage limitations are evident and need to be addressed. For example, polar-orbiting LEO imagers typically cover the entire globe in one day, leaving out natural occurrences with high spatial and temporal variability. High-orbit Geostationary Observations (GEO) tackle this limitation by offering regular daily observation of the same object.
Artificial Intelligence (AI) and Machine Learning (ML) are gaining enormous attention in geomatics. These technologies can positively transform and disrupt the field by augmenting and replacing elements of conventional remote sensing, modelling, and assimilation tools. The Internet of Things (IoT) and SmallSats will continue to generate new environmental data. This is expected to fuel the growth of the remote sensing technology market.
The field of machine learning is rapidly evolving. Because machine learning models can adapt to nonlinearity, they are more efficient and accurate. There are numerous applications in remote sensing and geosciences, including retrieval algorithms, code acceleration, crop disease detection, and bias modification, consisting of aerosol products, vegetation indices, retrievals, trace gases, land surface, and, most recently, ocean products.
In turn, this increases the workload of remote sensing analysts and specialists. Many organizations rely on remote sensing and imagery data, which they obtain and analyze using advanced data analysis techniques. The data acquisition can be accelerated by using spatial modelling, machine learning, and deep learning, which will allow the algorithms to learn to understand and process ever-increasing amounts of data.
The COVID-19 pandemic has negatively impacted several industries. Consequently, stakeholders and governments request strategies to restore normalcy while effectively combating the pandemic. However, governments and businesses closely associated with the satellite and space industries respond differently to the situation. Nevertheless, airborne and satellite data can aid in detecting indirect impacts of the pandemic through remote sensing by using historical remote sensing data as a baseline and then tracking the economic, environmental, and societal impacts caused by the pandemic outbreak.
Due to the increasing need to quantify the social and economic impact of the pandemic outbreak, the demand for crisis monitoring and business intelligence has increased dramatically. Currently, companies that provide satellite data services are actively contributing to the response efforts by providing processing and storage capabilities for modelling and other research needs and analyzing the pandemic's overall impact. Companies also provide earth observation imagery for monitoring remotely located infrastructure.
In addition, as several nations worldwide-imposed lockdowns as part of their efforts to halt the disease's spread, satellite data and imagery assisted in gaining access to data without violating social distance regulations.
The Global Remote Sensing Technology Market share is categorized by
Active and passive sensing technologies comprise the technology segment. Passive remote sensing technology monitors and analyses surface characteristics by measuring the sunlight reflected on Earth's surface. Active sensing technology, in contrast, emits its light to monitor and analyze surface characteristics. Dynamic sensing technology circumvents the inability of passive sensors to function at night. Despite this, the passive sensing technology segment held the largest market share in 2021 and is expected to grow at a CAGR of 13% and reach USD 28,900 Million by 2030.
The aerial systems segment held the largest market share in 2021 and is projected to grow at a compound annual growth rate of 13.5% between 2022 and 2030. The increasing use of unmanned aerial vehicles (UAV) in aerial mapping is the primary driver of the segment's rapid expansion. The application of aerial mapping reduces human error and increases the overall speed of surveying and area coverage. In addition, they can aid in the surveying of areas inaccessible to satellite images, thereby enhancing their utility. These factors make aerial platforms the platform of choice for remote sensing applications. The segment of satellite-based sensing is also anticipated to expand steadily, primarily due to satellite-based weather forecasting applications.
n 2021, the military and intelligence sector captured more than a quarter of the market for remote sensing technology and is expected to grow at a CAGR of 11.5% in the forecasted 2022-2030. The segment's large revenue share is attributable to the ability of these sensing technologies to carry out covert applications without putting human lives at risk. The primary applications of remote sensing technologies in the military are intelligence gathering and navigation support. As more and more military units adopt technologies for their operations over the next seven years, it is expected that the segment will experience steady growth. Other applications include agriculture & living resources, disaster management, infrastructure, and weather, among others, and military and intelligence.
The Remote Sensing Technology market share is segmented into North America, Europe, Asia-Pacific, Latin America, and the Middle East and Africa. North America is anticipated to hold the largest market share of USD 10,650 million by 2030, growing at a CAGR of approximately 10%.
This share is attributable to significant market participants, such as Esri, General Dynamics Mission Systems, Inc., Lockheed Martin Corporation, and Raytheon Technologies Corporation. The utilization of remote sensing technology in precision agriculture applications is anticipated to drive market expansion over the forecast period. The technology equips water resource managers with tools to mitigate the effects of dry spells and drought and match crop irrigation needs.
Over the next nine years, Asia Pacific is expected to grow at a substantial CAGR of over 14%. This is due to the increasing adoption of earth observation applications for infrastructure development. Countries such as India, China, and Japan are launching satellites to improve their earth observation capabilities and development assistance. The Indian Space Research Organization (ISRO) had announced plans to launch ten additional earth observation satellites within the next two years. Additionally, government initiatives for urban infrastructure development, such as India's Smart City Mission, are anticipated to boost the market growth in the country and region.
|Market Size||USD in Billion By 2030|
|Forecast Units||Value (USD Million)|
|Report Coverage||Revenue Forecast, Competitive Landscape, Growth Factors, Environment & Regulatory Landscape and Trends|
|Segments Covered||by Technology: (Active Sensing), Platform (Satellite, Aerial Systems), Application (Military & Intelligence)|
|Geographies Covered||North America, Europe, Asia-Pacific, LAME and Rest of the World|
|Key Companies Profiled/Vendors||Maxar Technologies, Esri, General Dynamics Mission Systems Inc, Hexagon, Lockheed Martin Corporation, Orbital Insight, Planet Labs Inc., Raytheon Technologies Corporation, Teledyne Technologies Incorporated,|
|Key Market Opportunities||The Technology Industry'S Substantial Growth Fuels The Remote Sensing Technology Market|