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Satellite Data Services Market: Rise in Demand for AI & Big Data Technology in Space Industry

Posted | Updated by Insights team:
Dr. Evangelo Damigos; PhD | Head of Digital Futures Research Desk
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Publication | Update: Sep 2020

According to the Markets & Markets Report, on Satellite Data Services Market, the satellite data services market size is projected to grow from USD 7.5 billion in 2019 to USD 23.4 billion by 2025, at a CAGR of 21.0% from 2019 to 2025. Some of the factors that are expected to fuel the growth of the market are significant advancements in geospatial imagery analytics with the introduction of AI and big data, privatization of space industry, and growth of cloud computing.

Based on the vertical, the environmental segment of the satellite data services market is projected to grow at the highest CAGR during the forecast period.

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Based on the vertical, the environmental segment of the satellite data services industry is projected to grow at the highest CAGR from 2019 to 2025. Satellite data or imagery is used in large turnkey projects to analyze their expected impact on the environment, boost their efficiency, and lessen their carbon footprint. Hyperspectral satellite imagery incorporated with field and laboratory data for analysis can be used to derive more quantitative and precise soil properties directly linked to soil degradation status, such as soil chemical properties, organic matter, mineralogical content, etc.

Based on the end-use, the commercial segment is expected to lead the satellite data services market from 2019 to 2025.

Based on the end-use, the commercial segment of the satellite data services market is projected to grow at the highest CAGR from 2019 to 2025. The extensive use of satellite imagery for multi-scale geological mapping, monitoring pipelines via satellite in near real-time, track large project developments, shipping routes, construction sites, the need for satellite data services has increased over the years, and as technology gets more advanced, autonomous drilling and monitoring via satellite will play a key role in commercial industries

Based on service, the data analytics segment of the satellite data services market is projected to grow at the highest CAGR from 2019 to 2025.

Based on service, the data analytics segment of the satellite data services market is projected to grow at the highest CAGR from 2019 to 2025. The data analytics segment is segmented further into image data processing which includes pan-sharpening, orthorectification, mosaicking, cloud patching, and others. Demand for these services will grow during the forecast period as a combination of them are required as a prerequisite for developing GIS maps and analyzing data presented in a satellite image.

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Asia Pacific satellite data services market is projected to grow at the highest CAGR from 2019 to 2025.

Asia Pacific is anticipated to be the fastest-growing market for satellite imagery and data analytics. Over the past decade, satellite imagery and data analytical technologies have been used for rural and agricultural development in this region. Companies, operating in various verticals such as energy & power, engineering & infrastructure, agriculture, transport & logistics, and maritime, among others, are using data analytical technologies to identify potential markets to enhance their growth prospects and undertake strategic decisions. The increasing adoption of data analytics for satellite imagery by governments such as India, China, and Singapore, to assist urban infrastructure development and planning, map land use, and monitor agriculture under the precision agriculture modules is driving he growth of the market.

Key Market Players

Various players such as Airbus SE (Netherlands), Harris Geospatial Solutions, Inc. (US), DigitalGlobe (US), Satellite Imaging Corporation (US), Planet Labs, Inc.(US), ICEYE (Finland), URSA Space Systems (US), SATPALDA Geospatial Services (India), Earth-i Ltd. (UK), and Land Info Worldwide Mapping (US) are focusing on providing  satellite data services with advanced features such as feature extraction, Digital Terrain Model (DTM), Digital Surface Model (DSM), and land cover & change detection, among others. These players have adopted various growth strategies such as contracts, acquisitions, expansions, new product launches, and partnerships & agreements to expand their presence in the satellite data services further.

There are opportunities for innovative companies to provide image data services for various verticals such as defense & security, energy & power, environmental, agriculture.

The Allied Market Research report presents information related to key drivers, restraints, and opportunities along with detailed analysis of the global satellite data services market.

The global satellite data services market is experiencing a significant growth since the advent of data driven fourth industrial revolution. Satellite data services compromise of selling geo-spatial imagery, chemical, physical, and biological characteristics data of earth, which is produced and stored in satellites revolving around the earth’s orbit. Additionally, satellite date services also cater to defense forces by providing data to enhance communication between defense services. Moreover, satellite data services are transforming business landscape by bringing transparency and efficiency among different industries such as critical infrastructure protection and military reconnaissance. Further, satellite data services analyze data presented in a satellite image to provide data analytics.

COVID-19 Scenario Analysis on Satellite Data Services Market:

• COVID-19 pandemic has forced space industry companies to put their satellite launch and manufacturing operations on hold due to government regulations to contain the spread of virus.
• Satellite data service companies are facing short term operational issues due to lack of site access restrictions imposed by authorities to contain the COVID-19.
• Satellite data services are facing high server down time, since servers require constant maintenance for maximum up time.
• Satellite data services are crunching their financial resources by server up keep and maintenance without consumers of data services. Since, COVID-19 has impacted all industries, the buyers of data services have reduced significantly during the lockdown imposed by the government.
• Space industry is witnessing a huge workforce shortage, since most companies or agencies rely on international workforce for their operations.

Top impacting factors: market scenario analysis, trends, drivers and impact analysis

Surge in privatization of space industry, increase in demand for AI & big data, and rise in adoption of cloud computing are the factors that drive the global satellite data services market. However, potential data breaches and expensive data access hinder the market growth. On the contrary, emergence of satellite as a service and increasing usage of satellite data services in agriculture by government present new pathways in the industry.

The global satellite data services market trends are as follows:

Surge in privatization of space industry

Privatization of space industry is facilitating satellite imagery adopters with insightful spatial imagery. Additionally, privatization of space has increased competition amongst the satellite data service providers. Moreover, privatization has enabled growth & investment in the satellite and space data service technologies. Hence, surge in privatization of satellite data services is expected to boost the global satellite data services market.

Demand for AI & big data

Big data is systematic extraction and analysis of large data sets that are too large for traditional data processing software. Launch of satellites by satellite manufacturers into lower and medium orbits to facilitate data services can be attributed to increase in demand for big data. Moreover, use of big data in satellite imagery reduces data acquisition cost, data storage cost, and data processing cost which is driving the growth of the market. In addition, AI enables data analytics and geospatial analytics of high-resolution satellite imagery. Such usage of AI & big data in satellite data services for business-driven application is expected to fuel the growth global satellite data services market.

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Objectives and Study Scope

This study has assimilated knowledge and insight from business and subject-matter experts, and from a broad spectrum of market initiatives. Building on this research, the objectives of this market research report is to provide actionable intelligence on opportunities alongside the market size of various segments, as well as fact-based information on key factors influencing the market- growth drivers, industry-specific challenges and other critical issues in terms of detailed analysis and impact.

The report in its entirety provides a comprehensive overview of the current global condition, as well as notable opportunities and challenges. The analysis reflects market size, latest trends, growth drivers, threats, opportunities, as well as key market segments. The study addresses market dynamics in several geographic segments along with market analysis for the current market environment and future scenario over the forecast period. The report also segments the market into various categories based on the product, end user, application, type, and region.
The report also studies various growth drivers and restraints impacting the  market, plus a comprehensive market and vendor landscape in addition to a SWOT analysis of the key players.  This analysis also examines the competitive landscape within each market. Market factors are assessed by examining barriers to entry and market opportunities. Strategies adopted by key players including recent developments, new product launches, merger and acquisitions, and other insightful updates are provided.

Research Process & Methodology

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We leverage extensive primary research, our contact database, knowledge of companies and industry relationships, patent and academic journal searches, and Institutes and University associate links to frame a strong visibility in the markets and technologies we cover.

We draw on available data sources and methods to profile developments. We use computerised data mining methods and analytical techniques, including cluster and regression modelling, to identify patterns from publicly available online information on enterprise web sites.
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In addition to our own desk research, various secondary sources, such as Hoovers, Dun & Bradstreet, Bloomberg BusinessWeek, Statista, are referred to identify key players in the industry, supply chain and market size, percentage shares, splits, and breakdowns into segments and subsegments with respect to individual growth trends, prospects, and contribution to the total market.

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Forecast methodology

The future outlook “forecast” is based on a set of statistical methods such as regression analysis, industry specific drivers as well as analyst evaluations, as well as analysis of the trends that influence economic outcomes and business decision making.
The Global Economic Model is covering the political environment, the macroeconomic environment, market opportunities, policy towards free enterprise and competition, policy towards foreign investment, foreign trade and exchange controls, taxes, financing, the labour market and infrastructure. We aim update our market forecast to include the latest market developments and trends.

Forecasts, Data modelling and indicator normalisation

Review of independent forecasts for the main macroeconomic variables by the following organizations provide a holistic overview of the range of alternative opinions:

  • Cambridge Econometrics (CE)

  • The Centre for Economic and Business Research (CEBR)

  • Experian Economics (EE)

  • Oxford Economics (OE)

As a result, the reported forecasts derive from different forecasters and may not represent the view of any one forecaster over the whole of the forecast period. These projections provide an indication of what is, in our view most likely to happen, not what it will definitely happen.

Short- and medium-term forecasts are based on a “demand-side” forecasting framework, under the assumption that supply adjusts to meet demand either directly through changes in output or through the depletion of inventories.
Long-term projections rely on a supply-side framework, in which output is determined by the availability of labour and capital equipment and the growth in productivity.
Long-term growth prospects, are impacted by factors including the workforce capabilities, the openness of the economy to trade, the legal framework, fiscal policy, the degree of government regulation.

Direct contribution to GDP
The method for calculating the direct contribution of an industry to GDP, is to measure its ‘gross value added’ (GVA); that is, to calculate the difference between the industry’s total pre­tax revenue and its total bought­in costs (costs excluding wages and salaries).

Forecasts of GDP growth: GDP = CN+IN+GS+NEX

GDP growth estimates take into account:

  • Consumption, expressed as a function of income, wealth, prices and interest rates;

  • Investment as a function of the return on capital and changes in capacity utilization; Government spending as a function of intervention initiatives and state of the economy;

  • Net exports as a function of global economic conditions.

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Market Quantification
All relevant markets are quantified utilizing revenue figures for the forecast period. The Compound Annual Growth Rate (CAGR) within each segment is used to measure growth and to extrapolate data when figures are not publicly available.

Revenues

Our market segments reflect major categories and subcategories of the global market, followed by an analysis of statistical data covering national spending and international trade relations and patterns. Market values reflect revenues paid by the final customer / end user to vendors and service providers either directly or through distribution channels, excluding VAT. Local currencies are converted to USD using the yearly average exchange rates of local currencies to the USD for the respective year as provided by the IMF World Economic Outlook Database.

Industry Life Cycle Market Phase

Market phase is determined using factors in the Industry Life Cycle model. The adapted market phase definitions are as follows:

  • Nascent: New market need not yet determined; growth begins increasing toward end of cycle

  • Growth: Growth trajectory picks up; high growth rates

  • Mature: Typically fewer firms than growth phase, as dominant solutions continue to capture the majority of market share and market consolidation occurs, displaying lower growth rates that are typically on par with the general economy

  • Decline: Further market consolidation, rapidly declining growth rates

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The Global Economic Model
The Global Economic Model brings together macroeconomic and sectoral forecasts for quantifying the key relationships.

The model is a hybrid statistical model that uses macroeconomic variables and inter-industry linkages to forecast sectoral output. The model is used to forecast not just output, but prices, wages, employment and investment. The principal variables driving the industry model are the components of final demand, which directly or indirectly determine the demand facing each industry. However, other macroeconomic assumptions — in particular exchange rates, as well as world commodity prices — also enter into the equation, as well as other industry specific factors that have been or are expected to impact.

  • Vector Auto Regression (VAR) statistical models capturing the linear interdependencies among multiple time series, are best used for short-term forecasting, whereby shocks to demand will generate economic cycles that can be influenced by fiscal and monetary policy.

  • Dynamic-Stochastic Equilibrium (DSE) models replicate the behaviour of the economy by analyzing the interaction of economic variables, whereby output is determined by supply side factors, such as investment, demographics, labour participation and productivity.

  • Dynamic Econometric Error Correction (DEEC) modelling combines VAR and DSE models by estimating the speed at which a dependent variable returns to its equilibrium after a shock, as well as assessing the impact of a company, industry, new technology, regulation, or market change. DEEC modelling is best suited for forecasting.

Forecasts of GDP growth per capita based on these factors can then be combined with demographic projections to give forecasts for overall GDP growth.
Wherever possible, publicly available data from official sources are used for the latest available year. Qualitative indicators are normalised (on the basis of: Normalised x = (x - Min(x)) / (Max(x) - Min(x)) where Min(x) and Max(x) are, the lowest and highest values for any given indicator respectively) and then aggregated across categories to enable an overall comparison. The normalised value is then transformed into a positive number on a scale of 0 to 100. The weighting assigned to each indicator can be changed to reflect different assumptions about their relative importance.

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The principal explanatory variable in each industry’s output equation is the Total Demand variable, encompassing exogenous macroeconomic assumptions, consumer spending and investment, and intermediate demand for goods and services by sectors of the economy for use as inputs in the production of their own goods and services.

Elasticities
Elasticity measures the response of one economic variable to a change in another economic variable, whether the good or service is demanded as an input into a final product or whether it is the final product, and provides insight into the proportional impact of different economic actions and policy decisions.
Demand elasticities measure the change in the quantity demanded of a particular good or service as a result of changes to other economic variables, such as its own price, the price of competing or complementary goods and services, income levels, taxes.
Demand elasticities can be influenced by several factors. Each of these factors, along with the specific characteristics of the product, will interact to determine its overall responsiveness of demand to changes in prices and incomes.
The individual characteristics of a good or service will have an impact, but there are also a number of general factors that will typically affect the sensitivity of demand, such as the availability of substitutes, whereby the elasticity is typically higher the greater the number of available substitutes, as consumers can easily switch between different products.
The degree of necessity. Luxury products and habit forming ones, typically have a higher elasticity.
Proportion of the budget consumed by the item. Products that consume a large portion of the consumer’s budget tend to have greater elasticity.
Elasticities tend to be greater over the long run because consumers have more time to adjust their behaviour.
Finally, if the product or service is an input into a final product then the price elasticity will depend on the price elasticity of the final product, its cost share in the production costs, and the availability of substitutes for that good or service.

Prices
Prices are also forecast using an input-output framework. Input costs have two components; labour costs are driven by wages, while intermediate costs are computed as an input-output weighted aggregate of input sectors’ prices. Employment is a function of output and real sectoral wages, that are forecast as a function of whole economy growth in wages. Investment is forecast as a function of output and aggregate level business investment.

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