The geospatial analytics market is expected to grow from USD 40.65 Billion in 2018 to USD 86.32 Billion by 2023, at a CAGR of 16.3% from 2018 to 2023.
The global market is projected to witness a massive growth during the forecast period, majorly driven by the increasing penetration of Internet of Things (IoT), integration of geospatial technology with mainstream technologies, and significant advancements in geospatial analytics with the introduction of artificial intelligence and big data.
With the introduction of artificial intelligence and big data in the market, geospatial analytics can provide better and less expensive geospatial data to organizations across the globe. These solutions also provide additional benefits such as the ability to serve on-demand analytics, increased accessibility and ability to analyze complex and large datasets, and analyzing multiple types of geospatial information through cloud-based geospatial analytics.
A key restraining factors impacting the growth of the geospatial analytics market is the high cost of geospatial analytics solutions. The development of geospatial analytics solutions for acquiring real-time data increases the complexity of the GIS software. High complexities involved in the development of GIS software and real-time data collection result in high cost of software. Due to this, companies with limited financial resources are not able to invest in commercial geospatial solutions. The implementation of geospatial analytics solutions requires high initial investment, thereby resulting in a lower rate of adoption in small and medium-sized companies.
Key Topics Covered:
2 Research Methodology
3 Executive Summary
4 Premium Insights 4.1 Attractive Opportunities in the Geospatial Analytics Market 4.2 Market By Component 4.3 Market Top Three Types 4.4 Market By Application 4.5 Market Top Three Verticals and Regions
5 Market Overview and Industry Trends 5.1 Market Overview 5.1.1 Introduction 5.1.2 Drivers 22.214.171.124 Increasing Penetration of Internet of Things (IoT) 126.96.36.199 Integration of Geospatial Technology With Mainstream Technologies 188.8.131.52 Advancements in Geospatial Analytics With the Introduction of Artificial Intelligence and Big Data Analytics 5.1.3 Restraints 184.108.40.206 High Cost of Geospatial Analytics Solutions 220.127.116.11 Regulations and Legal Issues 5.1.4 Opportunities 18.104.22.168 Increasing Use of Location-Based Services 22.214.171.124 Development of 4d Gis Software 5.1.5 Challenges 126.96.36.199 Complexities Involved in Integration of Geospatial Data With Enterprise Solutions 5.2 Industry Trends 5.2.1 Introduction 5.2.2 Geospatial Analytics: Case Studies 188.8.131.52 Case Study 1: Retail Company Increases Operational Productivity 184.108.40.206 Case Study 2: Healthcare Company Improves Perinatal Health Services 5.3 Regulatory Implications 5.4 Standards