How big is the China Geospatial Analytics Market?

The China Geospatial Analytics Market size is expected to reach USD 2.52 billion in 2024 and grow at a CAGR of 10.69% to reach USD 4.19 billion by 2029. Read More

What is the current China Geospatial Analytics Market size?

In 2024, the China Geospatial Analytics Market size is expected to reach USD 2.52 billion. Read More

Who are the key players in China Geospatial Analytics Market?

Qianxun Spatial Intelligence, SZ Soarability Technology LLC, Jiangsu Xingyue Surveying and Mapping Technology Co., Ltd., Zhejiang Zhenshan Technology Co., Ltd. and Weihai Wuzhou Navi-Tech are the major companies operating in the China Geospatial Analytics Market. Read More

What years does this China Geospatial Analytics Market cover, and what was the market size in 2023?

In 2023, the China Geospatial Analytics Market size was estimated at USD 2.25 billion. The report covers the China Geospatial Analytics Market historical market size for years: 2019, 2020, 2021, 2022 and 2023. The report also forecasts the China Geospatial Analytics Market size for years: 2024, 2025, 2026, 2027, 2028 and 2029. Read More

China Geospatial Analytics Market Share

Statistics for the 2023 & 2024 China Geospatial Analytics market share, created by Mordor Intelligence™ Industry Reports. China Geospatial Analytics share report includes a market forecast to 2029 and historical overview. Get a sample of this industry share analysis as a free report PDF download.

Market Share of China Geospatial Analytics Industry

The China Geospatial Analytics market is semi-consolidated, with significant players in the market. The players in the market are updating the solution offerings to provide precise data and sustain the market.

In July 2023, a new round of iterative updating was recently completed for GeoQ Data traffic block data. Transportation Neighborhood (TN) is a means of refining the granularity of the map, which can help us more clearly and accurately grasp the distribution of urban population and customer groups. TN is a more natural method for splitting, and the results obtained in this way will be more precise than gridlike division.