Upgrade the geographical information foundation, and the commercial space industry needs to complete the last mile.

On May 9th, the National Geomatics Center of China released the "15th Five-Year Plan for the Development of the National Geomatics Center of China".

This is a planning document in the field of surveying, mapping, and geographic information, but its scope extends beyond the surveying and mapping industry.

In terms of content, the plan covers areas such as the national surveying and mapping datum, basic geographic information database, real - world 3D China, Tianditu (China's national geographic information public service platform), global geographic information resources, geographic information data elements, and AI geospatial analysis.

These areas are related to industrial links such as remote sensing satellites, aerial photography, UAV aerial surveying, Beidou high - precision positioning, aerospace data processing, and geographic information software.

What are the highlights of this plan? What opportunities does it mean for enterprises in the aerospace industry chain? Xingdong Wuji attempts to conduct an analysis from six aspects.

I. What does this plan really aim at?

Let's first look at the plan itself.

The National Geomatics Center of China mentioned in the document that during the "14th Five - Year Plan" period, the Geomatics Center had formed a relatively complete business pattern, including the surveying and mapping datum, the "One Network" of the national satellite navigation and positioning reference stations, land surveying and mapping, the construction of global geographic information resources, support services for natural resource surveys and monitoring, the application ecosystem of Tianditu, and the data application ecosystem of real - world 3D China.

During the "15th Five - Year Plan", the direction is clearer. The plan proposes:

It is necessary to focus on the development of the digital economy and artificial intelligence, concentrate on the service of geographic information data elements and security management, and create a full - process business system covering project planning and design, production organization and implementation, application services, and security management.

This shows that the national basic geographic information system is moving from traditional surveying and mapping result management to a more complete construction of the spatio - temporal data base.

For the aerospace industry chain, this change is crucial. Remote sensing satellites, aerial photography, UAV aerial surveying, Beidou high - precision positioning, geographic information software, and aerospace data platforms used to belong to different links.

In this plan, they all serve one thing: to provide data, benchmarks, platforms, algorithms, and application capabilities for the national - level spatio - temporal data base.

The nine key business directions proposed in the plan basically cover this chain. At the front end are the surveying and mapping datum and the location service ecosystem. In the middle are the basic surveying and mapping data resources, real - world 3D China, and the upgrade of the national basic geographic information database. At the back end are Tianditu, natural resource surveys and monitoring, the elementization of geographic information data, emergency surveying and mapping support, and the development of public - version surveying and mapping results.

In the past, many aerospace enterprises were used to proving themselves by their capabilities, such as the number of satellites they could launch, the resolution, the revisit period, and the algorithm recognition rate. After entering the national - level geographic information system, the evaluation criteria will be more complex.

Whether the data can be supplied stably in the long term, whether it can be connected to the unified coordinate framework, whether it can meet the database quality requirements, whether it can pass the security management, and whether it can support businesses such as natural resources, urban governance, and emergency surveying and mapping will all become new thresholds.

II. Satellites, aviation, and UAVs will benefit first from the data update demand

To upgrade the geographic information base, the first step is still data.

The plan mentions data update in many places. For example, continuously carry out the construction of basic surveying and mapping data resources to support the upgrade and transformation of the national basic geographic information database; promote the construction of real - world 3D China; provide support services for natural resource surveys and monitoring; and promote the construction of global geographic information resources.

These tasks in the industry chain first require a stable data source.

Remote sensing satellites are suitable for large - scale, periodic, and continuous surface observation, which can support the monitoring of land space, ecological environment, agriculture, water conservancy, disasters, and urban expansion.

Aerial photography is suitable for high - precision, large - scale, urban - level, and regional - level modeling. UAV aerial surveying is more flexible and suitable for high - frequency updates in local areas such as industrial parks, construction sites, mines, disaster sites, and along key projects.

In the upgrade of real - world 3D and the basic geographic information database, these three types of data sources will form a hierarchical collaboration. Satellites can cover large areas, aerial photography can create detailed base maps, and UAVs can supplement local changes. Data sources such as vehicle - borne measurement, ground laser scanning, and Internet of Things sensing will also supplement ground details.

This will change the competition indicators of aerospace data enterprises.

In the past, when talking about remote sensing capabilities, the industry often looked at resolution, swath width, revisit period, and constellation scale. When talking about UAV aerial surveying, people often looked at flight efficiency, modeling accuracy, and operation cost. After entering the national - level geographic information system, these are not enough.

Whether the data can be connected to the unified coordinate framework, whether the geometric accuracy is stable, whether the time phase is traceable, whether the format is standardized, whether it can be integrated with vectors, images, DEM, and 3D models, whether it can be continuously updated, and whether it can pass the security review will all become more practical requirements.

Therefore, we believe that opportunities will flow more to enterprises with engineering delivery capabilities.

Remote sensing satellite companies should not only provide raw images but also provide orthorectification, radiometric correction, change detection, thematic products, and API services.

UAV aerial surveying enterprises should not only complete a single flight collection but also ensure that the results meet surveying and mapping specifications and can enter the database and business platform.

3D modeling enterprises should not only pursue good - looking models but also deal with issues such as lightweighting, semanticization, update mechanisms, and system calls.

For enterprises in the aerospace industry chain, there are still opportunities in data collection, and the value of data processing will continue to increase. Image processing, point cloud processing, 3D reconstruction, change detection, feature classification, data fusion, and quality inspection will all become important links.

III. Beidou high - precision location service will become a greater underlying capability

This plan attaches great importance to the construction of the national surveying and mapping datum and the location service ecosystem, which is worth looking at separately.

The plan mentions that it is necessary to optimize the "One Network" of the national satellite navigation and positioning reference stations, improve the national surveying and mapping datum system, and build a new - generation CGCS2000 (2025) coordinate framework.

That is to say, for the digital world to function, there must first be a unified, stable, and accurate location benchmark.

If maps, remote sensing images, 3D models, urban components, low - altitude flight routes, natural resource map spots, and project boundaries use different coordinate systems, it will be difficult to integrate them later. Although the data seems to be in the same space, they may actually not align, overlap, or be calculated accurately.

The opportunities in the Beidou industry chain should be considered in this context.

As the "One Network" of the national satellite navigation and positioning reference stations continues to improve, the value of Beidou high - precision location service will further extend to the underlying capabilities. It not only provides positioning for vehicles, ships, people, and equipment but also provides unified location services for industries such as cities, transportation, agriculture, energy, low - altitude operations, and emergency response.

The reference station network, differential services, real - time positioning, and data processing platforms all have long - term operation value. Many industry customers do not care about the technical details behind it. They care about whether the positioning is stable, whether the error is controllable, whether the service is continuous, and whether problems can be quickly responded to.

In addition, the low - altitude economy will also be affected.

For the large - scale development of low - altitude flight, it cannot rely solely on the aircraft itself. Drone logistics, urban inspection, emergency rescue, low - altitude tourism, and agricultural and forestry plant protection all need to know where the aircraft is, what the surrounding environment is like, whether it can pass safely, and whether it enters sensitive areas.

This requires Beidou positioning, as well as the joint support of 3D geographic information, airspace data, communication coverage, meteorology, and supervision systems.

For Beidou enterprises, chips, modules, and terminals are still important in the next stage, but the greater value lies in service - orientation and platform - building.

IV. The elementization of data opens up the productization space for aerospace data

In this plan, there is an easily overlooked point, that is the elementization of geographic information data.

The plan proposes that it is necessary to continuously carry out the business of gathering and labeling geographic information data, explore the construction of a trustworthy geographic information data space, and conduct the registration of public data resource products and services.

For laypeople, these sentences are not as intuitive as satellites, Beidou, and real - world 3D. But for enterprises in the aerospace industry chain, it may be closer to the core of commercialization.

Aerospace data has always had a lot of potential, but there has always been a problem, that is the value of data does not mean that enterprises can generate continuous revenue.

Many aerospace data projects are still project - based. When customers have a demand, enterprises conduct a single collection, processing, and delivery. Once the project ends, the revenue also ends. It is not easy to reuse the data, call it across scenarios, turn it into a stable product, and charge continuously for services.

The elementization of data solves this problem.

It requires that data should not just be file packages, image maps, point cloud results, and project attachments, but should become resources that can be managed, labeled, registered, authorized, circulated, and called. Only when reaching this step can aerospace data have the opportunity to move from project delivery to product services.

There will be several types of opportunities here.

Data governance will become more important. Remote sensing images, aerial images, UAV data, 3D models, and vector data come from different sources, have different accuracies, times, and formats. If the coordinates, standards, and quality inspections cannot be unified, it will be difficult to enter a larger data system.

For AI to enter geospatial analysis, high - quality labeled data is indispensable. Stable sample systems are needed for cultivated land, forests, water bodies, roads, buildings, mines, shorelines, vehicles, ships, and disaster damage. Therefore, data labeling will also become a basic task.

In addition, the productization of data will also change the revenue structure. Raw images have value, but what customers really need are often the results. For example, the construction changes in a certain area, the risk points along a project, the restoration progress of a mine, and the 3D base of a city area. Processing data into thematic products, API interfaces, layer services, and industry reports is closer to sustainable revenue.

Geographic information data involves locations, boundaries, facilities, and spatial relationships, and some also involve sensitive areas and classified results. Hierarchical classification, permission control, desensitization processing, traceable calling, and a trustworthy data space will be the prerequisites for enterprises to enter core scenarios.

For commercial aerospace, this is especially important. Assets ultimately need to generate revenue. If aerospace data cannot be productized, it is easy to remain at the stage of capability demonstration. Only by entering the data element system, registering public data resource products and services, and being called in the daily business of government and enterprise customers can a more stable commercial closed - loop be formed.

V. AI geospatial agents push remote sensing interpretation into business systems

There is another notable mention in this plan - geospatial analysis agents.

Nowadays, all industries are talking about AI, and the geographic information industry is no exception. There are already many applications in remote sensing image recognition, change detection, automatic mapping, 3D modeling, and data labeling. But if AI is only understood as identifying roads, buildings, water bodies, and cultivated land in an image, it is too shallow.

Geospatial analysis agents are a layer of capabilities closer to business systems. They need to view images, call data, understand rules, and run processes.

For example, in natural resource supervision, the system needs to call historical images, the latest remote sensing data, planning boundaries, land - use map spots, and approval information to determine whether a change is abnormal.

In disaster emergency response, the system needs to overlay pre - disaster base maps, post - disaster images, terrain, water systems, roads, and the distribution of population and facilities to quickly determine the damage scope and rescue routes.

In low - altitude operations, the system needs to integrate 3D terrain, buildings, no - fly zones, communication coverage, and meteorological information to assist in route planning and risk identification.

This goes beyond the scope of traditional remote sensing interpretation.

In the past, remote sensing interpretation was more like extracting targets from images. What geospatial agents need to do is to put the targets back into the business scenario and answer specific questions. For example, whether there are changes in a piece of land, whether a road can be passed, where the risks are in an area, which facilities are affected by a disaster, and whether a low - altitude flight route is safe.

For enterprises in the aerospace industry chain, there will be new opportunities here.

Remote sensing satellite companies can extend from image supply to change monitoring, thematic analysis, and intelligent services.

Geographic information software companies can integrate spatial analysis capabilities into systems such as natural resources, urban governance, transportation, emergency response, and energy.

AI enterprises can train models more suitable for geospatial tasks around remote sensing images, 3D scenes, spatial relationships, and industry rules.

Low - altitude economy service providers can combine 3D maps, location services, route planning, and supervision capabilities to develop systems for operation management.

However, geospatial agents cannot be solved only by general large - scale models.

Spatial data has its own complexity. It involves coordinates, scales, projections, time phases, topological relationships, as well as feature classification, boundary accuracy, and data sources. If a model does not understand these basic rules, it is likely to give results that seem smooth but are actually unreliable. For natural resources, emergency response, transportation, and low - altitude supervision, the spatial analysis results need to be verifiable, and the generation speed should not be the only pursuit.

Therefore, the real opportunity for AI in the geographic information industry lies in connecting spatial data, industry rules, business processes, and manual review mechanisms.

Image recognition is just the first step. Then there are data scheduling, model reasoning, rule verification, result review, report generation, and business transfer.

VI. Opportunities do not equal dividends. Enterprises need to cross four thresholds

The release of opportunities in the plan does not mean that all aerospace enterprises will directly benefit.

The construction of the national basic geographic information system naturally has high - standard, high - specification, and high - security requirements. It requires data, as well as qualifications, standards, compliance, operation and maintenance, and service capabilities. For many enterprises, the real challenge may not be technical demonstration, but whether they can enter the system in the long term.

The first threshold is qualifications. Surveying, mapping, and geographic information are not ordinary data businesses. There are clear qualification and management requirements for links such as basic surveying and mapping, map services, real - world 3D, classified results, and location services. Even if an enterprise has remote sensing data, UAV collection capabilities, or AI algorithms, it does not mean that it can directly enter the core business chain.

The second threshold is standards. The national - level geographic information base is most afraid of data being developed independently. If the coordinates, accuracies, and formats of images, point clouds, 3D models, vector data, and positioning data are not unified, it will be difficult to enter the basic database and business platform later.

The third threshold is continuous update. Geographic information data is not something that can be completed once and for all. Cities are changing, projects are advancing, and cultivated land, forests, water bodies, mines, roads, and buildings are all changing. Real - world 3D, natural resource monitoring, low - altitude operations, and emergency support all require data to be updated at a certain frequency.

The fourth threshold is a commercial closed - loop. A common problem for aerospace data enterprises is that although they have completed many projects, their continuous revenue is unstable. The plan's mention of data elements, application ecosystems,