The initiation of the National Geographic Information System (NGIS) in the late 20th century aimed to establish a comprehensive framework for collecting, managing, utilizing, and distributing national spatial data. The introduction and development of remote sensing technology have particularly underscored the importance of spatial information in various fields such as land management, environmental monitoring, and disaster response. Advancements in aerial photography and satellite imagery have enabled remote sensing technology to be utilized as a tool to observe the status and changes in the land rapidly and accurately, thereby becoming an essential element of national spatial data (Chung and Kim, 2003; Kim et al., 2017). In the 1960s, remote sensing in Korea began with the production of maps using aerial photography. Additionally, since the 1990s, it has rapidly advanced to satellite-based remote sensing technology, significantly enhancing the efficiency of land management through its integration with the national spatial data policy (Ryoo et al., 2000). construction and utilization of spatial data infrastructure through several master plans. The 1st NGIS focused on establishing a Geographic Information System (GIS) foundation and constructing a spatial information database (Ministry of Land, Infrastructure and Transport, 1997; Ministry of Land, Infrastructure and Transport, 2005). The 2nd NGIS involved the integrated management of spatial data and the development of various application systems to support policy decision-making (Kwon and Kim, 2006; Kim et al., 2008). The 3rd NGIS aimed to establish a foundation for realizing ubiquitous land, targeting real-time and precise land management through high-resolution sensing data (Ministry of Land, Infrastructure and Transport, 2005; Park et al., 2009a). During this period, remote sensing technology played a vital role in data acquisition across various public sectors such as disaster management and environmental monitoring. This significantly enhanced the real-time analysis and visualization capabilities of spatial data. The 4th NGIS focused on expanding the utilization of spatial data through openness and sharing by establishing an open spatial data platform and making various data publicly available (Ministry of Land, Infrastructure and Transport, 2013; Kang and Hwang, 2014). The 5th NGIS responded to the advancement of smartphone and Information and Communications Technology (ICT) convergence technologies by integrating technologies such as the Internet of Things (IoT) with remote sensing data, thereby broadening the scope of spatial data utilization (Lee and Yoon, 2016). The 6th NGIS introduced digital twin (DT) technology in preparation for the Fourth Industrial Revolution, with remote sensing data playing a key role in replicating the physical state of the national land in virtual environments (Jang and Kim, 2023). Recently, the integration of advanced technologies such as DTs, big data, and Artificial Intelligence (AI) has further expanded the utilization scope of remote sensing data. These technologies enable real-time monitoring and simulation of the national land, enhancing the accuracy and efficiency of policy decision-making (Nativi et al., 2021).

This paper comprehensively examines the national spatial data policy and remote sensing technology, analyzing how remote sensing technology has been introduced and utilized at each stage of the NGIS. Additionally, by exploring the future prospects of remote sensing and spatial data, the study aims to propose policy implications in response to forthcoming technological advancements in satellite imagery technology and the development of DT applications. Through this analysis, the paper explores the contributions of remote sensing technology to the construction of DTs and land management and seeks to identify directions for future policy support.

2.1. Introduction of Remote Sensing in the Early NGIS

Remote sensing technology began with map production using aerial photography in the 1960s. Prior to this, after liberation in 1945, photogrammetry technology was introduced under the supervision of the U.S. Far East Command to facilitate national land reconstruction, initiating the production of topographic maps and land surveys. Following an aerial photogrammetry project agreement with the Netherlands in 1966, the first national basic topographic maps were produced domestically starting in 1967 (National Geographic Information Institute, 2008). This shift from terrain surveying-based map production methods to aerial photogrammetric techniques significantly improved accuracy, enabling these maps to be utilized as essential data for land development. In 1974, after the establishment of the National Geography Institute (currently the National Geographic Information Institute, NGII), the production of 1:5,000 topographic maps using aerial photogrammetry commenced for the first time (Table 1). During this period, the need for improved spatial information management emerged, leading to the systematic establishment of spatial information at the national level, including land use maps and image maps based on satellite imagery (National Geographic Information Institute, 2008).

Table 1 . Status of 1:5,000 topographical map production.

Year	1975	1976	1977	1978	1979	1980	1981	1982	1983	1984	1985	1986	1987
Number of map sheet	276	704	634	703	849	981	1,036	990	1,053	950	966	900	900
Year	1988	1989	1990	1991	1992	1993	1994	1995	1996	1997	1998	1999	Total
Number of map sheet	914	800	843	750	573	421	284	152	136	107	73	253	16,248

In the 1990s, satellite-based remote sensing technology began to be actively utilized. In particular, the launch of the KOMPSAT-1 satellite in 1999 marked the beginning of high-resolution spatial data collection using the nation’s domestic satellite system (Ryoo et al., 2000). Additionally, the application of KOMPSAT-1 payloads by user groups has significantly enhanced the ability to collect and analyze spatial data in map production and land management such as the creation of three-dimensional (3D) topographic maps and land use analysis. This advancement served as the starting point for integrating remote sensing technology into the national spatial data policy (Table 2).

Table 2 . Application of KOMPSAT-1 payloads by user groups (Ryoo et al., 2000).

Payload	Basic Requirements of Users
EOC	Cartography, Topographic Analysis, Land Management, Coastal Management, Disaster Management, Environment, Agriculture, Water Resources Management, Land Use Survey, Geology, S/W Development, Information on North Korea, etc.
OSMI	Environment, Coastal/Harbor, Ocean Currents/Temperature, Marine Life, Resources, Meteorology, S/W Development, etc.
SPS	Ionosphere Observation, Space Radiation Research

EOC: Electro Optical Camera, OSMI: Ocean Scanning Multispectral Imager, SPS: Space Physical Sensor..

The 1st NGIS, launched in 1995, was a government-led effort aimed at establishing a national GIS foundation and constructing spatial data infrastructure, including national topographic maps and cadastral maps, to enhance the efficiency of land management (Ministry of Land, Infrastructure and Transport, 1997; Ministry of Land, Infrastructure and Transport, 2005). During the five-year implementation period, the objective was to sequentially digitize topographic maps, thematic maps (land use maps, forest maps, geological maps, soil maps), cadastral maps, and underground facility maps, thereby establishing a foundational national spatial information database (DB) and its standards (Han, 1997). During the 1st NGIS phase, remote sensing technology based on aerial photography was employed as a key tool for map production. This period focused on creating nationwide 1:5,000 and 1:25,000 topographic maps, generating initial demand for GIS applications. NGIS not only emphasized the construction of spatial data at the national level but also initiated the establishment of institutional frameworks, including standards and spatial data security management regulations, to create a foundation for the effective utilization of spatial data in both public and private sectors (Ministry of Land, Infrastructure and Transport, 2010). However, the NGIS project encountered certain limitations during its initial phase. Foundational data required long-term archiving, and the development of systems to utilize this data necessitated significant investment. Additionally, the 1st NGIS project involved only a few government departments and local governments rather than being a cross-departmental initiative, which posed challenges in comprehensively advancing NGIS (Han, 1997).

2.2. Technological Advancements and NGIS

From 2001 to 2005, the 2nd NGIS focused on expanding GIS utilization. A key feature of this plan was the integrated management of spatial data and the establishment of national-level application systems to support policy decision-making (Kwon and Kim, 2006; Kim et al., 2008). Importantly, satellite and aerial imagery were defined as “fundamental spatial data” within the regulation¹ of the 「Framework Act on National Spatial Data Infrastructure」. A comprehensive promotion strategy was established, encompassing policies, technologies, institutional frameworks, and budgets for constructing and providing national spatial data (Ministry of Land, Infrastructure and Transport, 2002). During this period, a system for collecting spatial data across the entire national land was established, utilizing both aerial photographs and KOMPSAT data. This led to the government’s production of nationwide image maps. Meanwhile, the private sector began proposing methods for producing image maps through rapid and cost-effective aerial photography using unmanned aerial vehicles (UAVs) (Yoo et al., 2006). Specifically, in the public sector, efforts were focused on developing sector-specific utilization frameworks for NGIS, building spatial data systems for facility management, transportation planning, hydrological modeling, and other purposes. This marked the full-scale introduction of remote sensing technology for nationwide land management (Kim and Kim, 2001; Yang et al., 2003). For instance, various thematic maps, such as land cover classification, precision soil maps, forest thematic maps, and marine spatial information, were produced. These maps, along with GIS system integration techniques, supported reliable decision-making in central government agencies, local governments, and public sectors (Ministry of Land, Infrastructure and Transport, 2002; Yang et al., 2002; Jung et al., 2005; Jang, 2005; Lee et al., 2003).

The 3rd NGIS (2006–2010) concentrated on upgrading administrative services systems based on spatial information to efficiently achieve a ubiquitous national land, aiming for real-time and precise land management through the use of high-resolution sensing data (Ministry of Land, Infrastructure and Transport, 2005; Park et al., 2009a; Ministry of Land, Infrastructure and Transport, 2010). For satellite imagery, IKONOS images, which offered higher resolution than the previously utilized KOMPSAT-1 images (6.6 m @ pan), along with the use of the KOMPSAT-2 satellite launched in 2006, were employed to produce 1m-level high-resolution images in land management, urban planning, and environmental monitoring administrative services (Seo et al., 2013).

To develop the core spatial information technologies necessary for achieving the goal of ubiquitous national land under the 3rd NGIS, the Korean Land Spatialization Program (KLSP) was initiated in 2006. As the largest R&D project in the spatial information sector, the KLSP had a budget of approximately 142 billion KRW and spanned until 2012. The project was divided into two phases: the first phase (2006–2009) focused on research and technology development, while the second phase (2009–2012) aimed at commercializing the developed technologies through the establishment of testbeds and conducting experiments (Park et al., 2009a; Park et al., 2009b; Bae et al., 2012). This project comprises five core research projects. Notably, the second core research project, titled ‘Land Monitoring’, advanced remote sensing acquisition, analysis, and detection technologies. This enhancement improved the capability to analyze and visualize spatial data in real time. Specifically, to develop real-time aerial monitoring technology, remote sensing data was acquired using UAVs, and real-time aerial data communication and processing technologies were developed on the ground station. Furthermore, by developing and integrating mobile monitoring with Closed Circuit Television (CCTV) integrated monitoring technologies, the project provided immediate information on land changes—including disasters, change detection, and environmental conditions—across the entire nation (Park et al., 2009b).

The 3rd NGIS also completed the production of fundamental spatial data and began to establish not only standards for existing data but also future-oriented national standardization, including data quality and procedural standards to expand the utilization and enhance the compatibility of spatial data. Additionally, GIS utilization infrastructure for local governments and industries was initiated (Chung and Choi, 2006). Through these efforts, the utilization of spatial data expanded in both public and private sectors. Specifically, remote sensing technology and spatial data played crucial roles in establishing key infrastructures such as 3D spatial information, land use information, and forest spatial information that were commonly required by local governments (Ministry of Land, Infrastructure and Transport, 2005).

Ultimately, advancements in data production, application system development, standards, and distribution structures significantly contributed to real-time and precise land management and policy decision-making through the 1st, 2nd, and 3rd phases of NGIS (Table 3).

Table 3 . The tasks and achievements of the 1st, 2nd, and 3rd master plans for NGIS (Ministry of Land, Infrastructure and Transport, 2010).

Division	The 1st Master Plan for NGIS (1995–2000)	The 2nd Master Plan for NGIS (2001–2005)	The 3rd Master Plan for NGIS (2006–2010)
Geospatial Information Construction	Computerization of topographic and cadastral maps. Construction of thematic maps(land use map, and etc.).	Construction of fundamental spatial data (roads, rivers, buildings, etc.).	Construction of national/maritime base maps, national control points, spatial images, etc..
Application System Construction	Construction of underground facility map.	Promotion of GIS utilization systems development for land use, underground, and marine areas, etc..	Construction of application systems including 3D national spatial information, UPIS, KOPSS, and building integration.
Standardization	Establishment of standards required for the construction of national basic maps, thematic maps, underground facility maps, etc.. Establishment of standards for the exchange and distribution of spatial data.	Establishment of standards for 1 fundamental spatial data, 13 spatial data, and 4 application systems.	Standardization of geographic information and establishment of a national GIS standard system.
Technology Development	Mapping technology, DB Tool, GIS S/W Technology development.	3D GIS, high-precision satellite image processing, etc..	Development of core technologies through the Intelligent Land Information Technology Innovation Project.
Research	Conducting research for the implementation of the NGIS Project.	Implementation of national GIS issues and long-term policy support project.	Conducting research for national GIS issues until 2007 and projects for policy implementation in 2008.

2.3. Digital Convergence and Expansion of Application of Spatial Data

In the 4th national spatial data policy master plan (2011–2013, formerly NGIS), efforts were made to establish a platform system for utilizing and supporting national spatial data, aimed at integrating and providing services so that anyone could easily access and use spatial information. Therefore, a spatial data open platform called ‘V-World²’ was established, releasing 114,387 datasets (consisting of 47 types of spatial data) online (Ministry of Land, Infrastructure and Transport, 2013; Kang and Hwang, 2014). However, providers faced challenges in maintaining the timeliness and consistency of the spatial data. On the other hand, users encountered difficulties in accessing and obtaining raw data, which hindered the platform’s ability to attract a wide range of users (Ministry of Land, Infrastructure and Transport, 2013).

The master plan for the national spatial data policy is a legally mandated plan established every five years in accordance with the law³. However, the 5th master plan (2013–2017) was formulated in 2013 to proactively address the rapid development of smartphone and ICT convergence technologies, as well as the changing policy environment brought by the new administration (Government 3.0). During this period, technologies such as big data and the IoT were integrated with remote sensing data analysis, significantly enhancing the processing of large volumes of data and improving precision in analysis. For example, in the application of u-City, remote sensing was used to create 3D urban models, enabling real-time monitoring of traffic flow, air quality, and energy consumption. These integrated models have been widely proposed, contributing to more detailed administration (Yeon and Lee, 2008; Lee and Yoon, 2016).

Another feature of the 5th master plan was the integration of public safety policies with spatial data technology. This included the establishment of a smart city operation framework and the implementation of indoor spatial information to support a safe urban management system. Additionally, to prepare resilient national land in preparation for natural disasters, flood risk maps, land use systems, and landslide risk maps were proactively developed (Ministry of Land, Infrastructure and Transport, 2013). Remote sensing technology, in particular, has played a critical role in disaster management. Since the 2000s, numerous studies have used various remote sensing techniques, such as optical imagery, thermal imaging, and synthetic aperture radar (SAR), to conduct vulnerability assessments or damage analyses and mapping before and after specific natural disasters, including floods, wildfires, earthquakes, and volcanic eruptions (Hakim and Lee, 2020). In Korea, the National Disaster Management Research Institute under the Ministry of the Interior and Safety launched an R&D project for developing a national disaster safety monitoring system using satellites to build a disaster prevention and response system based on remote sensing. This project aimed to establish a system tailored to monitor and manage disasters in Korea. Additionally, satellite data reception and network systems were developed to respond in a timely manner to disaster situations. These systems utilized around ten different sources, including Landsat-8 and MODIS, to monitor national land features such as wildfires, urban heat islands, and changes in water surface areas (Kim et al., 2019). This monitoring information has improved the speed and accuracy of government decision-making during disaster management and response processes. Furthermore, the need for the development of dedicated spatial data satellites to respond to disasters, climate change, and environmental shifts was recognized, leading to the development of the National Land Satellite-1, part of the Compact Advanced Satellites (CAS500) series, which began in 2015.

2.4. Integration of Digital Twin and Remote Sensing Technologies

The 6th national spatial data policy master plan (2018–2022) formally introduced DT technology to establish the policy direction in preparation for the Fourth Industrial Revolution (Ministry of Land, Infrastructure and Transport, 2018). Remote sensing data were instrumental not only in representing the physical state of the national land but also in reproducing it within virtual environments (Jang and Kim, 2023). Furthermore, in response to the necessity of implementing public policies based on spatial big data, the government led the provision of platforms capable of collecting and analyzing spatial big data, such as the K-Geo Platform⁴, Spatial Big Data Platform⁵, Geospatial Information Platform⁶, and Statistical Geographic Information Service⁷. This enabled comprehensive analysis and research by integrating spatial data with administrative, demographic, economic, transportation, and public opinion data (Ahn et al., 2013; Choi et al., 2019; Lee and Yoon, 2020; Jang and Lee, 2022). Specifically, the Ministry of Land, Infrastructure and Transport (MOLIT) is developing technologies for absolute or relative positional corrections of heterogeneous satellite data to convert various satellite images and ancillary information into Satellite Image Information Big Data for satellite-based national land management. Since 2022, the ministry has been developing application technologies that can be pilot-applied to urban planning, water resources, forest resources, infrastructure, and industrial management using the Satellite Image Information Big Data (Kim, 2023).

The ongoing 7th national spatial data master plan, as shown in Fig. 1, emphasizes maximizing the value of spatial data utilization and presents the vision of realizing a ‘Digital Twin KOREA with interconnected data’ (Ministry of Land, Infrastructure and Transport, 2023). As part of this strategy, initiatives are being undertaken to produce the latest high-precision spatial data, establish a DT based on national spatial data, and activate location-based convergent industries. High-resolution aerial photographs and satellite images are being collected to develop DTs based on national spatial data, enabling time-series monitoring of national land and the production of up-to-date spatial information (Ministry of Land, Infrastructure and Transport, 2023).

Figure 1. Status of national spatial information policy implementation (Ministry of Land, Infrastructure and Transport, 2024a).

The advancement of real-time data acquisition, 3D modeling, and visualization technologies has made the construction of spatial data-based DTs possible (Bang, 2020). Specifically, the MOLIT has established a system for collecting and utilizing National Land Satellite imagery, producing the latest high-resolution image maps of the entire national land.

2.4.1. National Spatial Data-based Digital Twin System

A DT is a technology that replicates the real world’s exact appearance, attributes, conditions, and situations in a virtual space. Spatial data, including remote sensing data, is essential in constructing and maintaining this virtual environment (Nativi et al., 2021). Currently, spatial information is integrated with data collected from various sensors and developed into DTs, serving as core infrastructure in emerging industries such as smart cities and urban air mobility (Ministry of Land, Infrastructure and Transport, 2024b). Through this integration, it becomes possible to monitor the state of national land in real time and establish an environment where various scenarios for decision-making can be predicted and addressed through simulations (Fig. 2).

Figure 2. Concept of national spatial data-based DT (Ministry of Land, Infrastructure and Transport, 2023).

In response, the MOLIT has developed a framework for the National Spatial Data-based Digital Twin (NDT). It has defined the data components of the object-based DT, which is the smallest unit within this framework. In this context, an object refers to spatial entities existing both above and below ground, such as buildings, roads, and rivers. The components comprise 3D spatial information (e.g., 3D terrain data, 3D models), IoT sensing data (e.g., weather, dust levels), and social sensing data (e.g., pedestrian flow, card transactions). Additionally, a common identification code is being designed to connect and integrate the components. This will establish a data flow that allows 3D models and sensing data produced by various public and private entities to be connected to city- and national-level DT (Fig. 3). Furthermore, individual object DTs are being integrated with city and national-level DTs, creating a virtuous cycle where changes in the attributes or states of object DTs or city-level DTs automatically update the corresponding objects in the federated NDT.

Figure 3. Federated NDT (Ministry of Land, Infrastructure and Transport, 2023).

Within the NDT framework, the NGII is working on rapidly updating high-precision National Base Maps with object-level change information of the land. Additionally, the 3D spatial information component of the NDT is being updated annually, with improvements made to ensure data quality. Furthermore, NGII aims to complete the nationwide construction of High Definition Road Maps by 2030 to support autonomous driving. Indoor Spatial Information for public facilities is also being continuously produced to enhance public safety, welfare, and disaster management.

2.4.2. The Role of National Land Satellites in the Digital Twin

The National Land Satellite observes at high resolutions (PAN: 0.5 m, MS: 2 m) to fulfill missions addressing public sector demands such as land and resource management, disaster response, and the production of national spatial data. From 2021 to 2024, the National Land Satellite produced approximately 6,119 orthoimages of the Korean Peninsula, covering about 97%of the entire region (National Geographic Information Institute, 2024). To satisfy diverse user demands and consider convenience and usability, the outputs of the National Land Satellite currently include orthoimages, analysis ready data (ARD), mosaic images, image maps, and disaster-related spatial information. Among these, mosaic products are generated by merging satellite images according to administrative districts or specific areas of interest upon request (National Geographic Information Institute, 2023). By merging multiple individual satellite images into a single mosaic for large areas, administrative and public agencies can easily obtain up-to-date imagery for their respective areas (Fig. 4). This is expected to increase the use of satellite imagery as foundational data for urban planning and infrastructure development in DT applications.

Figure 4. A mosaic product of national land satellite images (Seoul).

In order to build a DT based on national spatial data, a continuous archive of image information is being produced through the National Land Satellite. Efforts are actively underway to construct spatial data to areas where aerial photography is not feasible, such as North Korea and border regions. Additionally, in preparation for the end of the mission of the National Land Satellite-1, the development of the next-generation satellites is underway to ensure seamless mission continuity. Therefore, the National Land Satellite is expected to enhance the efficiency of national land management by providing the latest high-resolution imagery that reflects the current state of the land in the DT as part of the 7th national spatial data policy master plan.

3.1. Future Prospects of Remote Sensing Data

Spatial data, which began with paper maps, has evolved through digital maps and is now advancing toward intelligent spatial information (Geo-AI) through the integration of ICT technologies such as AI, IoT, cloud, big data, and mobile (AICBM). This evolution is expected to significantly influence various fields, including urban development, transportation, welfare, and the environment (Korea Agency for Infrastructure Technology Advancement, 2021). In future societies, spatial information will be based on the virtualization of land, which rapidly and accurately represents the real world. This information will be combined with heterogeneous data to enhance spatial awareness and analysis, thereby actively contributing to optimal decision-making (Loukili et al., 2022). For the efficient use of intelligent spatial information, high-quality spatial data must be produced in a timely manner to meet user needs. To date, spatial information has been produced periodically at the national level, but it has limitations in reflecting the rapidly changing landscape (Korea Agency for Infrastructure Technology Advancement, 2021). In other words, the appropriate form of spatial data is needed at the right time, and satellite imagery can serve as a key source of this data. With active investment in satellite development and the reduction in space development costs, the use of satellite imagery is increasing worldwide. Korea has also been developing various satellites, starting with the KOMPSAT-1, followed by the development of medium-sized satellites (i.e., CAS500 series) and microsatellites.

As satellite development increases, the utilization of satellite imagery is meeting the “3Vs” of big data, as defined in data science: Volume, Velocity, and Variety (Park et al., 2023). In the context of satellite imagery, “Volume” refers to the increase in available satellite imagery as satellite development expands. In the past, space technology was primarily developed by government-led or state-led efforts for security and military purposes due to high development risks and substantial investments. However, major advanced countries are now promoting the development of space technology through public-private partnerships to enhance the competitiveness of the space industry (Ministry of Science and ICT, 2023). Most of the space industry’s focus is on satellite development, resulting in a significant increase in the number of satellite launches—from 500 in 2018 to approximately 2,900 in 2023. The proportion of small satellites (including micro and nano) has risen from 61% in 2013 to 97% in 2023, and over 3,000 satellites are expected to be launched annually by 2031 (Min, 2024; Euroconsult, 2023).

In Korea, substantial investment is also being directed toward satellite development fields, including the development of satellite payload technology, satellite bus standardization technology, and small satellite manufacturing (Ministry of Science and ICT, 2023). Starting with the development of the CAS500 in 2015, Korea is currently developing various satellites, including a microsatellite constellation system (EO and SAR). As private sector investment in medium and small satellites increases, it is expected that, in the near future, imagery from multiple satellites will be observed and analyzed in near real-time, much like CCTV. Thus, to effectively integrate the vast volumes of data captured from various satellites into the spatial information domain in a timely manner, the development of advanced technologies for rapid data acquisition and analysis is crucial.

From this perspective, “Velocity” refers to the rapid reception and processing of captured satellite imagery. The amount of information captured by Earth observation satellites in a single day amounts to thousands of terabytes (TB), with approximately tens of gigabytes (GB) being accumulated in space every second. As satellite development accelerates, the volume of data stored in space is expected to increase even further. Consequently, various research is being conducted to enhance communication technologies, improve satellite imagery processing speeds, and develop cloud-based ground station services, with new service models continually emerging (Lee, 2022).

Regarding communications, the current use of K-band electromagnetic waves allows for a transmission speed of around 5 Gbps, which is insufficient for transmitting large amounts of satellite data in a short period (Kumar et al., 2023). By using laser-based optical communication systems instead of electromagnetic waves, Tbps-level data transmission becomes possible (Kang, 2023a). For instance, NASA’s TeraByte Infrared Delivery (TBIRD) CubeSat, launched in 2022, achieved a maximum transmission speed of 200 Gbps, sending 1.4 TB of data to the ground station in just five minutes (Riesing et al., 2023). If the challenges related to communication between transmission devices and weather conditions can be overcome, satellite imagery could be transmitted to the ground even more quickly.

In the past, ground stations were physical facilities dedicated to individual satellites. However, with the advancement of microsatellite constellations, the demand for cloud-based ground station services has been increasingly expanding (Cho and Jo, 2022). A representative example is Amazon’s AWS Ground Station as a Service, which has been in operation since 2019. This service allows for the rapid transmission of satellite data using Amazon’s global network and ground station antennas, regardless of time (Hughes et al., 2021). As the number of satellites increases, cloud-based ground station services are expected to become even more prevalent.

Moreover, the integration of AI in onboard processors enables satellites to conduct real-time image analysis, substantially reducing the processing time for satellite imagery (Kim et al., 2022). For instance, Phi-Sat-1, developed by Intel and launched in September 2022, successfully carried out a test mission utilizing an onboard convolutional neural network (CNN) algorithm to detect cloud coverage in captured images. The satellite autonomously filtered out data with excessive cloud cover, avoiding transmission to ground stations. Similarly, China’s Beijing-3 satellite, equipped with a high-performance processor, captured a 3,800 km2 area of San Francisco and automatically identified objects within 42 seconds (Kwon et al., 2022). AI-based onboard processors are anticipated to become a pivotal technology for enhancing the efficiency of satellite data management and collection in the future.

In the field of satellite imagery utilization, “Variety” refers to the generation of diverse products and services derived from satellite imagery. In the past, satellite imagery was primarily used for basic interpretation and object extraction using simple image classification techniques. However, with ongoing technological advancements, it is expected that tailored outputs for various fields and purposes, leveraging technologies such as deep learning, will become increasingly accessible. Currently, the NGII is preparing to offer not only high-resolution satellite imagery but also mosaic images, image maps, land classification data, and change detection information, all tailored to user requirements. Furthermore, in the future, large language models (LLMs) are anticipated to possess the capability to sift through extensive satellite imagery datasets, efficiently identifying information aligned with user requirements and enabling users to conduct data analysis in their preferred formats. Many companies specializing in image analysis are already developing conversational AI systems designed to facilitate the easy search and analysis of satellite data for users (Kaylin and Rahul, 2023).

To date, identifying appropriate data within the vast volumes of satellite imagery has been challenging, and the time needed for ground transmission and processing has made it difficult to deliver the required data promptly. Furthermore, analyzing satellite imagery over extensive areas has proven to be a complex task. Increasing the number of satellites without corresponding advancements in related technologies may actually complicate the utilization of satellite imagery even further. However, as technologies for collecting, analyzing, and utilizing satellite imagery continue to advance, users will be able to more easily locate the imagery they require and access appropriate solutions. Ultimately, this will increase the future value of satellite imagery within the spatial information application. In the near future, satellite imagery is expected to be seamlessly integrated with other spatial data, enabling its application across a broad range of policies, while also allowing the public to more easily access and utilize it.

3.2. Policy Support and Development Directions in Spatial Information

The Framework Act on National Spatial Data Infrastructure defines spatial data as “the locational data of natural or artificial objects existing in space, including the space above ground, space underground, space above water and space underwater, and the data necessary for spatial identification and decision-making related thereto”. The key concept here is decision-making. Historically, spatial information was primarily used for spatial awareness of natural and man-made features. With the advancement of technologies such as AICBM, spatial information has transitioned from being merely about spatial awareness to becoming Geo-AI, a tool for informed decision-making. This process involves leveraging vast amounts of data collected from the physical environment to create virtual environments that closely mirror reality. These virtual models enable comprehensive analysis and predictions, ultimately leading to the development of optimal solutions for real-world challenges (Ryu, 2019).

The government acknowledges spatial information as a key instrument applicable to a wide range of sectors, such as transportation, meteorology, environmental management, crime prevention, public health, and disaster response. Future policy support and development directions in spatial information are expected to shift toward cyber-physical systems (CPS), which enable the analysis and control of the real world (Kim and Jeon, 2021). To further develop spatial information, it is essential to conduct research on technology development concerning the construction and utilization of spatial data and to establish a solid policy framework. The key future tasks can be summarized as follows: First, innovative technological advancements in the construction and updating of high-quality spatial information are essential. Among the various elements of spatial information, one of the most crucial is high-precision indoor positioning technology. In the past, spatial information for external environments, such as aerial photography and digital elevation models, was considered vital. However, with the rise in indoor activities within high-rise buildings, complex malls, and apartments, precise indoor positioning technology has emerged as a critical component for DTs and the metaverse (Ministry of Land, Infrastructure and Transport, 2023). Various indoor positioning methods using Bluetooth, WiFi, and other technologies, in addition to traditional GNSS-based methods, have been proposed (Roh and Kim, 2019). However, these technologies currently lack the centimeter-level accuracy required for DTs, highlighting the need for the development of high-precision positioning technologies (Qi et al., 2024).

Furthermore, advancements in technology for constructing and updating 3D spatial information, a fundamental component of DTs, are required. DTs, which virtualize the real world and connect it with the virtual world, inherently depend on 3D data. Spatial information for DTs is transitioning from 2D to 3D. However, the construction of high-quality 3D models for buildings, roads, infrastructure, and indoor structures remains both time-consuming and expensive (Jang and Joo, 2020). Therefore, policies must focus on advancing efficient 3D spatial information construction technologies, such as hybrid sensors that combine aerial photography and Light Detection and Ranging (LiDAR) scanning, as well as automated object data generation systems. Additionally, a 3D grid system must be implemented to facilitate the use and management of 3D spatial information. This system will serve as a framework for managing all spatial dimensions—ground, underground, air, and ocean—in a unified 3D format (Yoo et al., 2017). Thereby, this system would become the fundamental framework for future spatial information, integrating various types of data such as meteorological, environmental, administrative, and statistical information.

Secondly, a robust foundation for utilizing spatial information must be established. To maximize the use of government-produced spatial data, there is a need for a platform capable of integrating, analyzing, and utilizing diverse forms of spatial information. Currently, quality constraints hinder the integration of various spatial data, making it challenging to develop innovative services in the private sector and restricting policy support in the public sector (Ministry of Land, Infrastructure and Transport, 2023). For spatial information to be easily accessible to all users, it is essential to develop standards and technologies that allow for the seamless integration of heterogeneous data (Yoon and Kim, 2021). In the past, the government was the primary producer of spatial information. However, today, a wide range of spatial data is available, including vehicle data, social media data, mobile phone base station information, and smartphone photos (Kang, 2023b). Therefore, if standardized methods for data conversion and compatibility are established, enabling the integration and utilization of data produced by private companies and individuals, the scope of usable spatial information will greatly expand.

Moreover, to facilitate the utilization of diverse spatial information, a comprehensive spatial information integration platform must be developed to manage, open, and share spatial data, foster new business models, and generate high-value-added analytical outcomes (Kim et al., 2014). In the past, only public sector spatial information was shared and managed. However, moving forward, both public and private sectors will construct and share spatial information. With large volumes of spatial data being collected and provided on a unified platform, users may need to invest considerable time and effort in searching for and analyzing the specific spatial information they require. Thus, a spatial information integration platform should be developed to enable users to efficiently extract and process only the data relevant to their needs. To accomplish this, an intelligent spatial information platform incorporating Geo-AI and LLMs should be developed. Leveraging the natural language processing capabilities of LLMs, users would be able to locate specific spatial data from diverse datasets. With AI-driven tools for visualization and analysis, users could then utilize spatial information tailored to their objectives (Li and Ning, 2023).

This paper has comprehensively explored the development of remote sensing technology within Korea’s national spatial data policy and its influence on policy-making processes. From its early reliance on aerial photography in the 1960s to the contemporary integration of high-resolution satellite data, remote sensing technology has continuously advanced to address the evolving needs of efficient land management, environmental monitoring, and disaster response. The study underscored the pivotal role of remote sensing in enhancing decision-making processes across diverse public sectors.

As an integral component of the national spatial data policy, remote sensing has significantly influenced urban planning, infrastructure management, environmental protection, and disaster risk reduction. The incorporation of advanced technologies, such as digital twins, has further expanded the applications of remote sensing by enabling real-time monitoring, precise data analysis, and predictive modeling. Additionally, the National Land Satellite system has been instrumental in providing accurate and timely spatial data for both public and private sectors.

Future research should prioritize the development of robust methodologies for integrating heterogeneous data sources, enhancing real-time processing capabilities through artificial intelligence and cloud-based ground station services, and improving the accuracy and scalability of 3D spatial modeling, particularly in the context of DT applications. Continued innovation in technology and sustained policy support will be crucial in maximizing the potential of remote sensing as an indispensable tool for decision-makers in the coming years.

None.

No potential conflict of interest relevant to this article was reported.

Enforcement Decree of 『Framework Act on National Spatial Data Infrastructure』

V-World, https://www.vworld.kr/

National Spatial Data Infrastructure Act

https://kgeop.go.kr/, K-Geo Platform by MOLIT

https://geobigdata.go.kr/portal/, Spatial Bigdata Platform by MOLIT

https://map.ngii.go.kr/, Geospatial Information Platform by NGII

https://sgis.kostat.go.kr/, Statistical Geographic Information Service by Statistics Korea