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National Spatial Data Policy and Remote Sensing: Technological Advancements, Policy Implications, and Future Prospects
... Remote sensing technologies are essential elements for converting raw measurements into spatial data and for interpreting spatial data into information. Lee et al. (2024b) provided a comprehensive review of the evolution of Korea's national spatial data policy and remote sensing technologies. They examined how remote sensing technologies in Korea had been influenced and utilized throughout the first to the seventh master plans of the national spatial data policy of the Korean government . ...
... Highresolution images from the CAS500-1 played a critical role in enhancing the availability and timeliness of national spatial data. Lee et al. (2024b) emphasized the current role of national land satellites in the establishment of national digital twin based on spatial data and their future roles in supporting future national spatial data policy. Hong et al. (2024) summarized remote sensing technology developed in the agricultural sector. ...
High-precision indoor positioning technology is regarded as one of the core components of artificial intelligence (AI) and Internet of Things (IoT) applications. Over the past decades, society has observed a burgeoning demand for indoor location-based services (iLBSs). Concurrently, ongoing technological innovations have been instrumental in establishing more accurate, particularly meter-level indoor positioning systems. In scenarios where the penetration of satellite signals indoors proves problematic, research efforts focused on high-precision intelligent indoor positioning technology have seen a substantial increase. Consequently, a stable assortment of location sources and their respective positioning methods have emerged, characterizing modern technological resilience. This academic composition serves to illuminate the current status of meter-level indoor positioning technologies. An in-depth overview is provided in this paper, segmenting these technologies into distinct types based on specific positioning principles such as geometric relationships, fingerprint matching, incremental estimation, and quantum navigation. The purpose and principles underlying each method are elucidated, followed by a rigorous examination and analysis of their respective technological strides. Subsequently, we encapsulate the unique attributes and strengths of high-precision indoor positioning technology in a concise summary. This thorough investigation aspires to be a catalyst in the progression and refinement of indoor positioning technologies. Lastly, we broach prospective trends, including diversification, intelligence, and popularization, and we speculate on a bright future ripe with opportunities for these technological innovations.
Large Language Models (LLMs), such as ChatGPT, demonstrate a strong understanding of human natural language and have been explored and applied in various fields, including reasoning, creative writing, code generation, translation, and information retrieval. By adopting LLM as the reasoning core, we introduce Autonomous GIS as an AI-powered geographic information system (GIS) that leverages the LLM's general abilities in natural language understanding, reasoning, and coding for addressing spatial problems with automatic spatial data collection, analysis, and visualization. We envision that autonomous GIS will need to achieve five autonomous goals: self-generating, self-organizing, self-verifying, self-executing, and self-growing. We developed a prototype system called LLM-Geo using the GPT-4 API, demonstrating what an autonomous GIS looks like and how it delivers expected results without human intervention using three case studies. For all case studies, LLM-Geo returned accurate results, including aggregated numbers, graphs, and maps.. Although still in its infancy and lacking several important modules such as logging and code testing, LLM-Geo demonstrates a potential path toward the next-generation AI-powered GIS. We advocate for the GIScience community to devote more efforts to the research and development of autonomous GIS, making spatial analysis easier, faster, and more accessible to a broader audience.
With advances in NanoSat (CubeSat) and high-resolution sensors, the amount of raw data to be analyzed by human supervisors has been explosively increasing for satellite image analysis. To reduce the raw data, the satellite onboard AI processing with low-power COTS (Commercial, Off-The-Shelf) HW has emerged from a real satellite mission. It filters the useless data (e.g. cloudy images) that is worthless to supervisors, achieving efficient satellite-ground station communication. In the application for complex object recognition, however, additional explanation is required for the reliability of the AI prediction due to its low performance. Although various eXplainable AI (XAI) methods for providing human-interpretable explanation have been studied, the pyramid architecture in a deep network leads to the background bias problem which visual explanation only focuses on the background context around the object. Missing the small objects in a tiny region leads to poor explainability although the AI model corrects the object class. To resolve the problems, we propose a novel federated onboard-ground station (FOGS) computing with Cascading Pyramid Attention Network (CPANet) for reliable onboard XAI in object recognition. We present an XAI architecture with a cascading attention mechanism for mitigating the background bias for the onboard processing. By exploiting the localization ability in pyramid feature blocks, we can extract high-quality visual explanation covering the both semantic and small contexts of an object. For enhancing visual explainability of complex satellite images, we also describe a novel computing federation with the ground station and supervisors. In the ground station, active learning-based sample selection and attention refinement scheme with a simple feedback method are conducted to achieve the robustness of explanation and efficient supervisor’s annotation cost, simultaneously. Experiments on various datasets show that the proposed system improves accuracy in object recognition and accurate visual explanation detecting small contexts of objects even in a peripheral region. Then, our attention refinement mechanism demonstrates that the inconsistent explanation can be efficiently resolved only with very simple selection-based feedback.
This manuscript discusses the key characteristics of the Digital Ecosystems (DEs) model, which, we argue, is particularly appropriate for connecting and orchestrating the many heterogeneous and autonomous online systems, infrastructures, and platforms that constitute the bedrock of a digitally transformed society. Big Data and AI systems have enabled the implementation of the Digital Twin paradigm (introduced first in the manufacturing sector) in all the sectors of society. DEs promise to be a flexible and operative framework that allow the development of local, national, and international Digital Twins. In particular, the “Digital Twins of the Earth” may generate the actionable intelligence that is necessary to address global change challenges, facilitate the European Green transition, and contribute to realizing the UN Sustainable Development Goals (SDG) agenda. The case of the Destination Earth initiative and system is discussed in the manuscript as an example to address the broader DE concepts. In respect to the more traditional data and information infrastructural philosophy, DE solutions present important advantages as to flexibility and viability. However, designing and implementing an effective collaborative DE is far more difficult than a traditional digital system. DEs require the definition and the governance of a metasystemic level, which is not necessary for a traditional information system. The manuscript discusses the principles, patterns, and architectural viewpoints characterizing a thriving DE supporting the generation and operation of “Digital Twins of the Earth”. The conclusions present a set of conditions, best practices, and base capabilities for building a knowledge framework, which makes use of the Digital Twin paradigm and the DE approach to support decision makers with the SDG agenda implementation.
Indonesia is more prone to natural disasters due to its geological condition under the three main plates, making Indonesia experience frequent seismic activity, causing earthquakes, volcanic eruption, and tsunami. Those disasters could lead to other disasters such as landslides, floods, land subsidence, and coastal inundation. Monitoring those disasters could be essential to predict and prevent damage to the environment. We reviewed the application of remote sensing and Geographic Information System (GIS) for detecting natural disasters in the case of Indonesia, based on 43 articles. The remote sensing and GIS method will be focused on InSAR techniques, image classification, and susceptibility mapping. InSAR method has been used to monitor natural disasters affecting the deformation of the earth’s surface in Indonesia, such as earthquakes, volcanic activity, and land subsidence. Monitoring landslides in Indonesia using InSAR techniques has not been found in many studies; hence it is crucial to monitor the unstable slope that leads to a landslide. Image classification techniques have been used to monitor pre-and post-natural disasters in Indonesia, such as earthquakes, tsunami, forest fires, and volcano eruptions. It has a lack of studies about the classification of flood damage in Indonesia. However, flood mapping was found in susceptibility maps, as many studies about the landslide susceptibility map in Indonesia have been conducted. However, a land subsidence susceptibility map was the one subject to be studied more to decrease land subsidence damage, considering many reported cases found about land subsidence frequently occur in several cities in Indonesia.
The aim of this study is to propose service-oriented connection model among National Geospatial Information Platforms(NGIPs). For this, the study analyzes the necessity of NGIPs connection and extracts the issues related to the connection among NGIPs through Industrial-University-Institute experts survey. Based on this analysis, this study constructs service-oriented connection model for NGIPs, so called Single Point Access model and proposes the policy and technological counterplan to realize this model. This study result can be applied to establish a platform government based on geospatial information, policy for NGIP, and the national Information plan.
In this study, the concept of spatial big data and effective ways to build a spatial big data system are presented. Big Data is defined as 3V(volume, variety, velocity). Spatial big data is the basis for evolution from 3V's big data to 6V's big data(volume, variety, velocity, value, veracity, visualization). In order to build an effective spatial big data, spatial big data system building should be promoted. In addition, spatial big data system should be performed a national spatial information base, convergence platform, service providers, and providers as a factor of production. The spatial big data system is made up of infrastructure(hardware), technology (software), spatial big data(data), human resources, law etc. The goals for the spatial big data system build are spatial-based policy support, spatial big data platform based industries enable, spatial big data fusion-based composition, spatial active in social issues. Strategies for achieving the objectives are build the government-wide cooperation, new industry creation and activation, and spatial big data platform built, technologies competitiveness of spatial big data.
Design and development of a compact orthomode transducer (OMT) for K-band is described in this paper. An OMT comprises basic square waveguide port, and it is employed to isolate the single direct polarizations in an orthogonally coupled port and direct waveguide port. This model is intended for K-band task and can be utilized in satellite correspondence systems. The symmetric RF power transmission is coupled to a standard port, and a flared waveguide segment is utilized. The configured OMT covers the 24.5–25.4 GHz recurrence band for direct port as well as a connected port. An executed structure has coefficients of reflection across the K-band at all ports better than −12 dB. An implemented structure has point-to-point segregation and is greater than 32 dB, and the insertion loss is about 0.35 dB across the K-band. CST simulator has been used to optimize and simulate the OMT. The constructed model is sensible for satellite systems.KeywordsAntenna feedOrthomode transducerWaveguideIsolationK-band
Over the past decade, big data incorporating a spatial component “GEOSPATIAL BIG DATA” has become a global focus,
increasingly attracting the attention of academia, industry, government and other organizations. The possibility of managing
and processing geospatial big data to help decision-making therefore appears to be an important scientifc and societal issue.
But it is difcult to store, manage, process, analyze, visualize and extract useful information from geospatial big data using
traditional approaches on local machines. In this article, a survey of geospatial big data platforms was conducted. In this
context, several studies of the literature have been evaluated in terms of the diferent technologies and the main platforms
for processing geospatial big data. This article is intended to guide researchers working on geospatial big data applications.
View-only version: https://rdcu.be/cVKxR
In recent years, our society, because of the arrival of a new paradigm according to the rapid changes in ICT has entered into future smart society and the ubiquitous era. So it can be a notable turning point in the city and administrative spatial informatization, aspects of the era change. Therefore, this study was to derive a desirable vision for the city of Busan Centum City Informatization in the dream of leading global smart city of Busan by applying `scenario planning` as a foresight method. Soon this study derived a successful local informatization strategy for Centum City in Busan. It proposed the use of the administrative aspects of information with spatial informatization as metadata information. Also this study explored the future leadership strategy of Busan Centum City in smart society. Eventually in 2030 to around, In order to still remain Busan Centum City as a leading ICT smart city, this study suggested the following strategy. It is important to increase the satisfaction of citizen services through the use of the administrative aspects of information with spatial informatization as metadata information for urban information system.
Recently, Korea government make an effort to make jobs through public information disclosure and a public-private partnerships. In this regard, the MOLIT (Ministry of Land, Infrastructure and Transport) is pushing the V-World Business. The V-World is the public platform for the government to disclose spatial and adminstration information. However, the V-World is still not been able to fulfill the role of a public platform, private partnerships window, Warehouse jobs. So, the molit is promoting the V-World advanced project, creating a long-term plan. This study performed a user satisfaction survey and analysis, this result are used as a basis data of the efficient execution of the V-World advanced project and creating long-term planning. Also, we suggested V-World Service Improvement, Open API Service Improvement, future service direction. This study improve the current the V-World, will be utilized as basic data of improving utilization of the use.
Recently, it is very important to create economic value as well as develop core algorithms and technologies in the field of R&D. Various R&D projects make an effort to do the technology commercialization of their results and, as part of efforts, many studies on business model(BM) are conducted to create economic benefits in using the developed technology. However, it is difficult to use the general business model methodologies, which are usually utilized for companies, to the government's research due to different processes and characteristics between them. And for the practical application of business models, it needs to systematize conceptual business models in technical perspective through technical architecture analysis. In this study, a business model development process and a technical architecture analysis for national R&D project is developed for the technology commercialization. In addition, the process is applied to Korean Land Spatialization Program (KLSP) organized by Ministry of Land, Transport and Maritime Affairs to verify the feasibility of its practical application.
According to "Special law for the safety management of facilities", facilities of group 1 and 2 which are larger than a specified size should be examined periodically by experts. In addition, the other ones not belonging to the group 1 and 2 should be also managed in accordance with "Basic law for the management of disaster and safety" by the facility managers. However, there are many cases that these regulations are not kept in the field of safety management because most of safety management work has been done manually without a formal procedure. The purpose of this research is to develop an facility safety management system based on the National Geographic Information System(NGIS) which can integrates and manages the facility safety management information. The final system integrates the information which is related to several laws and distributed among several organizations.
Korean Land Spatialization Program (KLSP) is a R&D program of the National GIS Project for developing ubiquitous GIS technologies under control of Ministry of Land, Transport and Maritime Affairs. The first program from 2006 to 2012, initiated with 42 million of private matching fund. Aiming 'Innovation of the GIS technology for the ubiquitous Korean land', KLSP consists of five core research projects and one research coordination project. The coordination project's purpose is to practically utilize and commercialize the results of core research projects. Korean Land Spatialization Group (KLSG) is planning a test-bed for testing, integrating, and exhibit- ing the KLSP's outcomes. Integrations of the outcomes are mandatory for the successful KLSG Test-Bed. The main objective of this paper is to introduce KLSP test-bed and three methodologies for integration of the outcomes in KLSP. As a plan of integrations, especially, this paper proposes SWE SOS (Sensor Observation Service) prototype to achieve interoperability of the geo-sensor networks.
The information about land use presents future development and vision being the basis of nation development. therefore, it is necessary to more active research that can detect wide land use and changes for the information and efficient management about land use. In this study, we wished to analyze effectively land use changes to west coastal area that is fast changing land use by the latest national land development and urbanization. this study executed land cover classification using 4 year's Landsat TM images including INCHEON in west coast, and efficiently could manage the result of land cover changes through Arc/Info GRID analysis. specially, by using ArcView, we could variously detect land cover changes, and query and search easily past land cover changes of pixel that correspond to specific region.
The visual implementation of 3-dimensional national environment is focused by the requirement and importance in the fields such as, national development plan, telecommunication facility deployment plan, railway construction, construction engineering, spatial city development, safety and disaster prevention engineering. The currently used DEM system using contour lines, which embodies national geographic information based on the 2-D digital maps and facility information has limitation in implementation in reproducing the 3-D spatial city. Moreover, this method often neglects the altitude of the rail way infrastructure which has narrow width and long length. There it is needed to apply laser measurement technique in the spatial target object to obtain accuracy. Currently, the LiDAR data which combines the laser measurement skill and GPS has been introduced to obtain high resolution accuracy in the altitude measurement. In this paper, we first investigate the LiDAR based researches in advanced foreign countries, then we propose data a generation scheme and an algorithm for the optimal manage and synthesis of railway facility system in our 3-D spatial terrain information. For this object, LiDAR based height data transformed to DEM, and the real time unification of the vector via digital image mapping and raster via exactness evaluation is transformed to make it possible to trace the model of generated 3- dimensional downtown building with long distance for 3D tract model generation
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