• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.373-383
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• 2015

Spatial information has been widely used for efficient land use and management, disaster management, environment management, infrastructure management, corporate marketing, and cultural assets management, and the need for spatial information is expected to be increased. For this reason, central government, local government and public institutions must establish a National Spatial Information System (Fifteen systems related to spatial information managed by National Spatial Data Infrastructure Policy office, NSIS) framework that guarantees high accuracy and quality. The NSIS will provide convenience usage of spatial information in the field of decision-making or civil support. However the current National Spatial Information System is mainly established with separate processes, which causes data redundancy, deterioration of information, passive opening, and sharing of the spatial data. This study suggests 4 standards, which has been derived by applying value-chain model to NSIS data flow, and they are ‘Production and Establishment’, ‘Integration and Sharing’, ‘Application and Fusion’ and ‘Release and Opening’. Based on these standards, the 15 NSIS were analyzed to draw out implications and reforming directions were suggested. By following these suggestions we expect more recent, consist, accurate, and connected National Spatial Information Service which will be more open to public and then satisfy the demands.

• Journal of Korea Spatial Information System Society
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• v.3 no.1 s.5
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• pp.95-108
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• 2001

The provision of spatial data is a key infrastructural requirement for the promotion of economic growth, environmental quality, social progress, etc. 4S technology integrates 4 kinds of systems that process spatial data: GIS (Geographic Information System), GNSS (Global Navigation Satellite System), ITS (Intelligent Transport System), and SIIS (Spatial Imagery Information System). Spatial data processing field is expected to get synergy effect and overcomes development limit of individual unit technology via 4S technology. This paper discusses both the development of 4S-kernel technology and the construction of 4S-based framework, In the development of 4S kernel technology, we will concentrate on the following issues: the development of 4S base components for reciprocity integration among GIS, SIIS, GNSS and ITS technologies, the development of 4S-Mobile S/W and H/W, 4S-Van components, and national LBS technologies. And in the construction of 4S-based framework, we will especially concentrate on the ISP for overall 4S technologies, the international cooperative research center, and the guide model deduction for supervision and certification of 4S projects. Finally, we examine about how the construction of 4S-baed framework affects 4S industry.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.587-607
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• 2020

Soil moisture is essential information for meteorological and hydrological analyses. To date, many efforts have been made to achieve the two goals for soil moisture data, i.e., the improvement of accuracy and resolution, which is very challenging. We presented an ensemble downscaling method for quality improvement of gridded soil moisture data in terms of the accuracy and the spatial resolution by the integration of BMA (Bayesian model averaging) and ATPRK (area-to-point regression kriging). In the experiments, the BMA ensemble showed a 22% better accuracy than the data sets from ESA CCI (European Space Agency-Climate Change Initiative), ERA5 (ECMWF Reanalysis 5), and GLDAS (Global Land Data Assimilation System) in terms of RMSE (root mean square error). Also, the ATPRK downscaling could enhance the spatial resolution from 0.25° to 0.05° while preserving the improved accuracy and the spatial pattern of the BMA ensemble, without under- or over-estimation. The quality-improved data sets can contribute to a variety of local and regional applications related to soil moisture, such as agriculture, forest, hydrology, and meteorology. Because the ensemble downscaling method can be applied to the other land surface variables such as temperature, humidity, precipitation, and evapotranspiration, it can be a viable option to complement the accuracy and the spatial resolution of satellite images and numerical models.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.148-148
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• 2022

Spatiotemporal precipitation data is one of the primary quantities in hydrological as well as climatological studies. Despite the fact that the estimation of these data has made considerable progress owing to advances in remote sensing, the discrepancy between satellite-derived precipitation product (SPP) data and observed data is still remarkable. This study aims to propose an effective deep learning model (DLM) for bias correction of SPPs. In which TRMM (The Tropical Rainfall Measuring Mission), CMORPH (CPC Morphing technique), and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) are three SPPs with a spatial resolution of 0.25o exploited for bias correction, and APHRODITE (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) data is used as a benchmark to evaluate the effectiveness of DLM. We selected the Mekong River Basin as a case study area because it is one of the largest watersheds in the world and spans many countries. The adjusted dataset has demonstrated an impressive performance of DLM in bias correction of SPPs in terms of both spatial and temporal evaluation. The findings of this study indicate that DLM can generate reliable estimates for the gridded satellite-based precipitation bias correction.

• International Journal of Highway Engineering
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• v.13 no.3
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• pp.111-119
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• 2011

The noise prediction model, KRON-2006, in South Korea has been developed for obtaining the average noise level. The model is based on an outdoor sound propagation method based on ISO9613 and ASJ Model-1998 and supports the analysis of the linear noise source, such as highway, for obtaining Leq. Because of that, the model can't obtain Lmax, Lmin from the time series noise profile based on traffic at every moment. In order to address this problem, the real time noise prediction model based on traffic simulation using GIS model and algorithm is proposed. It can predict the vehicle point noise level based on vehicle type, speed generated from traffic simulation by using headway and obtain Lmax, Lmin as integrating the noise profile generated from it at every moment. An evalution of the noise prediciton model using field measurements finds good agreement between predicted and measured noise levels at 1m, 8m, 15m from curb of the near side lane.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.13-21
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• 2011

The purpose of this study is enhancing CFD model by applying detailed and accurate CFD input data produced from 3D City model and integrating CFD model with 3D city model with OpenGL, 3D city aerodynamic simulation, and visualization tool. CFD_NIMR_SNU model developed by NIMR and SNU and 3D City model produced by NGII were used as input data. Wind flow and pollution diffusion simulator and viewer were developed in this study. Atmospheric environment simulation and visualization tool will save time and cost for urban climate planning and management by enhancing visual communication.

• Spatial Information Research
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• v.16 no.4
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• pp.499-511
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• 2008

To solve the emerging geospatial problems, more creative and effective spatial information infrastructures are required. To solve the emerging geospatial problems at a national level, this study assumes that the current Korean NSDI considered descriptive needs to be more prescriptive. The future NSDI will require a more useful integration vehicle for matters and places of national importance such as national security and emergency prevention and management. The purpose of this study is to identify "What can be done for the Korean NSDI to be more prescriptive?" This study reviews previous researches and new SDI concepts, analyzes the Korean NSDI in terms of a descriptive NSDI, and proposes a prescriptive NSDI model for Korean geospatial problems. The model includes new aspects of an advanced NSDI and several tasks for the future prescriptive Korean NSDI.

• Journal of Environmental Impact Assessment
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• v.19 no.4
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• pp.381-396
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• 2010

It is essential to consider strategies, spatial planning, and reflection of sustainability for the creation of sound urban spaces. To this end, there is a need for plans that can secure better sustainability through strategic environmental assessment (SEA) of plans. This study examined the literature and available precedent to develop a SEA model for administrative plans for urban development including metropolitan plans, urban master plans and urban management plans. In the course of development of the model, environmental issues associated with the urban plans were analyzed by classifying them into ten categories, including "spatial planning," "conservation planning," "greenbelt systems," "habitats." and etc. according to their rank. Furthermore, those issues were reflected on the development of environmental evaluation indices for the plans. Overall and detailed environmental indices that can be applied to the administrative plans for urban development including metropolitan plans, urban master plans and urban management plans were devised for five stages: (1) Establishment of development goals and strategy, (2) Analysis of current status and characteristics, (3) Conceptualization of spatial structure, (4) Planning for each department, and (5) Execution and management. Sub plans are more detailed and concrete. Criteria based on the evaluation indices, when performing evaluations on plans based on each environmental assessment index in reference to experts and the literature, were used to forecast their effects, i.e. whether they had a positive, negative, or no effect or relationship, or whether their effects was uncertain. Based on the forecasts, this study then presents means to establish more improvable plans. Furthermore, by synthesis of the effects according to each index and integration of the process, plans were analyzed overall. This study reflects the characteristics of the present time period based on issues in the SEA process and techniques in upper level administrative plans being newly established, and presents them according to the stage of each plan. Furthermore, by forecasting the effect of plans by stage, this study presents proposals for improvement, and in this aspect, can be meaningful in promoting plan improvements through SEA.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.4
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• pp.88-97
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• 2004

A Grid-based distributed evaporation prediction model which calculates temporal and spatial evaporation with a heat balance method was developed. And, the model was considered as the integration with distributed hydrological model in near future. 'This model was programmed by fortran language and used ASCII formatted map data of DEM (Digital Elevation Model) and land cover map extracted by remote sensing data. Also, temporal variations and spatial distributions of evaporation are presented by using GIS. To verify the applicability of the model, it was applied to the Shonai river basin ($532km^2$) which has sufficient meteorological and hydrological data, Japan. The result shows that the estimated mean annual evaporation was 825.4mm, and this value is estimated as suitable things in considering rainfall and discharge data in study area.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.329-329
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• 2022

Accurate characterization of terrestrial precipitation variation from high spatial resolution satellite sensors is beneficial for urban hydrology and microscale agriculture modeling, as well as natural disasters (e.g., urban flooding) early warning. However, the widely-used top-down approach for precipitation retrieval from microwave satellites is limited in several hydrological and agricultural applications due to their coarse spatial resolution. In this research, we aim to apply a novel bottom-up method, the parameterized SM2RAIN, where precipitation can be estimated from soil moisture signals based on an inversion of water balance model, to generate high spatial resolution terrestrial precipitation estimates at 0.01º grid (roughly 1-km) from the C-band SAR Sentinel-1. This product was then tested against a common reanalysis-based precipitation data and a domestic rain gauge network from the Korean Meteorological Administration (KMA) over central South Korea, since a clear difference between climatic types (coasts and mainlands) and land covers (croplands and mixed forests) was reported in this area. The results showed that seasonal precipitation variability strongly affected the SM2RAIN performances, and the product derived from separated parameters (rainy and non-rainy seasons) outperformed that estimated considering the entire year. In addition, the product retrieved over the mainland mixed forest region showed slightly superior performance compared to that over the coastal cropland region, suggesting that the 6-day time resolution of S1 data is suitable for capturing the stable precipitation pattern in mainland mixed forests rather than the highly variable precipitation pattern in coastal croplands. Future studies suggest comparing this product to the traditional top-down products, as well as evaluating their integration for enhancing high spatial resolution precipitation over entire South Korea.