• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.143-143
• /
• 2022

Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.

• Journal of Korea Technology Innovation Society
• /
• v.1 no.3
• /
• pp.313-325
• /
• 1998

Government-Supported Research Institutes(GSRI) have done complex product(CP) development with national needs. The products to be developed have very limited demand. The most important things at CP development are technology innovation through knowledge creation and acquisition. Then, this paper suggests the technology innovation system for CP development. In CP development like satellite, government must do strategic management at national level and technology management at program level. Two managements are tools to achieve the strategic goals. The key points in CP are integration and interface among subsystems and person. From these factors and innovation system, R&D planning and practice are based on sharing and creation of knowledge. CP development projects ought to overlap and parallel for sustainable acquisition and creation of knowledge.

• Journal of Aerospace System Engineering
• /
• v.9 no.2
• /
• pp.41-46
• /
• 2015

The various risk factors that affected schedule, costs and mission success, etc. in development of the satellite. This paper derives the considerable "Cost of Quality" factors in the satellite development phase through the survey of practical techniques in respect of measurement of quality cost in the commercial products manufacturing, and proposes mitigation strategy of quality cost using the approach that can be minimized it.

• Korean Management Science Review
• /
• v.23 no.3
• /
• pp.41-61
• /
• 2006

This study is to propose a sales forecasting framework for new products in the prelaunch phase where no saies data are available. For the purpose we first develop an extended Bass model with the dynamic market potential and then propose an estimation method based on the market survey and scenario methodology. The proposed parameter estimation method is different from previous studies in that most of them have only Proposed the management judgments or analogies. We also apply the proposed model to satellite DMB market in Korea to verify the model.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.173-173
• /
• 2023

The Mekong River Basin (MRB) is a crucial watershed in Asia, impacting over 60 million people across six developing nations. Accurate satellite-based precipitation products (SPPs) are essential for effective hydrological and watershed management in this region. However, the performance of SPPs has been varied and limited. The APHRODITE product, a unique gauge-based dataset for MRB, is widely used but is only available until 2015. In this study, we present a novel framework for correcting SPPs in the MRB by employing a deep learning approach that combines convolutional neural networks and encoder-decoder architecture to address pixel-by-pixel bias and enhance accuracy. The DLF was applied to four widely used SPPs (TRMM, CMORPH, CHIRPS, and PERSIANN-CDR) in MRB. For the original SPPs, the TRMM product outperformed the other SPPs. Results revealed that the DLF effectively bridged the spatial-temporal gap between the SPPs and the gauge-based dataset (APHRODITE). Among the four corrected products, ADJ-TRMM demonstrated the best performance, followed by ADJ-CDR, ADJ-CHIRPS, and ADJ-CMORPH. The DLF offered a robust and adaptable solution for bias correction in the MRB and beyond, capable of detecting intricate patterns and learning from data to make appropriate adjustments. With the discontinuation of the APHRODITE product, DLF represents a promising solution for generating a more current and reliable dataset for MRB research. This research showcased the potential of deep learning-based methods for improving the accuracy of SPPs, particularly in regions like the MRB, where gauge-based datasets are limited or discontinued.

• Journal of Aerospace System Engineering
• /
• v.8 no.2
• /
• pp.49-54
• /
• 2014

The main purpose of Korea Space Launch Vehicle II(KSLV-II) Program is to develop a domestic launch vehicle that can deliver a 1.5ton class application satellite into a Low Earth Orbit(600~800km). The data management is an essential factor in systems engineering for success of large-scale complex systems development, and it systematically manages the information and technical data for the total life-cycle of a system. In this paper, data management policies and processes on KSLV-II program are presented, and product life-cycle management system for KSLV-II program is also presented.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.37 no.9
• /
• pp.923-930
• /
• 2009

In this paper, we introduce a satellite conceptual design software which can be used for outlining a new satellite as well as for educational purpose. This software consists of three commercial tools: MATLAB, STK(Satellite Tool Kit), and Excel. The management of the design software is done by MATLAB which provides basic calculations, GUI(Graphical User Interface), Excel data base management, and STK control. STK, an orbital simulation software developed by AGI, takes a part of obtaining accurate orbital information of a satellite. Excel, a product of Microsoft, is used for the data base of previous satellites and for the saving place of temporary and final results of the software. The conceptual design of a satellite is to roughly estimate power system and mass. In the power system design, the sizes of solar array and battery are determined. Based on the database of existing satellites, we can estimate the subsystems's mass fraction of a target satellite. Design examples for Kompsat 1 and 2 are suggested for verification of the developed software.

• Journal of Aerospace System Engineering
• /
• v.3 no.1
• /
• pp.6-11
• /
• 2009

It is anticipated that quality assurance for the Ka band Communication Payload System(COPS) development program of the communication, Ocean & Meteorological Satellite(COMS) may be a core technical factor to be concerned in order to avoid any failure, and to assure its final performance during the mission lifetime in space. Those can be managed and verified and assessed by performing the Quality Assurance (QA) and risk management which helps to prevent and to reduce the critical fails. This paper introduces the Product Assurance (PA) system and procedures for controlling and monitoring sub-contractors which were participated in Ka band Communication Payload System (COPS) development. Also this paper shows Quality Assurance (QA) procedures and detailed their processes for assured the product performed by local companies from site survey for selecting companies to delivery of their equipment.

• Journal of Aerospace System Engineering
• /
• v.2 no.1
• /
• pp.22-27
• /
• 2008

It is anticipated that quality assurance for the Ka band Communication Payload System(COPS) development program of the Communication, Ocean & Meteorological Satellite(COMS) may be a core technical factor to be concerned in order to avoid any failure, and to assure its performance during the mission lifetime in space. Those can be managed and verified and assessed by performing the Quality Assurance (QA) and risk management which helps to prevent and reduce the critical fails. This paper introduces the Product Assurance (PA) system and procedures for Ka band Communication Payload System which was established and performed during the Qualification Model (QM) manufacturing phase. In this paper, we present detailed process for the products manufactured by local companies according to PA procedures operated through whole phases from design to test of equipment. Also this paper shows Quality Assurance (QA) procedures and detailed their processes for assured the product quality manufactured by local companies.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2016.05a
• /
• pp.230-230
• /
• 2016

Hydrological modeling is a very complex task dealing with multi-source of data, but it can be potentially benefited from recent improvements and developments in remote sensing. The estimation of actual land surface evapotranspiration (ET), an important variable in water management, has become possible based entirely on satellite data. This study adopted a Surface Energy Balance Algorithm for Land (SEBAL) with the use of MODerate Resolution Imaging Spectrometer (MODIS) satellite products. The SEBAL model is one of the commonly used approach for the ET estimation. A primary advantage of the SEBAL model is rather its minimum requirement for ground-based weather data. The MODIS provides ET (MOD16) product that is based on the Penman-Monteith equation. This study aims to further develop the SEBAL model by employing a more rigorous parameterization scheme including the estimation of uncertainty associated with parameter and model selection in regression model. Finally, the proposed model is compared with the existing approaches and comprehensive discussion is then provided.