Kim, Soo-Ock;Chung, U-Ran;Kim, Seung-Heui;Choi, In-Myung;Yun, Jin-I.
Korean Journal of Agricultural and Forest Meteorology
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v.11
no.4
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pp.162-173
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2009
Information on the expected geographical shift of suitable zones for growing crops under future climate is a starting point of adaptation planning in agriculture and is attracting much concern from policy makers as well as researchers. Few practical schemes have been developed, however, because of the difficulty in implementing the site-selection concept at an analytical level. In this study, we suggest site-selection criteria for quality Fuji apple production and integrate geospatial data and information available in public domains (e.g., digital elevation model, digital soil maps, digital climate maps, and predictive models for agroclimate and fruit quality) to implement this concept on a GIS platform. Primary criterion for selecting sites suitable for Fuji apple production includes land cover, topography, and soil texture. When the primary criterion is satisfied, climatic conditions such as the length of frost free season, freezing risk during the overwintering period, and the late frost risk in spring are tested as the secondary criterion. Finally, the third criterion checks for fruit quality such as color and shape. Land attributes related to these factors in each criterion were implemented in ArcGIS environment as relevant raster layers for spatial analysis, and retrieval procedures were automated by writing programs compatible with ArcGIS. This scheme was applied to the A1B projected climates for South Korea in the future normal years (2011-2040, 2041-2070, and 2071-2100) as well as the current climate condition observed in 1971-2000 for selecting the sites suitable for quality Fuji apple production in each period. Results showed that this scheme can figure out the geographical shift of suitable zones at landscape scales as well as the latitudinal shift of northern limit for cultivation at national or regional scales.
The normalized difference vegetation index (NDVI) derived from satellite images is a crucial tool to monitor forests and agriculture for broad areas because the periodic acquisition of the data is ensured. However, optical sensor-based vegetation indices(VI) are not accessible in some areas covered by clouds. This paper presented a synthetic aperture radar (SAR) based approach to retrieval of the optical sensor-based NDVI using machine learning. SAR system can observe the land surface day and night in all weather conditions. Radar vegetation indices (RVI) from the Sentinel-1 vertical-vertical (VV) and vertical-horizontal (VH) polarizations, surface elevation, and air temperature are used as the input features for an automated machine learning (AutoML) model to conduct the gap-filling of the Sentinel-2 NDVI. The mean bias error (MAE) was 7.214E-05, and the correlation coefficient (CC) was 0.878, demonstrating the feasibility of the proposed method. This approach can be applied to gap-free nationwide NDVI construction using Sentinel-1 and Sentinel-2 images for environmental monitoring and resource management.
The long-term imbalances between supply and demand in office market can weaken urban growth since excessive supply of offices led to office market instability and excessive demand of offices weakens growth of urban industry. Recently, there have been a lot of new large-scale supplies, which increased volatility in Seoul office market. Nevertheless, new supply of Seoul office has not been fully examined. Given this, the focus of this article was on confirming the influences of profitability, replacement cost, and demand on new office supplies in Seoul. In examining those influences, another focus was on their relative influences over time. For these purposes, we analyzed quarterly data of Seoul office market between 2003 and 2015 using a vector error correction model (VECM). As a result, in terms of the influences on the current new supply, the impact of supply before the first quarter was negative, while that of office employment before the first quarter was positive. Also, that of interest rate before the second quarter was positive, while those of cap rate before the first quarter and cap rate before the second quarter were negative. Based on the findings, it is suggested that prediction models on Seoul offices need to be developed considering the influences of profitability, replacement cost, and demand on new office supplies in Seoul.
Journal of the Korean Regional Science Association
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v.33
no.1
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pp.69-85
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2017
The positive changes in urban space and urban activities resulting from the urban services provided by Smart City is not accomplished by simply creating the physical environment built on ICT but through the cooperation and participation of citizens and private sector, which is in fact key to success. In this study, this research analyzed the role and structure of smart governance, which is a system of horizontal cooperation between public and private sector, and analyze its role in developing Smart City. The study also proposes various ways to facilitate such development in each of critical categories. For this purpose, this research studied 228 smart services across 11 categories registered in the Ministry of Land and Transport in Korea to analyze the spatial distribution of smart services by spatial hierarchy and their characteristics Also, the research conducted a case study of MetroGIS, which is an information collaboration governance system for the greater area of Minneapolis and St. Paul in the state of Minnesota, United States, to explore how governance is formed; its organizational structure; the role of sub-level organization hierarchy and their interrelationship. The results of the analysis suggest that the following conditions are required to create a smart city: first, public sector resource assistance for building community; second, enhanced communication system within the community and with outside the community; securing financial stability and establishing a model of sustainable development to induce the community to evolve into a governance form.
This study investigated the time-series relationship between housing consumer sentiment and housing prices in the five major districts in Seoul and also analyzed the effect of the housing consumer sentiment on housing prices using Granger Causality and VEC (Vector Error Correction) models. To describe the key results, first of all, housing consumer sentiment and regional housing market prices were closely related to each other, and the consumer sentiment strongly affected the change of housing prices. Second, the housing consumer sentiment was confirmed to have a discriminatory effect on the housing prices among the districts in Seoul in the short term. Specifically, the housing price of the east southern district (ESD) was the main reason for the change in housing consumer sentiment in Seoul, and that the resulting impact was transferred to other districts. Third, it was analyzed that regions other than the ESD would increase the housing prices in the long term as the housing consumer sentiment turned positive, but that the ESD would see a steady tone. Fourth, in the case of relative influence by district, housing (apartment) price fluctuation in a district was generally found to be most affected by adjacent or competitive districts. Through these findings, this study confirmed that there is a clear causality between housing consumer sentiment and housing prices in each district of Seoul and that there is a discriminatory influence on housing consumer sentiment among the districts.
The background of the research is the following. With the prosperity of drone industry, the government has been actively promoting measures to nominate 'drone photographing free areas'. However, existing laws, and procedures are rather unclear with related environmental factors in discordance with one another. Hence, voices in need for establishing a clear precondition for nominating drone photography free area have been rising. The purpose of the research is to provide measures for the preconditions to establish photography free areas for convenient drone photographing. The research utilizes literary methods, conducting focus group interviews to coordinate with specialists who can participate and discuss so that they can provide improvement measures. The research renders improvement measures in different sectors including 2x items in aviation security law, 8x items in free area nomination and procedure, 4x items in infrastructure establishment and information management area. The expected effects are the following: by attaching drone photography with aviation security law, nominating photography free area can be linked up with the Ministry of Land Infrastructure and Technology. Secondly, by enlarging photography restricted area to upper mid-air, a three dimensional drone security will be possible. Thirdly, by providing a 'Yongin area standard model', free area nomination will become more easy. Future research will focus on enhancing aviation security law regarding drone photographing. In addition, the promotion to nominate free areas for 33x responsible areas in accordance with the National Intelligence service will be required.
Traffic volumes are fundamental data widely used in various traffic analysis, such as origin-and-destination establishment, total traveled kilometer distance calculation, congestion evaluation, and so on. The low number of links collecting the traffic-volume data in a large urban highway network has weakened the quality of the analyses in practice. This study proposes a method to estimate the traffic volume data on a highway link where no collection device is available by introducing a spatial statistic technique with (1) the traffic-volume data from TOPIS, and National Transport Information Center in the Ministry of Land, Infrastructure, and (2) the navigation data from private navigation. Two different component models were prepared for the interrupted and the uninterrupted flows respectively, due to their different traffic-flow characteristics: the piecewise constant function and the regression kriging. The comparison of the traffic volumes estimated by the proposed method against the ones counted in the field showed that the level of error includes 6.26% in MAPE and 5,410 in RMSE, and thus the prediction error is 20.3% in MAPE.
Kim, Sun-Min;Yorozu, Kazuaki;Tachikawa, Yasuto;Shiiba, Michiharu
Proceedings of the Korea Water Resources Association Conference
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2011.05a
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pp.15-15
/
2011
The radar observation system in Japan is operated by two governmental groups: Japan Meteorological Agency (JMA) and the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) of Japan. The JMA radar observation network is comprised of 20 C-band radars (with a wavelength of 5.6 cm), which cover most of the Japan Islands and observe rainfall intensity and distribution. And the MLIT's radar observation system is composed of 26 C-band radars throughout Japan. The observed radar echo from each radar unit is first modified, and then sent to the National Bureau of Synthesis Process within the MLIT. Through several steps for homogenizing observation accuracy, including distance and elevation correction, synthesized rainfall intensity maps for the entire nation of Japan are generated every 5 minutes. The MLIT has recently launched a new radar observation network system designed for flash flood observation and forecasting in small river basins within urban areas. It is called the X-band multi parameter radar network, and is distinguished by its dual polarimetric wave pulses of short length (3cm). Attenuation problems resulting from the short wave length of radar echo are strengthened by polarimetric wavelengths and very dense radar networks. Currently, the network is established within four areas. Each area is observed using 3-4 X-band radars with very fine resolution in spatial (250 m) and temporal (1 minute intervals). This study provides a series of utilization procedures for the new input data into a real-time forecasting system. First of all, the accuracy of the X-band radar observation was determined by comparing its results with the rainfall intensities as observed by ground gauge stations. It was also compared with conventional C-band radar observation. The rainfall information from the new radar network was then provided to a distributed hydrologic model to simulate river discharges. The simulated river discharges were evaluated again using the observed river discharge to estimate the applicability of the new observation network in the context of operations regarding flood forecasting. It was able to determine that the newly equipped X-band polarimetric radar network shows somewhat improved observation accuracy compared to conventional C-band radar observation. However, it has a tendency to underestimate the rainfall, and the accuracy is not always superior to that of the C-band radar. The accuracy evaluation of the X-band radar observation in this study was conducted using only limited rainfall events, and more cases should be examined for developing a broader understanding of the general behavior of the X-band radar and for improving observation accuracy.
Kompsat-5 is the first Earth Observation Satellite which is equipped with an SAR in Korea. SAR images are generated by receiving signals reflected from an object by microwaves emitted from a SAR antenna. Because the wavelengths of microwaves are longer than the size of particles in the atmosphere, it can penetrate clouds and fog, and high-resolution images can be obtained without distinction between day and night. However, there is no color information in SAR images. To overcome these limitations of SAR images, colorization of SAR images using Cycle GAN, a deep learning model developed for domain translation, was conducted. Training of Cycle GAN is unstable due to the unsupervised learning based on unpaired dataset. Therefore, we proposed MS Cycle GAN applying multi-scale discriminator to solve the training instability of Cycle GAN and to improve the performance of colorization in this paper. To compare colorization performance of MS Cycle GAN and Cycle GAN, generated images by both models were compared qualitatively and quantitatively. Training Cycle GAN with multi-scale discriminator shows the losses of generators and discriminators are significantly reduced compared to the conventional Cycle GAN, and we identified that generated images by MS Cycle GAN are well-matched with the characteristics of regions such as leaves, rivers, and land.
Until recently, most people have invested in a traditional portfolio consisting of stocks, bonds and real estates based on the three-division method of properties in Korea. However, this study analyzed the impact of the composition of a portfolio combining representative real estate indirect investment products such as Reits and real estate funds on the investment performance. For this purpose, the empirical analysis using the mean variance model, which is the most appropriate method for the portfolio composition, was used. For variables used in this study, mixed asset portfolios were classified into Portfolio A through Portfolio G depending on the composition of assets, and the price indices selected as Kospi, Krx bond, Reits Trus Y7, Hanwha-Lasal fund, and Office (Seoul). The results are as follows; first Portfolio D, which combined bonds, stocks, Reits and Real Estate funds, and Portfolio G, which added the office, the actual real estate, were shown to have the lowest risk. second, Portfolio B composed of bonds, stocks and Reits and Portfolio D with added real estate funds had the lowest risk while Portfolio F composed of bonds, stocks, offices and real estate funds, and Portfolio G with added Reits were the most profitable. As a result, it has been analyzed that it was more effective to compose a portfolio including Reits and real estate funds, which were real estate indirect investment products that eliminated the illiquidity limitation of real estates than real estates, the traditional three-division method of properties. Therefore, it is possible to minimize the risk of investors and reduce the cost of ownership of the real estate by solving the illiquidity problem that is the biggest disadvantage of the direct investment, In addition, it is considered that it is more necessary to reinvigorate the real estate indirect investment market where small amounts can be invested.
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