• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.2
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• pp.113-122
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• 2021

Urban expansion, particularly converting sub-urban areas to residential and commercial land use in metropolitan areas, has been considered as a significant signal of regional economic development. However, this results in urban climate change. One of the key impacts of rapid urbanization on the environment is the effect of UHI (Urban Heat Island). Understanding the effects of urban land cover change on UHI is crucial for improving the ecology and sustainability of cities. This research reports an application of remote sensing data, GIS (Geographic Information Systems) for assessing effects of urban land cover change on the LST (Land Surface Temperature) and heat budget components in Ho Chi Minh City, where is one of the fastest urbanizing region of Vietnam. The change of urban land cover component and LST in the city was derived by using multi-temporal Landsat data for the period of 1998 - 2020. The analysis showed that, from 1998 to 2020 the city had been drastically urbanized into multiple directions, with the urban areas increasing from approximately 125.281 km² in 1998 to 162.6 km² in 2007, and 267.2 km² in 2020, respectively. The results of retrieved LST revealed the radiant temperature for 1998 ranging from 20.2℃ to 31.2℃, while that for 2020 remarkably higher ranging from 22.1℃ to 42.3℃. The results also revealed that given the same percentage of urban land cover components, vegetation area is more effective to reduce the value of LST, meanwhile the impervious surface is the most effective factor to increase the value of the LST.

• Journal of The Geomorphological Association of Korea
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• v.28 no.2
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• pp.31-44
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• 2021

Due to recent climate change, continuous soil loss is occurring in the mountainous watershed. The development of geographic information systems allows the spatial simulation of soil loss through hydrological models, but more researches applied to the mountain watershed areas in Korea are needed. In this study, prior to simulating the soil loss characteristics of the mountainous watershed, the field monitoring and the SWAT and GeoWEPP models were used to simulate and analyze the rainfall and runoff characteristics in the mountainous watershed area of Jirisan National Park. As a result of monitoring, runoff showed a characteristic of a rapid response as rainfall increased and decreased. In the simulation runoff results of calibrated SWAT models, R², RMSE and NSE was 0.95, 0.03, and 0.95, respectively. The runoff simulation results of the GeoWEPP model were evaluated as 0.89, 0.30, and 0.83 for R², RMSE, and NSE, respectively. These results, therefore, imply that the runoff simulated through SWAT and GeoWEPP models can be used to simulate soil loss. However, the results of the two models differ from the parameters and base flow of actual main channel, and further consideration is required to increase the model's accuracy.

• Clean Technology
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• v.26 no.3
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• pp.228-236
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• 2020

Korea has an economy based on manufacturing industrial fields, which produce high amounts of hazardous wastes, in spite of few landfill candidates, and a significant concern for fine airborne particulates; therefore, traditional waste management is difficult to apply in this country. Moreover, waste collection and accumulation have recently been intensified by the waste import prohibitions or regulations in developing nations, the universalization of delivery services in Korea, and the global COVID-19 crisis. This study thus presents a domestic waste management strategy that aims to address the recent issues on waste. The contents of the strategy as the main results of the study include the (1) improvement of the compatibility of the classification codes between the domestic hazardous waste and the international ones such as those of the Basel Convention; (2) consideration of the mixed hazard indices to represent toxicity from low-content components such as rare earth metals often contained in electrical and electronic equipment waste; (3) management application based on risks throughout the life cycles of waste; (4) establishment of detailed material flow information of waste by integrating the Albaro system, Pollutant Release and Transfer Register (PRTR) system, and online trade databases; (5) real-time monitoring and prediction of the waste movement or discharge using positional sensors and geographic information systems, among others; and (6) selection and implementation of optimal treatment or recycling practices through Life Cycle Assessment (LCA) and clean technologies.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1061-1073
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• 2017

In this study, images were classified using convolutional neural network (CNN) - a deep learning technique - to investigate the feasibility of information production through a combination of artificial intelligence and spatial data. CNN determines kernel attributes based on a classification criterion and extracts information from feature maps to classify each pixel. In this study, a CNN network was constructed to classify materials with similar spectral characteristics and attribute information; this is difficult to achieve by conventional image processing techniques. A Compact Airborne Spectrographic Imager(CASI) and an Airborne Imaging Spectrometer for Application (AISA) were used on the following three study sites to test this method: Site 1, Site 2, and Site 3. Site 1 and Site 2 were agricultural lands covered in various crops,such as potato, onion, and rice. Site 3 included different buildings,such as single and joint residential facilities. Results indicated that the classification of crop species at Site 1 and Site 2 using this method yielded accuracies of 96% and 99%, respectively. At Site 3, the designation of buildings according to their purpose yielded an accuracy of 96%. Using a combination of existing land cover maps and spatial data, we propose a thematic environmental map that provides seasonal crop types and facilitates the creation of a land cover map.

• Journal of the Korean earth science society
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• v.22 no.6
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• pp.491-499
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• 2001

Generally, several hydrological characteristics which can be obtained from geographic processing in GIS S/W would be utilized to actual hydrological applications such as landslide stability or drainage analysis. Furthermore, by using practical GIS extension programs, it can be possible that automatic extraction task of those information, which was time-consuming and complex processing, is performed as systematical and automatic processing. In this study, using ArcView GIS S/W and its extensions concerning hydrological processing, some waterflow and surface factors in the area of Yemi sheet scaled 1:50,000 were extracted. Then, assessment of landslide stability, determined by DEM-based variables were carried out in order to investigate practical applicability of extension programs. It is thought that several hydrological factors extracted by this study were significant information to predict field model or hydrological hazardous events. It also reveals that landslide potential is overall stable with stability index mapping and S-A plot, with theoretical basis. This methodology can be applicable to other areas related to hydrological characteristics with measurements in fields.

• Journal of Korea Spatial Information System Society
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• v.4 no.2 s.8
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• pp.55-64
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• 2002

VEfficient generation of road data is one of the most important issues in GIS (Geographic Information System). In this paper, we propose a hybrid approach for automatic generation of road data by combining mobile mapping and image processing techniques. Mobile mapping systems have a form of vehicle equipped with CCD camera, GPS, and INS. They can calculate absolute position of objects that appear in acquired image by photogrammetry, but it is labor-intensive and time-consuming. Automatic road detection methods have been studied also by image processing technology. However, the methods are likely to fail because of obstacles and exceptive conditions in the real world. To overcome the problems, we suggest a hybrid method for automatic road generation, by exploiting both GPS/INS data acquired by mobile mapping system and image processing algorithms. We design an estimator to estimate 3-D coordinates of road line and corresponding location in an image. The estimation process reduces complicated image processing operations that find road line. The missing coordinates of road line due to failure of estimation are obtained by cubic spline interpolation. The interpolation is done piecewise, separated by rapid change such as road intersection. We present experimental results of the suggested estimation and interpolation methods with image sequences acquired by mobile mapping system, and show that the methods are effective in generation of road data.

• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.201-207
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• 2020

In this study, the practicality of unmanned aerial vehicle photography information was identified. Therefore, a total of four consecutive surveys were conducted on the field-level survey areas among the areas subject to photography using unmanned aerial vehicles, and the changes in crop conditions were analyzed using pictures of unmanned aerial vehicles taken during each survey. It is appropriate to collect and utilize photographic information by directly taking pictures of the survey area according to the time of the on-site survey using unmanned aerial vehicles in the field layer, which is an area where many changes in topography, crop vegetation, and crop types are expected. And it turned out that it was appropriate to utilize satellite images in consideration of economic and efficient aspects in relatively unchanged rice paddies and facilities. If the survey area is well equipped with systems for crop cultivation, deep learning can be utilized in real time by utilizing libraries after obtaining photographic data for a certain area using unmanned aircraft in the future. Through this process, it is believed that it can be used to analyze the overall crop and shipment volume by identifying the crop status and surveying the quantity per unit area.

• Spatial Information Research
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• v.4 no.2
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• pp.131-146
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• 1996

The purpose of this study is to extract the main locational factors to affect the location of fastfood stores in Kangnam -Gu, Seoul by using Geographic Information Systems. The Franchise system, which came to be employed in full scale since 1990, now enjoying the booming period, especially fast food industry. The procedure of this research has four steps. First, the spatial distribution of fastfood chain stores in Seoul is analyzed by the land use and road map. Second, the spatial variations of fastfood stores in dong districts of Seoul is explained by multiple regression analysis. Third, the main locational factors to affect the location of fast food stores in Kangnam -Gu are extracted by demand and supply sides using GIS technologies. Finally, the potentiallocational zones where are selected by extracted locational factors are compared with the actual distribution of f astf ood stores in Kangnam - Gu. In terms of demand side, the main locational factors include commercial and service facilities, sub¬ways and bus stops which have a lot of pedestrians, and large apartment districts that have high popu¬lation densities. In terms of supply sides, the main locational factors include land use types and land value, accessibility. After fast food chain stores of Kangnam -Gu are overlaid final potentiallocational zones extracted by demand and supply sides of locational factors, it can be identified that over 80 % of fastfood stores are located in the potentiallocational zone. In conclusion, this study shows that spatial analysis functions may potentially be improved using GIS technologies. However there are still difficulties for the locational analysis for service industries to col¬lect appropriate data in terms of computerized base maps as well as consumer behavior and store characteristics itself.

• Journal of Korea Spatial Information System Society
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• v.7 no.3 s.15
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• pp.107-118
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• 2005

Various spatial data are utilized, through geographic information system, for the process to make a decision related to space. Generally, spatial data is large in quantity and it costs high and takes quite a long time for producing and maintaining it. An existing spatial data management system, tile-based one, for digital map manages spatial data being separated by a uniform data unit called tile. These systems can be implemented easily but have many problems such as they can directly store and manage feature included in tile. Therefore, in this paper, we suggest a feature-based spatial data management system for digital map. The proposed system is able to store and manage spatial data in the unit of feature directly. Hence this system is able to immediately update any change in the data and to supply users with the updated data without any delay. The proposed system can not only support a function of data input, management, supplying and update but also support unity origin coordinate conversion, UFID creation, feature unifying, feature dividing and metadata input which is not supported by the existing tile-based system. The proposed system can easily manage spatial data and can increase efficiency in processing and application.

• Journal of Korea Spatial Information System Society
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• v.2 no.2 s.4
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• pp.59-74
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• 2000

Because efficiency of the 1st-phase NGIS investment(1995-2000) has not been clearly measured, the action taken in the 2nd-phase NGIS project requires NGIS budgets to be evaluated in terms of effectiveness. Especially, the effective investments in local governments are critical for the NGIS projects, because they execute the much larger amount of budgets in total than other GIS projects. As indicated, for the successful NGIS implementation, it is important to obtain continuous political and financial supports from decision makers. As a persuasion measure for the budget appropriation, CBA(Cost-Benefit Analysis) and CEA(Cost-Efficiency Analysis) can play an important role for the decision makers. The major concern of this paper is how to measure the costs and benefits of the GIS implementation by considering important characteristics of the GIS projects in local governments, and existing theories are reviewed for this concern. The GISs in local governments can have different stages in terms of its evolution and the effectiveness of the applications can be represented variously. To identify categories for measuring costs and benefits of the various GISs, case studies and success stories are reviewed from both the foreign and domestic research. The categories of costs and benefits are determined from the tangible and intangible aspects. The categories for the quantitative and qualitative measure are proposed to evaluate the GISs in local governments. After measuring costs and benefits, three key evaluation methods in cost-benefit analysis are suggested as follows: 1) the benefit: cost ratio (B/C), 2) Internal Rate of Return (IRR), and 3) the net present values (NPV) of the costs and benefits. The sensitivity and uncertainty analysis are also helpful to make a decision for the GIS budget appropriation in local governments. In conclusion, although cost-benefit analysis is not an easy undertaking, it is certain that it can play an important role in the future for the GIS funding decisions in local governments.