• Journal of Korean Society for Geospatial Information Science
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• v.18 no.1
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• pp.63-72
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• 2010

In this study, an earth work design program which will improve the efficiency of earth work and enable to carry out the design using 3D Geospace-based earth work modelling in design stage was developed. Estimate of accurate earth work volume is achievable using 3D grid DEM, and based on this, a mass calculation chart was developed for movement of earth and equipment. In consideration for the resources for various construction equipments needed for civil engineering works, soil conversion and the passage is displayed. In addition, the result is restored in the form of open API-based KLM to make it possible for the users to identify the progress of the construction, thereby enhancing the intuitive understanding of three-dimensional visualization and making it easier to share the result of the analysis.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.06a
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• pp.150-158
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• 2008

참여와 공유 개방을 모토로 하는 Web 2.0이 GIS 기술과 접목되면서 GIS 분야에서의 새로운 패러다임으로 제시되고 있는 것이 Where2.0이다. Where2.0은 지리정보와 시맨틱웹을 연동하는 새로운 패러다임으로 Google의 Google Map이나 Microsoft의 Virtual Earth에서처럼 '나만의 지도'라는 새로운 비즈니스 및 서비스 모델이 각광을 받고 있다. GIS 시장적 측면에서 보면 Where 2.0 패러다임의 확산은 전문가 중심(Doer)의 GIS에서 일반사용자 중심(Viewer)의 GIS 시장의 확대로 나타나고 있으며, 비즈니스지원시장과 개인생산성 시장이 지속적으로 확대될 것으로 전망되고 있다[IDC2004]. 이에 본 고에서는 최근 이슈로 대두되고 있는 Geospatial Web의 기술적 동향을 살펴보고, 새로운 GIS 패러다임 속에서 보다 효과적인 지리정보 서비스를 제공할 수 있는 맞춤형 지리정보 제공 서비스 개념 및 모델을 제시하도록 한다.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1293-1297
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• 2016

Cholangiocarcinoma (CCA) is a serious problem in Thailand, particularly in the northeastern and northern regions. Database of population at risk are need required for monitoring, surveillance, home health care, and home visit. Therefore, this study aimed to develop a geographic information system (GIS) database and Google map of the population at risk of CCA in Mueang Yang district, Nakhon Ratchasima province, northeastern Thailand during June to October 2015. Populations at risk were screened using the Korat CCA verbal screening test (KCVST). Software included Microsoft Excel, ArcGIS, and Google Maps. The secondary data included the point of villages, sub-district boundaries, district boundaries, point of hospital in Mueang Yang district, used for created the spatial databese. The populations at risk for CCA and opisthorchiasis were used to create an arttribute database. Data were tranfered to WGS84 UTM ZONE 48. After the conversion, all of the data were imported into Google Earth using online web pages www.earthpoint.us. Some 222 from a 4,800 population at risk for CCA constituted a high risk group. Geo-visual display available at following www.google.com/maps/d/u/0/edit?mid=zPxtcHv_iDLo.kvPpxl5mAs90&hl=th. Geo-visual display 5 layers including: layer 1, village location and number of the population at risk for CCA; layer 2, sub-district health promotion hospital in Mueang Yang district and number of opisthorchiasis; layer 3, sub-district district and the number of population at risk for CCA; layer 4, district hospital and the number of population at risk for CCA and number of opisthorchiasis; and layer 5, district and the number of population at risk for CCA and number of opisthorchiasis. This GIS database and Google map production process is suitable for further monitoring, surveillance, and home health care for CCA sufferers.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.2
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• pp.719-722
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• 2016

Background: Cholangiocarcinoma (CCA) is a serious health problem in Thailand, particularly in northeastern and northern regions, but epidemiological studies are scarce and the spatial distribution of CCA remains to be determined. A database for the population at risk is required for monitoring, surveillance and organization of home health care. This study aim was to geo-visually display the distribution of CCA in northeast Thailand, using a geographic information system and Google Earth. Materials and Methods: A cross-sectional survey was carried out in 9 sub-districts and 133 villages in Chum Phuang district, Nakhon Ratchasima province during June and October 2015. Data on demography, and the population at risk for CCA were combined with the points of villages, sub-district boundaries, district boundaries, and points of hospitals in districts, then fed into a geographical information system. After the conversion, all of the data were imported into Google Earth for geo-visualization. Results: A total of 11,960 from 83,096 population were included in this study. Females and male were 52.5%, and 47.8%, the age group 41-50 years old 33.3%. Individual risk for CCA was identifed and classified by using the Korat CCA verbal screening test as low (92.8%), followed by high risk (6.74%), and no (0.49%), respectively. Gender ($X^2$-test=1143.63, p-value= 0.001), age group ($X^2$-test==211.36, p-value=0.0001), and sub-district ($X^2$-test=1471.858, p-value=0.0001) were significantly associated with CCA risk. Spatial distribution of the population at risk for CCA in Chum Phuang district was viewed with Google Earth. Geo-visual display followed Layer 1: District, Layer 2: Sub-district, Layer 3: Number of low risk in village, Layer 4: Number of high risk in village, and Layer 5: Hospital in Chum Phuang District and their related catchment areas. Conclusions: We present the first risk geo-visual display of CCA in this rural community, which is important for spatial targeting of control efforts. Risk appears to be strongly associated with gender, age group, and sub-district. Therefor, spatial distribution is suitable for the use in the further monitoring, surveillance, and home health care for CCA.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.3
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• pp.71-79
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• 2009

We expanded the 3D building information extraction method using shadow and vertical line from single high resolution image with meta information into the method for single high resolution image without meta information. Our method guesses an azimuth angle and an elevation angle of the sensor and the sun using reference building, selected by user, on an image. For test, we used an IKONOS image and an image extracted from the Google Earth. We calculated the Root Mean Square (RMS) error of heights extracted by our method using the building height extracted from stereo IKONOS image as reference, and the RMS error from the IKONOS image and the Google Earth image was under than 3 m. We also calculated the RMS error of horizontality position by comparison between building position extracted from only the IKONOS image and it from 1:1,000 digital map, and the result was under than 3 m. This test results showed that the height pattern of building models by our method was similar with it by the method using meta information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.357-363
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• 2014

The development of information technology grows the society and allows the user to generate more information and the requirements. According to recent growing interest in digital convergence technologies, digital convergence can be utilized by a variety of methods as a new study. Electronic culture atlas would be digitized cultural information that represents a particular area on the map. In detail, spatial data like as point, line, and area can be used to represent the culture information. Using electronic culture atlas, also, it is possible to provide and utilize information which is associated with time, space(map) and subject(culture). Thus, electronic culture atlas could be used as a method for the humanities or area studies and spread research results by displaying on the culture atlas. In general, existing electronic culture atlas used bitmap image mostly as a base map. Using bitmap image, it is difficult to represent to provide three-dimensional information of specific area. Also, it happens problem such as breakage occurs during zoom-in operation. To solve this problems, we design and implement electronic culture atlas based on Google Earth which is three-dimensional map service.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.113-126
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• 2021

This study was conducted to analyze the forest status and deforestation area changes of the DMZ region in North Korea based on satellite images. Using growing and non-growing season's RapidEye satellite images, land cover of the North Korean DMZ was classified into stocking land(conifer, deciduous, mixed), deforested land(unstocked mountain, cultivated mountain, bare mountain), and non-forest areas. Deforestation rates in the Yeonan-baecheon, Beopdong-Pyeonggang, Heoyang-Geumgang and Tongcheon-Goseong district were calculated as 14.24%, 16.75%, 5.98%, and 16.63% respectively. Forest fire and land use change of forest were considered as the main causes of deforestation of DMZ. Changes in deforestation area were analyzed through Google Earth images. As a results, it was shown that the area of deforestation was on a decreasing trend. This study can be used as basic data for establishing inter-Korean border region's forest cooperation strategies by providing forest spatial information on the North Korea's DMZ.

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1935-1943
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• 2022

The development and application of a high-resolution soil moisture mapping method using satellite imagery has been considered one of the major research themes in remote sensing. In this study, soil moisture mapping in the test area of Jeju Island was performed. The soil moisture was calculated with optical images using linearly adjusted Synthetic Aperture Radar (SAR) polarization images and incident angle. SAR Backscatter data, Analysis Ready Data (ARD) provided by Google Earth Engine (GEE), was used. In the soil moisture processing process, the optical image was applied to normalized difference vegetation index (NDVI) by surface reflectance of KOMPSAT-3 satellite images and the land cover map of Environmental Systems Research Institute (ESRI). When the SAR image and the optical images are fused, the reliability of the soil moisture product can be improved. To validate the soil moisture mapping product, a comparative analysis was conducted with normalized difference water index (NDWI) products by the KOMPSAT-3 image and those of the Landsat-8 satellite. As a result, it was shown that the soil moisture map and NDWI of the study area were slightly negative correlated, whereas NDWI using the KOMPSAT-3 images and the Landsat-8 satellite showed a highly correlated trend. Finally, it will be possible to produce precise soil moisture using KOMPSAT optical images and KOMPSAT SAR images without other external remotely sensed images, if the soil moisture calculation algorithm used in this study is further developed for the KOMPSAT-5 image.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.06a
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• pp.3-5
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• 2010

본 연구의 목적은 온라인과 오프라인 공간에 다양하게 존재하는 지리 관련 학습 자료를 매쉬업하여 지리교육사이트를 구현해 봄으로써 지도를 기반으로 한 지리교육용 웹 사이트 구축 가능성을 모색하는 데 있다. 그동안 교육 분야에서 API를 활용한 대부분의 연구가 사이트 구현을 제안하는 단계에 머무르고 있었다. 그러나 본 연구에서는 교과서 분석을 통하여 지리교육과 관련된 사진, 영상, 개념도, 모식도 등 다양한 자료를 매쉬업해 봄으로써, 정보 제공 방식의 변화를 추구하고, 직접 구현하여 API를 활용한 지리교육사이트의 구현 가능성을 제시한 것에 의의가 있다.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.219-222
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• 2007

Today, use of high resolution satellite image with at least 1m resolution is expanding into many more areas including forest, river way, city, seashore and so forth for disaster prevention. Interest in this medium is increasing among the general public due to the roll-out to the private sector as Google earth, Virtual Earth and so forth. However, pre-processing process that revises the geometrical distortion that result at the time of photographing is required in order to use high resolution satellite image. The purpose of this research is to search the most accurate GCP(Ground Control Point) information acquisition method that is used for the revision of high resolution satellite image's geometrical distortion through automated processing. Through this, it is possible to contribute to increasing the level of accuracy at the time of high resolution satellite image revision and to secure promptness.