• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.1
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• pp.143-152
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• 2010

These days, we can't confirm cadastre information about stereoscopic digital map that was consist of 2 dimensions and more difficult to understand of detailed parcel boundary, area, land using for 3 dimensions. An each local government providing three-dimensional that are connected to an aerial photograph with cadastre maps. Satisfaction is high for citizens but, this service additional cost for purchase of an aerial photograph order to provide of it. So far, in various ways are under study about three dimensions using Google Earth which is possible to provides 3 dimensional information by real time for individual parcel situation. The purpose of this study was analyzed an accuracy of overlapping between cadstre maps and an image on Google Earth Web in the each different coordinates system. Also, this paper could be provided for use possibility of 3 dimensions information service with an indicator of using or a guideline of direction for local government which provide 3 dimensions information oneday.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.79-86
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• 2010

This paper presents implementation of a system for effective visualizing flight information of aircraft using Google Earth. This system in order to use a detailed satellite image which provide from Google Earth used COM API. This system appeared the various flight information of the aircraft in the instrument panel using OpenGL and the aircraft flight condition is visible in the Google Earth Map. This research result used to flight evaluation and improvement. In future will be able to apply to flight software development.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.66-75
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• 2010

The authors argues that the current road updating system based on traditional aerial photograph or multi-spectral satellite image appears to be non-user friendly due to lack of the frequent cartographic representation for the new construction sites. Google Earth are currently being emerged as one of important places to extract road features since the RGB satellite image with high multi-temporal resolution can be accessed freely over large areas. This paper is primarily intended to evaluate optimal threshold of RGB pixel values to extract road features from Google Earth. An empirical study for five experimental sites was conducted to confirm how a RGB picture provided Google Earth can be used to extact the road feature. The results indicate that optimal threshold of RGB pixel values to extract road features was identified as 126, 125, 127 for manual operation which corresponds to 25%, 30%, 19%. Also, it was found that display scale difference of Google Earth was not very influential in tracking required RGB pixel value. As a result the 61cm resolution of Quickbird RGB data has shown the potential to realistically identified the major type of road feature by large scale spatial precision while the typical algorithm revealed successfully the area-wide optimal threshold of RGB pixel for road appeared in the study area.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.753-762
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• 2021

Google provides mapping services using satellite imagery, this is widely used for the study. Since about 20 years ago, research and business using drones have been expanding. Pix4D is widely used to create 3D information models using drones. This study compared the distance error by comparing the result of the road construction site with the DSM data of Google Earth and Pix4 D. Through this, we tried to understand the reliability of the result of distance measurement in Google Earth. A DTM result of 3.08 cm/pixel was obtained as a result of matching with 49666 key points for each image. The length and altitude of Pix4D and Google Earth were measured and compared using the obtained PCD. As a result, the average error of the distance based on the data of Pix4D was measured to be 0.68 m, confirming that the error was relatively small. As a result of measuring the altitude of Google Earth and Pix4D and comparing them, it was confirmed that the maximum error was 83.214m, which was measured using satellite images, but the error was quite large and there was inaccuracy. Through this, it was confirmed that there are difficulties in analyzing and acquiring data at road construction sites using Google Earth, and the result was obtained that point cloud data using drones is necessary.

• Journal of Korean Society of Rural Planning
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• v.15 no.4
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• pp.199-211
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• 2009

The aim of this paper is to investigate the applicability of high spatial resolution remote sensing images for conducting the rural amenity resources survey. There are a large number of rural amenity resources and field reconnaissance without a sufficient preliminary survey involves a big amount of cost and time even if the data quality cannot always be satisfied with the advanced study. Therefore, a new approach should be considered like the state-of-the-art remote sensing technology to support field survey of rural amenity resources as well as to identify the spatial attributes including the geographical location, pathway, area, and shape. Generally high-resolution satellite or aerial photo images are too expensive to cover a large area and not free of meteorological conditions, but recently rapidly-advanced internet-based image services, such as Google Earth, Microsoft Bing maps, Bluebirds, Daum maps, and so on, are expected to overcome the handicaps. The review of the different services shows that Google Earth would be the most feasible alternative for the survey of rural amenity resources in that it provides powerful tools to build spatial features and the attributes and the data format is completely compatible with other GIS(Geographic information system) software. Hence, this study tried to apply the Google Earth service to interpret the amenity resources and proposed the reformed work process conjugating the internet-based high-resolution images like satellite and aerial photo data.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.06a
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• pp.9-18
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• 2010

This study investigated the cadastral non-coincidence between real land using and cadastral book using Google Earth Web for difficult area to access that is more efficient method compared with field survey for saving time and money. An reading error has occurred eight parcels about dry field and paddy field but this method is more powerful in case of a danger area of steep, unregistered cemeteries of cadastral book using Google Earth Web of image interpretation that method takes 1 day, the accuracy is 96% and improved 20% more than field survey takes 5 days by 40 parcels. It's possible to reduce the manpower, time and budget could be minimized. In particular, it is need to land alteration of forests and fields category that finds 47 locations a burial ground of non register cadastre book. Google Earth Web method is enabling easy visual analysis of the future land administration of local governments to improving the reliability of temporal and economic costs can be very useful to reduce.

• Journal of the Korean Geographical Society
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• v.43 no.2
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• pp.188-201
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• 2008

With recent rapid globalization, accurate information for the foreign countries is increasingly important. Errors based on inaccurate information and unequal international relationships complicate the situations. In this article, authors analyzed the Japanese place names which appear on the Google Earth images and place name database of the NGA. Google Earth already becomes a tremendous soft power in internet society; therefore, accurate information on the satellite image is more necessary than ever. This article finds that many types of errors exist in the place names in Google Earth image service. Also many place names are listed with Japanese pronunciation in GNS database as variants. The Japanese place names have not been used in topographic maps published since 1910s and 1930s. Japanese place names were widely used in US military maps published in 1946. 1:250,000 maps published in 1954, however, doesn't seem to use Japanese pronunciation any more.

• Journal of People, Plants, and Environment
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• v.22 no.6
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• pp.563-573
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• 2019

The North Korean government conducted its first nuclear test in 2006 and more recently the sixth nuclear test on September 3, 2017. In order to identify how North Korea's nuclear tests have affected the environment, a scientific approach is required. Although North Korea's nuclear tests and their environmental destruction are not a severe threat to the environment of the Korean Peninsula at this time, identifying environmental damage and taking countermeasures in advance are essential to minimize their potential threats to the environments. The purpose of this study is to study the environmental impact of North Korea's nuclear tests using Google Earth image analysis. As a method of the study, we compare Google Earth images taken before and after each nuclear test was conducted in North Korea. To overcome limitations of the suggested comparison method, we cross-checked our results with those of previous scientific research. After the 1st-3rd nuclear tests, green spaces were found to be considerably reduced. In particular, when comparing the Google Earth images before and after the second nuclear test, some ground subsidences were observed. Such subsidences can cause tunnels on the mountainsides and cracks in rocks around the mountains, leading to the release of radioactive materials and contaminating groundwater. Besides, after the 4th-6th nuclear tests, decay and deforestation were observed not in the nuclear test sites, but in their surrounding areas. Especially after the 5th and 6th nuclear tests, the topography and the forests of the surrounding areas were severely damaged. In relation to North Korea's nuclear tests and their impact on the natural environment, we need to prepare various policy measures to reduce North Korea's environmental pollution and natural environment destruction. Those policy measures include the establishment of various cooperative governance between the Korean government, the private sector, the academia, NGOs, and international organizations.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.4
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• pp.275-278
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• 2006

Google Earth enables people to easily find information linked to geographical locations. Google Earth consists of a collection of zoomable satellite images laid over a 3-D Earth model and any geographically referenced information can be uploaded to the Web and then downloaded directly into Google Earth. This can be achieved by encoding in Google's open file format, KML (Keyhole Markup Language), where it is visible as a new layer superimposed on the satellite images. We used KML to create and share fine resolution gridded temperature data projected to 3 climatological normal years between 2011-2100 to visualize the site-specific warming and the resultant earlier blooming of spring flowers over the Korean Peninsula. Gridded temperature and phonology data were initially prepared in ArcGIS GRID format and converted to image files (.png), which can be loaded as new layers on Google Earth. We used a high resolution LCD monitor with a 2,560 by 1,600 resolution driven by a dual link DVI card to facilitate visual effects during the demonstration.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.341-344
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• 2007

A major obstacle to classify and validate Land Cover maps is the high cost of generating reference data or multiple thematic maps for subsequent comparative analysis. In case of inaccessible area such as North Korea, the high resolution satellite imagery may be used as in situ data so as to overcome the lack of reliable reference data. The objective of this paper is to investigate the possibility of utilizing QuickBird (0.6m) of North Korea obtained from Google Earth data provided thru internet. Monthly NDVI images of nine months from the summer of 2004 were classified into L=54 cluster using ISODATA algorithm, and these L clusters were assigned to 7 classes; coniferous forest, deciduous forest, mixed forest, paddy field, dry field, water and built-up area. The overall accuracy and Kappa index were 85.98% and 0.82, respectively, which represents about 10% point increase of classification accuracy than our previous study based on GCP point data around North Korea. Thus we can conclude that Google Earth may be used to substitute the traditional in situ data collection on the site where the accessibility is severely limited.