• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.107-116
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• 2012

We investigated the accuracy in three dimensional geo-positioning derived by four high resolution satellite images acquired by two different sensors using the vendor-provided rational polynomial coefficients(RPC) based block adjustment in this research. We used two in-track stereo pairs of GeoEye-1 and WorldView-2 satellite and DGPS surveying data. In this experiment, we analyzed accuracies of RPC block adjustment models of two kinds of homogeneous stereo pairs, four kinds of heterogeneous stereo pairs, three 3 triplet image pairs, and one quadruplet image pair separately. The result shows that the accuracies of the models are nearly same. The accuracy without any GCPs reaches about CEP(90) 2.3m and LEP(90) 2.5m and the accuracy with single GCP is about CEP(90) 0.3m and LEP(90) 0.5m.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.229-240
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• 2019

3D geo-spatial model have been widely used in the field of Civil Engineering, Medical, Computer Graphics, Urban Management and many other. Especially, the demand for high quality 3D spatial information such as precise road map construction has explosively increased, MMS and UAV techniques have been actively used to acquire them more easily and conveniently in surveying and geo-spatial field. However, in order to perform 3D modeling by integrating the two data set from MMS and UAV, its so needed an proper registration method is required to efficiently correct the difference between the raw data acquisition sensor, the point cloud data generation method, and the observation accuracy occurred when the two techniques are applied. In this study, we obtained UAV point colud data in Yeouido area as the study area in order to determine the automatic registration performance between MMS and UAV point cloud data using ICP(Iterative Closet Point) method. MMS observations was then performed in the study area by dividing 4 zones according to the level of overlap ratio and observation noise with based on UAV data. After we manually registered the MMS data to the UAV data, then compared the results which automatic registered using ICP method. In conclusion, the higher the overlap ratio and the lower the noise level, can bring the more accurate results in the automatic registration using ICP method.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.82-84
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• 2003

Watershed boundaries and flow paths within the watershed are the most important factors required in watershed analysis. Most often the derivation of watershed boundaries and stream network and flow paths is based on topographical maps but spatial variation of flow direction is not clearly understandable using this method. Water resources projects currently use 1: 50, 000-scale ground survey or aerial photography-based topographical maps to derive watershed boundary and stream network. In basins, where these maps are not available or not accessible it creates a real barrier to watershed geo-spatial analysis. Such situations require the use of global datasets, like GTOPO30. Global data sets like ETOPO5, GTOPO30 are the only data sets, which can be used to derive basin boundaries and stream network and other terrain variations like slope aspects and flow direction and flow accumulation of the watershed in the absence of topographic maps. Approximately 1-km grid-based GTOPO 30 data sets can derive better outputs for larger basins, but they fail in flat areas like the Karkheh basin in Iran and the Amudarya in Uzbekistan. A new window in geo-spatial hydrology has opened after the launching of the space-borne satellite stereo pair of the Terra ASTER sensor. ASTER data sets are available at very low cost for most areas of the world and global coverage is expected within the next four years. The DEM generated from ASTER data has a reasonably good accuracy, which can be used effectively for hydrology application, even in small basins. This paper demonstrates the use of stereo pairs in the generation of ASTER DEMs, the application of ASTER DEM for watershed boundary delineation, sub-watershed delineation and explores the possibility of understanding the drainage flow paths in irrigation command areas. All the ASTER derived products were compared with GTOPO and 1:50,000-based topographic map products and this comparison showed that ASTER stereo pairs can derive very good data sets for all the basins with good spatial variation, which are equal in quality to 1:50,000 scale maps-based products.

• Geophysics and Geophysical Exploration
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• v.10 no.1
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• pp.50-59
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• 2007

The advent of towed geo-electrical array surveying on water and land has resulted in datasets of magnitude approaching that of airborne electromagnetic surveying and most suited to 1D inversion. Robustness and complete automation is essential if processing and reliable interpretation of such data is to be viable. Sharp boundaries such as river beds and the top of saline aquifers must be resolved so use of smoothness constraints must be minimised. Suitable inversion algorithms must intelligently handle low signal-to-noise ratio data if conductive basement, that attenuates signal, is not to be misrepresented. A noise-level aware inversion algorithm that operates with one elastic thickness layer per electrode configuration has been coded. The noise-level aware inversion identifies if conductive basement has attenuated signal levels so that they are below noise level, and models conductive basement where appropriate. Layers in the initial models are distributed to span the effective depths of each of the geo-electric array quadrupoles. The algorithm works optimally on data collected using geo-electric arrays with an approximately exponential distribution of quadrupole effective depths. Inversion of data from arrays with linear electrodes, used to reduce contact resistance, and capacitive-line antennae is plausible. This paper demonstrates the effectiveness of the algorithm using theoretical examples and an example from a salt interception scheme on the Murray River, Australia.

• Spatial Information Research
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• v.12 no.4 s.31
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• pp.299-305
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• 2004

According to the facility of effective search and user-friendly access to various spatial data by building GIS, the demand for application of information and social effect has been increased. To meet such domestic demands, it has become necessary to develop local, regional, and global SDI(Spatial Data Infrastructure) which can support discovery, access, and use of spatial information in the decision-making process. Many developed countries are implementing and managing GSDI in accordance with their state and purpose. There are two typical international cases; U.S. Geospatial One-Stop and European Geo-Portal. These systems are observed the international standards so they provide standardization and interoperability of GI. In domestic cases, however, each sector is managing separately geospatial data management systems. From this point of view, this paper proposed implementation approaches of GOS that can provide interchange of geospatial information between supplier and user. This paper focused on standardization, considered technical and political factors and analyzed two cases of GOS such as U.S. and Europe cases into our spatial information environments. It is possible to search and access geospatial data effectively by introducing GOS. In addition, it is possible to promote popularization of geospatial information and development of GIS industy.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.682-686
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• 2003

This paper is concerned with 'reverse difference' of marine sediments at the Camau tongue in the extreme south of Vietnam. We demonstrate the importance of remote sensing in geomorphology and marine geological application, using only visual evaluation and some data-processing techniques. In this paper, about 10,000 km$^2$ of the territorial water in the extreme south of Vietnam is being studied. We show that form and behavior of Mekong and its branch can be determined by visually interpreting remote sensing images and using ERDAS IMAGE 8.5 software. Besides, the 'reverse difference' phenomenon is explained by flows of Mekong river and its branches.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.2
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• pp.47-53
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• 2012

Recently many developed countries have used satellite images for classifying cropland areas to reduce time and efforts put into field survey. Korea also has used satellite images for the same purpose since KOMPSAT-2 was successfully launched and operated in 2006, but still far way to go in order to achieve the required accuracy from the products. This study evaluated the accuracy of the calculated croplands by using the objected classification method with various satellite images including ASTER, Spot-5, Rapid eye, Quickbird-2, Geo eye-1. Also, their usability and effectiveness for the cropland survey were verified by comparing with field survey data. As results. Geo eye-1 and Rapid eye showed higher accuracy to calculate the paddy field areas while Geo eye-1 and Quickbird-2 showed higher accuracy to calculate the upland field areas.

• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.241-241
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• 2017

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.71-73
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• 2019

How much and where vehicles exist is an essential element in the implementation of a GeoAI-based urban environment that reflects traffic information. In this paper, we trained vehicle data using Mask R-CNN that deep learning model useful for object detection and extraction, and verified vehicle detection in actual aerial images taken with drones.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.21-22
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• 2021

Early academic warning is considered as an inherent problem in education data mining. Early and timely concern and guidance can save a student's university career. It is widely assumed as a multi-class classification system in view of machine learning. Therefore, An accurate and precise methodical solution is a complicated task to accomplish. For this issue, we present a hybrid model employing rough set theory with a back-propagation neural network to ameliorate the predictive capability of the system with an illustrative example. The experimental results show that it is an effective early academic warning model with an escalating improvement in predictive accuracy.