• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.6
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• pp.581-590
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• 2014

With rapid land development, land category should be updated on a regular basis. However, manual field surveys have certain limitations. In this study, attempts were made to extract a feature vector considering spectral signature by parcel, PIMP (Percent Imperviousness), texture, and VIs (Vegetation Indices) based on RapidEye satellite image and cadastral map. A total of nine land categories in which feature vectors were significantly extracted from the images were selected and classified using SVM (Support Vector Machine). According to accuracy assessment, by comparing the cadastral map and classification result, the overall accuracy was 0.74. In the paddy-field category, in particular, PO acc. (producer's accuracy) and US acc. (user's accuracy) were highest at 0.85 and 0.86, respectively.

• Spatial Information Research
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• v.19 no.3
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• pp.11-22
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• 2011

It is usual for the carbon dioxide emission to be calculated by official energy consumption statistics produced from a number of specialized industrial process such as refinery, power plant etc. The aim of this research was to evaluate potential of cadastral system in monitoring carbon dioxide emitted from land use. An empirical study for a cadastral category was conducted to demonstrate how a on-site measurement can be used to assist in estimating the carbon dioxide emission in terms of land use specific settings. The cadastral category based analysis made it possible to identify area-wide patterns of carbon dioxide emission, which cannot be acquired by traditional Government statistics. It was possible to identify successively increasing trends in the human-related parcels such as housing land while decreasing trends of carbon dioxide in sink parcels(eg. forest). The results indicate that the cadastral parcel could be used not only as a tool to monitor carbon dioxide emission, but also as an evidence to restrict initiation of development activities causing negative influence to carbon dioxide emission such as road construction. As a result, the research findings have established the new concept of "carbon dioxide emission monitoring based on cadastral category", proposed as an initial aim of this paper.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.5
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• pp.443-453
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• 2020

The automatic land category extraction method was proposed, and the accuracy was evaluated by learning the aerial photo characteristics by land category in the border area with various restrictions on the acquisition of geospatial data. As experimental data, this study used four years' worth of published aerial photos as well as serial cadastral maps from the same time period. In evaluating the results of land category extraction by learning features from different temporal and spatial ranges of aerial photos, it was found that land category extraction accuracy improved as the temporal and spatial ranges increased. Moreover, the greater the diversity and quantity of provided learning images, the less the results were affected by the quality of images at a specific time to be extracted, thus generally demonstrating accurate and practical land category feature extraction.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.63-73
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• 2020

The Ministry of Land, Infrastructure and Transport carried out a pilot project for data maintenance in 2011 to ensure the accuracy of cadastral records nationwide, and now trying to reduce the errors such as omission of the cadastral book, inconsistency of land category between cadastral account book and cadastral map, etc. and the boundary between the map boundary, scale, and administrative areas. In this study, we looked at the currents status and problems of the cadastral research, improving the cadastral map, which has been promoted by the government and the cadastral office. In order to revitalize the cadastral map data maintenance project, it is necessary to re-establish the plan for each step for challenging the limitation of current data maintenance, and the master plan for promotion system, and develop manuals to maintain consistency and secure accuracy of cadastral map maintenance, such as "Coverage and Maintenance Guidelines for Cadastral Maps", and secure the national budget for error correction in cadastral map led by government.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.spc4_2
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• pp.421-430
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• 2014

Aerial imagery, Satellite imaging and Hyperspectral imaging(HSI) are widely using at mapping those of agriculture, woodland, waters shoreline, and land cover, but are rarely applied at the Cadastre. There are many study cases on the overlay of aerial imagery and satellite imaging with Cadastral Map and the upgrade and registration of Cadastre' Land Category, however, reported as successful. Therefore, this study has been aimed to show the use of the Hyperspectral Imaging technology for Cadastre, especially for the land category. Also, the HSI sensor could function as a geospatial acquisition tool for error checks of the existed land categories, and as a helpful tool for acquiring the attributes and spatial data, such as the agriculture, soil, and vegetation, etc. This result indicates that HSI sensor can implement the Multipurpse Cadastre(MPC) by fusing with the cadastral information.

• Spatial Information Research
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• v.12 no.1
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• pp.43-56
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• 2004

Basically a land parcel consists of a land parcel number, land category, land boundary and area, and land value is mostly determined by the land category. Generally people want to change their land use to increase their land value so that they can expect more benefits from the land. However, changing land use causes several problems with land properties, haphazard urban expansions and land category non-coincidences. Unfortunately, no effective solutions exist for land category non-coincidence problems. In this study, we proposed a methodology that can classify the land category based land covers using high resolution satellite images and digital topographic maps. For this, we obtained a parcel based land use/cover classification map. Using both this classification map and a digital cadastral map, we inspected land category non-coincidences. As a result, land category non-coincidence rates could be statistically measured and interpreted and demonstrate a possibility that we could quantitatively interpretate and measure cadastral non-coincidence automatically.

• Spatial Information Research
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• v.8 no.1
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• pp.69-83
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• 2000

Cadastral map is the basic data that prescribe a lot number, the classification of land category, a boundary and ownerships of the parcels. Because the analogue cadastral map is not appropriate for the Parcel Based Land Information System, computerization of cadastral map is needed. When considering other automatic vectorizing softwares, we conclude that they can not satisfy the accuracy needed in cadastral map. Also screen digitizing methods demand lots of time. So we developed semi-automatic vectorizing program that realized almost capacities, such as overlay display which is needed for screen digitizing , window link, vector file generation , and so forth. As comparing screen digitizing method using AutoCAD with our developed program, we could obtain not only almost same accuracy , but also 35 minute reduction in vectorizing.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7855-7862
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• 2015

Cadastral map information is created by registering parcel information such as location, lot number, land category and boundary through the cadastral survey. However, with regard to boundary point coordinate, computerized cadastral information data was registered to either two decimal places (unit in centimeter) or three decimal places (unit in millimeter) so that a confusion in cadastral administration and cadastral survey has been caused. Therefore, the purpose of this study is to look for a method of matching two different coordinate systems through the consideration of registration of cadastral information data and area calculation. In conclusion, the result of the investigation not only shows that areal change and the creation of minute polygons resulted from land alteration could be solved by changing boundary point coordinate from two decimal places to three decimal places, but also suggests that the related laws and regulations to register boundary point coordinate to three decimal places should be institutionally corrected and applied.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.57-66
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• 2011

The purpose of this study is to research into a method of selecting the subject parcel with a change in the category of land given surveying the land alteration state focusing on the present state of road in the government-owned and public land by using the fuzzy membership function and GIS spatial analysis. It selected the old town center of Incheon Jung-gu, and the new downtown & the forest land of Gyeyang-gu as the research subject region, and carried out GIS spatial analysis on a serial cadastral map, urban planning road layer of Korea Land Information System, practical width of road layer of Road Name Address Management System & cadastral data base, and then calculated the suitable index for the subject parcel with a change in the category of land by using the fuzzy membership function with having the critical value as the area ratio of each parcel on a serial cadastral map that was incorporated into road layer or practical width of road layer. It finally selected the parcel, which is different in land category from the real land usage, as the final subject parcel for altering land category, by using the screen of visualizing the suitable index and the aerial ortho photograph. As a result of the final selection, the fuzzy GIS spatial analysis method, which was suggested in this study, is judged to be efficient in the selection period and the methodology compared to the existing manual method. It could be confirmed to be more suitable method for downtown than forest land and for the new downtown than the old town center.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.763-776
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• 2021

This paper introduces a method of selecting priority update areas for subdivided land cover maps by training orthoimages and serial cadastral maps in a deep learning model. For the experiment, orthoimages and serial cadastral maps were obtained from the National Spatial Data Infrastructure Portal. Based on the VGG-16 model, 51,470 images were trained on 33 subdivided classifications within the experimental area and an accuracy evaluation was conducted. The overall accuracy was 61.42%. In addition, using the differences in the classification prediction probability of the misclassified polygon and the cosine similarity that numerically expresses the similarity of the land category features with the original subdivided land cover class, the cases were classified and the areas in which the boundary setting was incorrect and in which the image itself was determined to have a problem were identified as the priority update polygons that should be checked by operators.