• Journal of Korean Society for Geospatial Information Science
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• v.19 no.2
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• pp.9-17
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• 2011

For the exact status of the land such as land cover classification and land use classification, feature classification system has been utilized in several organizations and agencies. However, those classification systems are limited to detection of land change and it's also not suited for the extraction of land changed. In this study, we would proposed a standard feature classification system which presents both in natural and artificial change of land effectively. Based on comparison and analysis of domestic and foreign relevant feature classification system, we proposed a standard feature classification system. In order to validate the applicability of the proposed feature classification system, we evaluated the accuracy with using automatic feature classification based on supervised classification and pre-knowledge hierarchical classification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1858-1872
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• 2023

With the advance of radar technologies, the availability of synthetic aperture radar (SAR) images increases. To improve application of SAR images, a management system for SAR images is proposed in this paper. The system provides trainable land cover classification module and display of SAR images on the map. Users of the system can create their own classifier with their data, and obtain the classified results of newly captured SAR images by applying the classifier to the images. The classifier is based on convolutional neural network structure. Since there are differences among SAR images depending on capturing method and devices, a fixed classifier cannot cover all types of SAR land cover classification problems. Thus, it is adopted to create each user's classifier. In our experiments, it is shown that the module works well with two different SAR datasets. With this system, SAR data and land cover classification results are managed and easily displayed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.19 no.4
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• pp.385-393
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• 2001

Urban land use information is the base data for the urban planning, district-level planning, traffic impact assessment and environmental impact assessment, etc. The level of detail of the current land use information is not enough to analysis and planning. In this study, the status and problems of the current land use information is analysed. The advanced abroad cases, such as LBCS(Land Based Classification System) of American Planning Association, are studied. The purpose of this study is to develop the coding system for urban land use information classification. Through this system, it is anticipated to standardization of land use classification system and improvement of data compactability.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.144-147
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• 1999

The objective of this study is to quantitatively evaluate the effects of various SAR speckle reduction methods for multisource land-cover classification by backpropagation neural network, especially over the coastal region. The land-cover classification using neural network has an advantage over conventional statistical approaches in that it is distribution-free and no prior knowledge of the statistical distributions of the classes is needed. The goal of multisource land-cover classification acquired by different sensors is to reduce the classification error, and consequently SAR can be utilized an complementary tool to optical sensors. SAR speckle is, however, an serious limiting factor when it is exploited for land-cover classification. In order to reduce this problem. we test various speckle methods including Frost, Median, Kuan and EPOS. Interpreting the weights about training pixel samples, the “Importance Value” of each SAR images that reduced speckle can be estimated based on its contribution to the classification. In this study, the “Importance Value” is used as a criterion of the effectiveness.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.105-118
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• 2016

The purpose of this study is to improve the classification system of sub-divided land cover map among the land cover maps provided by the Ministry of Environment. To accomplish the purpose, first, the overseas country land cover map classification items were examined in priority. Second, the area ratio of each item established by applying the previous sub-divided classification system was analyzed. Third, the survey on the improvement of classification system targeting the users (experts and general public) who actually used the sub-divided land cover map was carried out. Fourth, a new classification system which improved the previous system by reclassifying 41 classification items into 33 items was finally established. Fifth, the established land cover classification items were applied on study area, and the land cover classification result according to the improvement method was compared with the previous classification system. Ilsan area in Goyang city where there are diverse geographic features with various land surface characteristics such as the urbanization area and agricultural land were distributed evenly were selected as the study area. The basic images used in this study were 0.25 m aerial ortho-photographs captured by the National Geographic Information Institute (NGII), and digital topographic map, detailed stock map plan, land registration map and administrative area map were used as the relevant reference data. As a result of applying the improved classification system into the study area, the area of culture-sports, leisure facilities was $1.84km^2$ which was approximately more than twice larger in comparison to the previous classification system. Other areas such as transportation and communication system and educational administration facilities were not classified. The result of this study has meaningful significance that it reflects the efficiency for the establishment and renewal of sub-divided land cover map in the future and actual users' needs.

• Journal of Korean Society of Rural Planning
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• v.1 no.2
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• pp.43-52
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• 1995

This study is to establish a planning methodology for rural area development with land suitability classification. Land suitability classification was carried out by introducing Geographic Information System. The planning methodology was applied to Sunheung district located in Youngpoong county, Kyongbuk Province, Korea. Land suitability classification by the GIS showed that only 29 % of present agricultural land were higher than class 2 and 71 % were in bad condition for agricultural land. Especially, 22.2 % of agricultural land were under class 5 as the lowest level and 265.2 ha of forest were possible to develop as an agricultural land. It was proved that GIS may be a powerful tool in rural planning process. In addition, it is thought that GIS can be applied to the fields of agricultural land management system in many ways.

• Journal of Korean Society of Rural Planning
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• v.3 no.2
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• pp.102-111
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• 1997

For rational agricultural land use planning, it is quite necessary to get hold of land suitability precisely and to make decision on land use patterns accordingly. In the methodological viewpoint, objective and scientific evaluation techniques for land suitability classification should be supported for the systematic land use planning. As one of technical development approaches to rational land use planning, this study tried to frame a land suitability evaluation system for agricultural purposes. Evaluation unit is defined as a tract of land bounded by road, other land units and topographical features. And quantification theory was applied in the determination works of evaluation criteria. The administrative area of Namsa-myon(district), Yongin-si(city), Kyunggi-do(province) was selected for the case study. In order to check the feasibility of the evaluation system developed in the study, field check team, consisting of 2 government officers and 2 representative farmers, carried out evaluation works by observation on 148 sample land units, 10% of total 1,480 ones. Between estimated and observed results, there showed very good relationship of its multiple correlation coefficient, R=0.9467.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_1
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• pp.499-505
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• 2007

A method of improving the correctness and confidence in land use classification as well as urban spatial structure analysis of local governments using GIS and satellite imagery is suggested. This study also compares and analyzes LSAS (Land Suitability Assessment System) results using two approaches-LSAS with priority classification, and LSAS using standard estimation factors without priority classification. The conclusions that can be drawn from this study are as follows. First, a method of maintaining up-to-date local government data by updating the LSAS database using high-resolution satellite imagery is suggested. Second, to formulate a scientific and reasonable land use plan from the viewpoint of territory development and urban management, a method of simultaneously processing the two described approaches is suggested. Finally, LSAS was constructed by using varieties of land information such as the cadastral map, the digital topographic map, varieties of thematic maps, and official land price data, and expects to utilize urban management plan establishment widely and effectively through regular data updating and problem resolution of data accuracy.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.261-265
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• 2004

The purpose of this study is to present a standardized scheme for providing agriculture-related information at various spatial resolutions of satellite images including Landsat＋ETM, KOMPSAT-1 EOC, ASTER VNIR, and IKONOS panchromatic and multi-spectral images. The satellite images were interpreted especially for identifying agricultural areas, crop types, agricultural facilities and structures. The results were compared with the land cover/land use classification system suggested by Ministry of Construction & Transportation based on NGIS (National Geographic Information System) and Ministry of Environment based on satellite remote sensing data. As a result, high-resolution agricultural land cover map from IKONOS imageries was made out. The results by IKONOS image will be provided to KOMPSAT-2 project for agricultural application.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.5
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• pp.99-112
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• 2020

This study aims to propose biotope field datasheet and biotope type classification based on habitat-based by analyzing the German biotope system. The German system began in 1976 and has established a habitat-based national biotope classification system. On the other hand, Korea institutionalized in 2018 to build a classification system based on land use and land cover, which is a classification system that does not fully reflect ecosystem in Korea. Germany operates 44 biotope classification systems and 40 biotope field datasheet. Korea uses a single biotope field datasheet regardless of the biotope type. This classification system may not reflect the characteristics of Korea's biotope ecological habitat. The biotope classification system of Korea was proposed by dividing it into five categories: mountain ecology, freshwater ecology, land ecology, coastal ecology, and development area to reflect ecosystem habitat. The biotope type was designed as a system of large-classification-middle-small classification and subdivided into medium-classification and subdivided in each biotope system. The major classifications were classified into 44 categories according to the mountainous biotope(11), freshwater biotope(8), terrestrial biotope (12), coastal biotope(6), and development biotope(7). Unlike Germany, Korea's biotope field datasheet was proposed in five ways according to the classification of major ecosystem types. The results of this study are expected to contribute to the policy suggestion and the utilization of ecosystem conservation because the biotope classification system is classified to reflect the characteristics of ecosystem habitats.