• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.2
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• pp.80-91
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• 2003

In this research, re-using band ratio data was proposed and examined as a method of raising the accuracy in landcover classification which is using satellite data.In order to determine the band which is used to calculation in the classified item, the six bands except the band 6 were combined with the band in which combination is possible and the landcover classification by MLC of supervised classification was carried out. In the result of landcover classification which is combined with forty nine combination, Two bands which were mostly used by band combination in the accuracy belonged inside the 10th place of a higher rank were selected and also calculated. landcover classification were performed again after the calculation result had been recombinated from the research. In addition, the new landcover classification result was compared and examined with the landcover classification using the old data. From the result of which was compared and examined the new landcover classification data recombinated calculation result with landcover classification using the original data, The classification accuracy of the new landcover classification data recombinated calculation result became low in ground but became improved in the all class. Specially The accuracy to urban area is very improved. therefore, it determined that reusing band ratio data is very useful when we need to analyze landcover classification and land information to urban area after that.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.317-321
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• 2007

"The project for production of medium classification landcover maps using satellite images" has been completed from 1998 until 2005 in Korea. As the 5th project was finished in 2005, medium classification landcover maps for all areas of South Korea have been produced. The products of project currently is used in lots of fields such as public governments, universities and research institutes for policy application and scientific research. But final results of the project have several problems which is insufficiency of reliability, discordance of classification codes and many others because each project was progressed year by year. In this study, problems of existing production methods about medium classification landcover maps are extracted and solution of problems is offered. Therefore, this study will make it possible to efficiently produce and update medium classification landcover maps.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.1
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• pp.147-155
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• 2010

Landcover information of access-denied area was extracted from low-medium and high resolution satellite image. Training for supervised classification was performed to refer visually by landcover map which is made and distributed from The Ministry of Environment. The classification result was compared by relating data of FACC land classification system. As we rasterize digital military map with same pixel size of satellite classification, the accuracy test was performed by image to image method. In vegetation case, ancillary data such as NDVI and image for seasons are going to improve accuracy. FACC code of FDB need to recognize the properties which can be automated.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.1
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• pp.127-133
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• 2015

Interests in ecosystem services have increased and a number of attempts to perform a quantitative valuation on them have been undertaken. To classify the ecosystem types landcover classification maps are generally used. However, some forest types on landcover classification maps have a number of errors. The purpose of this study is to verify the forest types on the landcover map by using a variety of field survey data and to suggest an improved method for forest type classifications. Forest types are compared by overlaying the landcover classification map with the 4th forest type map, and then they are verified by using National Forest Inventory, 3rd National Ecosystem Survey and field survey data. Misclassifications of forest types are found on the forest on the forest type map and farm and other grassland on the landcover map. Some errors of forest types occur at Daegu, Busan and Ulsan metropolitan cities and Gangwon province. The results of accuracy in comprehensive classification show that deciduous forest is 76.1%; coniferous forest is 54.0%; and mixed forest is 22.2%. In order to increase the classification accuracy of forest types a number of remote sensing images during various time periods should be used and the survey period of NFI and the National Forest Inventory and National Ecosystem Survey should be consistent. Also, examining areas with wide forest patch should be prioritized during the field survey in order to decrease any errors.

• Spatial Information Research
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• v.22 no.1
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• pp.27-33
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• 2014

Considering the wide coverage, the transparency from climate condition, Interferometric Synthetic Aperture Radar (InSAR) possesses a great potential for the landcover classification as shown in many precedent researches. In addition to the merits of InSAR products for the landcover classification, the time series analysis of InSAR pairs can provide a highly reliable basis to interpret landcover. We applied such idea with the test site in Mountain Baekdu located on the border between North Korea and China. Since it is recently noted as the potential volcanic activation site, the landcover especially the vegetation distribution information is highly essential to validate the reliability of Differential Interferometric Synthetic Aperture Radar (DInSAR) over Mt. Baekdu. The algorithms combining the auxiliary information from Moderate Resolution Imaging Spectroradiometer (MODIS) to analyze the phase coherence and backscatter coefficient of Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) was established. The results using InSAR signatures from two polarization modes of ALOS PALSAR showed high reliability for mining landcover and spatial distribution.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.3
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• pp.203-209
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• 2015

This paper discusses the effectiveness of using Landsat 8 TIR (Thermal Infrared) band images to improve the accuracy of landuse/landcover classification of urban areas. According to classification results for the study area using diverse band combinations, the classification accuracy using an image fusion process in which the TIR band is added to the visible and near infrared band was improved by 4.0%, compared to that using a band combination that does not consider the TIR band. For urban area landuse/landcover classification in particular, the producer’s accuracy and user’s accuracy values were improved by 10.2% and 3.8%, respectively. When MLC (Maximum Likelihood Classification), which is commonly applied to remote sensing images, was used, the TIR band images helped obtain a higher discriminant analysis in landuse/landcover classification.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.84-87
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• 2006

It was investigated what is the reasonable landcover classification system for the nonpoint pollution models. According to the parameters of the nonpoint pollution models, runoff curve number, crop management factor and Manning's roughness coefficient, the landcover classification system was proposed to manage the drainage basin of the Woopo wetland. Also, the rule-based classification method was adopted to extract the landcover information for this study area.

• Journal of Environmental Science International
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• v.15 no.4
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• pp.349-357
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• 2006

The purpose of this study is to evaluate the water pollution degree in the Mid-Nakdong River watershed regarding to landcover types using GIS method. As a result of landcover classification, rate of urban appeared highly on Daegu Metropolitan city. Also, rate of agriculture showed highly in the riparian zones of the Nakdong and Guemho River and rate of forest appeared highly in the borders of the study area. To identify the groups of watershed with similar landcover patterns using the Cluster Analysis. According to the cluster analysis, the fifty sub-watersheds were grouped in three clusters, 'Urban watershed', 'Agriculture watershed', 'Forest watershed'. The proportion of urban area in each cluster had a positive correlation with water pollution degree. Otherwise, the proportion of agriculture in the Agriculture watershed had a high positive correlation with water pollution degree. Therefore, it is necessary to estimate environmental capacity of water duality considering ecological and environmental characteristics of watershed ecosystem and expand water duality monitoring systems to small stream.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.303-309
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• 2008

Landcover map can use to establish basic national environment policy as main data predicting living place, counting pollution like a atmosphere, water and forest part. During the 1998-2005 years, Korean government made landcover maps using satellite image for part of south Korea. Landcover maps are offered free for public purpose to university and institute. So, it used basic data for policy and research parts. There are some problems for application parts because of inconsistency. So, in this study, to estimate accuracy of source data by quality checking for landcover maps. As a result, there are some errors like classification inconsistencies. So, it need verification process for landcover maps.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.465-474
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• 2009

To measure the amount of nonpoint source pollution, some efforts are tried to utilize satellite imagery. But, as the factors for water models do not relate with the landcover categories for satellite imagery, satellite imagery are adapted to roughly classified thematic map or used only for the image interpretation. The purpose of this study is to establish the landcover categories of satellite imagery to relate with the water models. To establish the categories of the landcover for the water models, it was investigated to get main factors of water flow models for the nonpoint source pollution and to review the existing study and the classification system. For this result, it was convinced that the basic unit on the nonpoint source pollution, landcover coefficients of SCS Curve Number, the crop factor of Universal Soil Loss Equation, Manning's roughness coefficients are the useful parameters to extract information from the satellite imagery. After the setup the categories for the landcover classification, it was finally defined from the consultation of the water model specialist. Woopo wetland watershed was selected to the study area because it is a representative wetland in Korea and needs the management system for nonpoint source pollution. There were used Landsat ETM Plus and SPOT-5 satellite imagery to assess the result of the image classification.