• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.14 no.1
• /
• pp.39-47
• /
• 1996

This paper is to provide land cover classification techniques for large area ranged in different pathos by classifying Landsat TM data of Jeonnam province. The analyses proceeded by individual scene because acquired dates are not same in different pathes. In this processing, troubles had happened something like variation of classes can be classified in two scenes and choice problem about overlapped area. Since spatial effects in large area affect data values, it was difficult to make a selection of classes and training fields. we could present a solution about these problems by trial and error method, and found that Bayesian maximum likelihood classification and majority filtering were effective to improve classification accuracy.

• Journal of Korean Society for Geospatial Information Science
• /
• v.25 no.1
• /
• pp.9-17
• /
• 2017

Hyperspectral imagery is used in the land cover classification with the principle component analysis and minimum noise fraction to reduce the data dimensionality and noise. Recently, studies on the supervised classification using various features having spectral information and spatial characteristic have been carried out. In this study, principle component bands and normalized difference vegetation index(NDVI) was utilized in the supervised classification for the land cover classification. To utilize additional information not included in the principle component bands by the hyperspectral imagery, we tried to increase the classification accuracy by using the NDVI. In addition, the extended attribute profiles(EAP) generated using the morphological filter was used as the input data. The random forest algorithm, which is one of the representative supervised classification, was used. The classification accuracy according to the application of various features based on EAP was compared. Two areas was selected in the experiments, and the quantitative evaluation was performed by using reference data. The classification accuracy of the proposed algorithm showed the highest classification accuracy of 85.72% and 91.14% compared with existing algorithms. Further research will need to develop a supervised classification algorithm and additional input datasets to improve the accuracy of land cover classification using hyperspectral imagery.

• Proceedings of the KSRS Conference
• /
• 2006.03a
• /
• pp.271-274
• /
• 2006

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.420-422
• /
• 2003

• Journal of Cadastre & Land InformatiX
• /
• v.49 no.1
• /
• pp.103-112
• /
• 2019

Extraction of region of interest for satellite image classification is one of the important techniques for efficient management of the national land space. However, recent studies on satellite image classification often depend on the information of the selected image in selecting the region of interest. This study propose an effective method of selecting the area of interest using the continuous digital topographic map constructed from high resolution images. The spatial information used in this research is based on the digital topographic map from 2013 to 2017 provided by the National Geographical Information Institute and the 2015 Sejong City land cover map provided by the Ministry of Environment. To verify the accuracy of the extracted area of interest, KOMPSAT-3A satellite images were used which taken on October 28, 2018 and July 7, 2018. The baseline samples for 2015 were extracted using the unchanged area of the continuous digital topographic map for 2013-2015 and the land cover map for 2015, and also extracted the baseline samples in 2018 using the unchanged area of the continuous digital topographic map for 2015-2017 and the land cover map for 2015. The redundant areas that occurred when merging continuous digital topographic maps and land cover maps were removed to prevent confusion of data. Finally, the checkpoints are generated within the region of interest, and the accuracy of the region of interest extracted from the K3A satellite images and the error matrix in 2015 and 2018 is shown, and the accuracy is approximately 93% and 72%, respectively. The accuracy of the region of interest can be used as a region of interest, and the misclassified region can be used as a reference for change detection.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.2 no.3
• /
• pp.60-70
• /
• 1999

The purpose of this study is to analyze the spatial change of water quality pollutant in the upper-stream of Kumho River basin. For this purpose, it compared with ground survey data of water quality measurement, using GIS and Landsat TM image, and then constructed a database of water quality pollutants in the watershed by Arc/Info. Also the land cover classification maps of 1985 and 1997 were prepared using maximum likelihood classification. This study detected and analysed the classified images to produce the area of land cover change per sub-basin. In addition, choropleth maps were prepared with spatial change value of water quality pollutants, and overlay analysis was carried out with weight score for each layer. The results of this study revealed that population, animals and fruit orchards were main factors in the spatial change of water pollution of Kumho River basin. The Comparision of pollutions by sub-basins showed a high pollution value in Daechang-chun and Omok -chun stream which follows through the urban area.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.14 no.2
• /
• pp.28-39
• /
• 2011

This study estimates the characteristics of flow loads by classification items of the Ministry of Environment and by land cover change using HyGIS-SWAT. The result of analyzing the land cover change using the classification items shows that the urban area and the farmland area in Mishim-cheon and Gap-cheon are expanding while the forest area is decreasing. The result of analyzing the characteristics of classification items shows that peak discharge increases and total yearly discharge decreases in Mushim-cheon. The result of analyzing the characteristics by data-construction period shows that peak discharge decreases but total discharge increases in Gap-cheon. Three land cover change scenarios are applicable to the expansion of urban area and farmland area. According to the result of application, urbanization influences and Farmland area expansion influences increase peak discharge, total yearly discharge and sediment concentration.

• Korean Journal of Remote Sensing
• /
• v.30 no.2
• /
• pp.207-218
• /
• 2014

The information on the land cover along stream corridor is important for stream restoration and maintenance activities. This study aims to review the different classification methods for mapping the status of stream corridors in Seom River using airborne RGB and CIR digital ortho imagery with a ground pixel resolution of 0.2m. The maximum likelihood classification, minimum distance classification, parallelepiped classification, mahalanobis distance classification algorithms were performed with regard to the improvement methods, the skewed data for training classifiers and filtering technique. From these results follows that, in aerial image classification, Maximum likelihood classification gave results the highest classification accuracy and the CIR image showed comparatively high precision.

• Journal of Korean Society of Rural Planning
• /
• v.19 no.2
• /
• pp.121-128
• /
• 2013

The greenhouse gas emission according to the energy consumption is the cause of global warming. With various climates, it is occurs the direct problems to ecosystem. The various studies are being to reduce the carbon dioxide, which accounts for more than 80% of the total greenhouse gas emissions. In this study, estimate the carbon usage using potential biomass extracted from forest type map according to land-use by satellite image, and estimate the amount of carbon dioxide, according to the energy consumption of urban area. The $CO_2$ adsorption is extracted by the amount of forest based on the direct absorption of tree, the other used investigated value. The $CO_2$ emission in Jecheon was 3,985,900 $TCO_2$ by energy consumption. At the land cover classification, the forest is analyzed as 624,085ha and the farmland is 148,700ha. The carbon dioxide absorption was estimated at 1,834,850 Tons from analyzed forest. In case of farmland, it was also estimated at 706,658 Tons.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.22 no.3
• /
• pp.293-301
• /
• 2004

This study analyzes the interrelationship with air pollution quality and land used patterns, and analyzes the history and optimal allocation of TMS using GIS. Seasonal air pollution map are maded of TMS data in study area, and land used patterns based on Land Cover Classification Map are reclassified as residential area, commercial area, industrial area, traffic concentrated area, and non-Polluted area. Pollution sources can be identified through analyzing the correlation of air pollution and land used patterns by GIS spatial overlaying technique. Hence, the result shows that it coincides with the characteristics of conventional air pollution. Air pollution quality measured by TMS shows similar to that of its near stations or the same land used patterns, through the history and allocation analysis of TMS. Therefore, it is need to consider these characteristics in setting TMS positions in the future.