• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.1D
• /
• pp.149-156
• /
• 2006

Existing method of landuse classification using aerial photographs or field survey requires relatively higher amount of time and cost due to necessary manual work. Especially in urban area where the pattern of landuse is densely aggregated, a landuse classification using satellite image is more complex. In this background, this study proposes a landuse classification method to utilize 1:1,000 digital topographic data and IKONOS satellite image. To prove the possibility of this method, the method was applied to Seoul metropolitan area. The results shows the total accuracy of approximately 95% and 14 landuse classes extracted. Based on the results from the pilot study, this method is applicable to landuse classification in urban area.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2004.11a
• /
• pp.343-347
• /
• 2004

Landuse information is used to plan land use, urban and environmental management as base data. And, demand for landuse information is rising due to ecological consideration in urban area. But existing method to extract landuse information from aerial photographs or satellite images is difficulte to describe sufficient urban landuses. Also landuse information need to be linked with statistical data because statistical data is used to make decision for urban planning and management with landuse. Therefore this study aims to examine the landuse classification method using statistical unit data and 1:1,000 digital topographic data. for the purpose, the method was applied to a part of metropolitan Seoul. The results of study shows that total accuracy is 95%. For the future, the method will be effectively applicable for the city maintenance.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.3
• /
• pp.203-209
• /
• 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 Korean Institute of Intelligent Systems Conference
• /
• 2001.12a
• /
• pp.1-4
• /
• 2001

The classification performance of Artificial Neural Network (ANN) and RBF-NN was compared for Landsat TM image. The RBF-NN was validated for three unique landuse types (e.g. Mixed landuse area, Cultivated area, Urban area), different input band combinations and classification class. The bootstrap resampling technique was employed to estimate the confidence intervals and distribution for unit load, The pollutant generation was varied significantly according to the classification accuracy and percentile unit load applied. Especially in urban area, where mixed landuse is dominant, the difference of estimated pollutant load is largely varied.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.17 no.1
• /
• pp.1-10
• /
• 1999

Landuse information is base data being applied as common database in the process of executing urban project service and is very available. But, the progress of business on landuse information building is deficient yet. In this study, we'd like to deal with landuse information projet that is the base of urban project, many landuse information building and the method of extraction of efficient second-information. Also, we built system to apply actively landuse information for urban projectors. And, we'd like to present the model on urban landuse classification system that wouldn't be standard yet by studying the method of urban landuse pattern using landuse in-formation being built. Also, we can evaluate if the model of urban landuse pattern comes up to present landuse. We can expect it is a base data by extracting unsuitable area from present landuse efficiently when we construct landuse project.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.16 no.2
• /
• pp.187-194
• /
• 1998

In this study, effective multispectral Landsat TM band combinations for a merging with the high resolution IRS-1C PAN data using the IHS method to improve landuse accuracy is discussed. From the pre-classified image using the merged images with TM all six band images(with the exception of band 6 image) and PAN image, a sample data which has ten classes was generated. An evaluation of the overall classification accuracy for the representative seven merged images which were merged using each TM three-band images and IRS-1C PAN image by IHS method for the sample area. The increase in classification accuracy is most significant with the inclusion of two of TM4, TM5 and TM7 infrared band images. Especially, the largest increase(11.8 percent) in landuse classification accuracy were investigated when Landsat TM247 bands were merged with IRS-1C PAN data. The classification accuracy when TM three band image and PAN image were used without merging is higher than result of the case of using the merged images.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.2 no.3
• /
• pp.38-46
• /
• 1999

The purpose of the study is to analyze the effect of urbanization, the degree of development in urban scale and the comparative analysis of landuse change in order to construct the important basic data for establishing development direction and characterizing each city. To analyze the urban growth patterns a land cover classification using Landsat TM data was performed : 1987 and 1997 for the change detection of each land cover. The results of this study demonstrates that urban areas increased on while forest areas had decreased all over the Korean cities. Especially, in case of the analysis on landuse conversion rate, we found out that the forest areas was first changed into agricultural areas, then it is consequently developed into urban areas in most rural areas. This study concludes that the insufficiency of the number of knowledged officials in the local administration and a government official in one's charge, tight financial conditions and absence of recognition of cities' characteristics, urban development following unrefined development patterns, inappropriate urban planning and policy of metropolitan cities and the negligence of peculiar development patterns of each city.

• Journal of Korean Society of Forest Science
• /
• v.98 no.6
• /
• pp.780-790
• /
• 2009

The objective of this study was to analyze 'Forestland Classification System' in Korea and to develop a strategy for its improvement. A survey was conducted in this study based on the Delphi technique, one of the interactive survey method relying on a panel of experts. The result indicated that the existing 'Forestland Classification System' was initiated for reasonable management of forestland, but now it turned into one of the most strict management restrictions. To improve forestland management in Korea, it was suggested to adopt 'Forest Function System' in this study. Moreover, to avoid indiscreet landuse conversion that might be occurred by substituting the 'Forest Function System' for the 'Forestland Classification System', it was suggested to adopt 'Forestland Conversion Propriety Assessment System'. In fact, landuse conversion has been regulated by the 'Environmental Impact Assessment System', but this system appeared inadequate to be applied to the forested area. Illegal acts for having permission of landuse conversion for reserved forests was another big issue in the forestland management. For example, alteration of the reserved status of forests or partition into patches smaller than the size limit has been attempted. Thus in this study, it was strongly recommended to take sanction against such illegal acts. In order to enhance the efficiency of forestland management, it was also suggested to integrate administrative agencies related to the landuse conversion or to take over the charge to local governments.

• KCID journal
• /
• v.21 no.1
• /
• pp.45-54
• /
• 2014

In this study, Agricultural Infrastructures of Shincheon-gun in North Korea are investigated using Kompsat-2 and RapidEye satellite imagery. Target agricultural infrastructures are agricultural landuse, irrigation and drainage canals, dammed pools for irrigation and pumping stations. KOMPSAT-2 satellite imagery are use to investigate agricultural hydraulic structures and agricultural landuse are investigated by RapidEye Imagery. Geometric correction are performed using 28 GCP and QUAC method are used for atmospherical correction in all imagery. ISODATA clustering and naked-eye classification method are used for extracting agricultural hydraulic structures and Object-based analysis is applied to classifying the agricultural landuse. Extraction results of agricultural hydraulic structures and agricultural are presented and we suggest the applicability of satellite imagery to investigate agricultural infrastructures in North Korea.

• The Journal of the Korea Contents Association
• /
• v.16 no.7
• /
• pp.31-41
• /
• 2016

Atmospheric correction as a preprocessing work should be performed to conduct accurately landcover/landuse classification using hyperspectral imagery. Atmospheric correction on airborne hyperspectral images was conducted and then the effect of atmospheric correction by comparing spectral reflectance characteristics before and after atmospheric correction for a few landuse classes was analyzed. In addition, land cover classification was first conducted respectively by the maximum likelihood method and the spectral angle mapper method after atmospheric correction and then the results were compared. Applying the spectral angle mapper method, the sea water area were able to be classified with the minimum of noise at the threshold angle of 4 arc degree. It is considered that object-based classification method, which take into account of scale, spectral information, shape, texture and so forth comprehensively, is more advantageous than pixel-based classification methods in conducting landcover classification of the coastal area with hyperspectral images in which even the same object represents various spectral characteristics.