• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.90-103
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• 2017

This study analyzed the surface temperature characteristics of urban green spaces under high summer temperatures to clarify the functions of green spaces in reducing urban temperatures. We obtained accurate surface temperature data using highresolution unmanned aerial vehicle images of the survey site, which was an isolated green space in the city. We analyzed differences in the surface temperature by land cover type, vegetation type, species type, and the relationship between surface temperature and vegetation volume. Based on the results, among the land cover types, wetlands and forests had low temperatures and paving areas had very high temperatures. Regarding vegetation type, broad-leaved trees had lower temperatures than coniferous trees in forests. However, in planted areas, coniferous trees had lower temperatures than broad-leaved trees. The temperature of long grass was higher than that of short grass, which suggested that the volume of grass affected the temperature. Regarding forest species type, the temperature of broad-leaved Robinia pseudoacacia forest and mixed broad-leaved forest was lower than coniferous Pinus densiflora forest. There was a slight difference in temperature between R. pseudoacacia forest and mixed broad-leaved forest. The analysis of the relationship between vegetation volume and temperature by forest species type indicated a negative correlation, where the temperature decreased with increasing vegetation volume, similar to the results of previous studies. However, we found a weak positive correlation in R. pseudoacacia forest; therefore, an increase in volume may not reduce the surface temperature depending on the dominant species.

• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.205-214
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• 2015

In this study, a novel land-cover classification framework for multi-temporal SAR data is presented that can combine multiple features extracted through data transforms and multiple classifiers. At first, data transforms using principle component analysis (PCA) and 3D wavelet transform are applied to multi-temporal SAR dataset for extracting new features which were different from original dataset. Then, three different classifiers including maximum likelihood classifier (MLC), neural network (NN) and support vector machine (SVM) are applied to three different dataset including data transform based features and original backscattering coefficients, and as a result, the diverse preliminary classification results are generated. These results are combined via a majority voting rule to generate a final classification result. From an experiment with a multi-temporal ENVISAT ASAR dataset, every preliminary classification result showed very different classification accuracy according to the used feature and classifier. The final classification result combining nine preliminary classification results showed the best classification accuracy because each preliminary classification result provided complementary information on land-covers. The improvement of classification accuracy in this study was mainly attributed to the diversity from combining not only different features based on data transforms, but also different classifiers. Therefore, the land-cover classification framework presented in this study would be effectively applied to the classification of multi-temporal SAR data and also be extended to multi-sensor remote sensing data fusion.

• Journal of Korean Society of Forest Science
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• v.101 no.3
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• pp.365-373
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• 2012

This study purposed to extract and assess the accuracy of assessment for deforestation area in Wonju city using medium resolution satellite image. The total size of deforestation area during the last nine years (2000-2008) was about 467 ha, and it was occurred annually about 52 ha. The most frequent form of deforestation was settlements (72%). Ninety percent of the size of deforestation was less than 2 ha in size. In addition, 79 percent of deforestation area was found within 500 m from the road network and within 100 m of the Forest/Non-forest boundary. This study compared the deforestation based on the administrative information (GIS deforestationI) with the deforestation (RS deforestation) extracted from the satellite imagery by vegetation indices (NDVI, NBR, NDWI). Extraction accuracy, mean-standard deviation${\times}1.5$ applied 3 by 3 filtering, showed reliable accuracy 35.47% k-value 0.20. However, error could be occurred because of the difference of land-use change and land-cover change. The actual rate of land-cover change deforestation area was 32% on administrative information. The 7.52% of forest management activities area was misjudged as deforestation by RS deforestation. Finally, the comparison of land-cover change deforestation (GIS deforestationII) with the RS deforestation accuracy, as a result NDVI mean-standard deviation${\times}2$ applied 3 by 3 filtering, showed improved accuracy 61.23%, k-value 0.23.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1663-1676
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• 2022

Recently, a number of deep-learning based land cover segmentation studies have been introduced. Some studies denoted that the performance of land cover segmentation deteriorated due to insufficient training data. In this study, we verified the improvement of land cover segmentation performance through data augmentation. U-Net was implemented for the segmentation model. And 2020 satellite-derived landcover dataset was utilized for the study data. The pixel accuracies were 0.905 and 0.923 for U-Net trained by original and augmented data respectively. And the mean F1 scores of those models were 0.720 and 0.775 respectively, indicating the better performance of data augmentation. In addition, F1 scores for building, road, paddy field, upland field, forest, and unclassified area class were 0.770, 0.568, 0.433, 0.455, 0.964, and 0.830 for the U-Net trained by original data. It is verified that data augmentation is effective in that the F1 scores of every class were improved to 0.838, 0.660, 0.791, 0.530, 0.969, and 0.860 respectively. Although, we applied data augmentation without considering class balances, we find that data augmentation can mitigate biased segmentation performance caused by data imbalance problems from the comparisons between the performances of two models. It is expected that this study would help to prove the importance and effectiveness of data augmentation in various image processing fields.

• The Journal of the Korea Contents Association
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• v.17 no.10
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• pp.72-84
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• 2017

This study aims to investigate how the service quality of a farm party affects the cognitive and emotional images of the farmhouse and revisit intentions by designing a research model and testing hypotheses. First, findings of the test show that when it comes to service quality, the physical environment and program contents of farm party have an effect on the cognitive image of the farmhouse while the qualification of party operators does not. Second, the physical environment of the party and party operator's qualification affect the emotional image but the program contents has no effect. Third, The cognitive and emotional images have an effect on the revisit intentions. It is certain that the farm party serves as cultural contents facilitating the rural economy and an emerging business model in the rural tourism. When we approach the farm party as a business model to provide service, not cultural contents as party, however, farmhouses may build a positive image as a new tourist destination and also see their economy facilitated. This study looks into Seoul and Gyeonggi areas and thus is geographically limited and does not cover national phenomenon.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4D
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• pp.569-577
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• 2008

The purpose of this study is focused on the development of compound classification process by mixing multitemporal data and annexing a specific image enhancement technique with a specific image classification algorithm, to gain more accurate land information from satellite imagery. That is, this study suggests the classification process using canonical correlation classification technique after principal component analysis for the mixed multitemporal data. The result of this proposed classification process is compared with the canonical correlation classification result of one date images, multitemporal imagery and a mixed image after principal component analysis for one date images. The satellite images which are used are the Landsat 5 TM images acquired on July 26, 1994 and September 1, 1996. Ground truth data for accuracy assessment is obtained from topographic map and aerial photograph, and all of the study area is used for accuracy assessment. The proposed compound classification process showed superior efficiency to appling canonical correlation classification technique for only one date image in classification accuracy by 8.2%. Especially, it was valid in classifying mixed urban area correctly. Conclusively, to improve the classification accuracy when extracting land cover information using Landsat TM image, appling canonical correlation classification technique after principal component analysis for multitemporal imagery is very useful.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.201-205
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• 2007

In the post-Cold War era, acquisition technique of high-resolution satellite imagery (HRSI) has begun to commercialize. IKONOS-2 satellite imaging data is supplied for the first time in the 21st century. Many researchers testified mapping possibility of the HRSI data instead of aerial photography. It is easy to renew and automate a topographical map because HRSI not only can be more taken widely and periodically than aerial photography, but also can be directly supplied as digital image. In this study matching size of IKONOS Geo-level stereo image is presented lot production of digital elevation model (DEM). We applied area based matching method using correlation coefficient of pixel brightness value between the two images. After matching line (where "matching line" implies straight line that is approximated to complex non-linear epipolar geometry) is established by exterior orientation parameters (EOPs) to minimize search area, the matching is tarried out based on this line. The experiment on matching size is performed according to land cover property, which is divided off into four areas (water, urban land, forest land and agricultural land). In each of the test areas, window size for the highest correlation coefficient is selected as propel size for matching. As the results of experiment, the proper size was selected as $123{\times}123$ pixels window, $13{\times}13$ pixels window, $129{\times}129$ pixels window and $81{\times}81$ pixels window in the water area, urban land, forest land and agricultural land, respectively. Of course, determination of the matching size by the correlation coefficient may be not absolute appraisal method. Optimum matching size using the geometric accuracy therefore, will be presented by the further work.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.4
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• pp.29-38
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• 2001

This study addresses the topic of suitability analysis for helping with land use planning, which is one of important decision-making in urban planning, utilizing geographic information system. Covering the Kumi City before integrating with neighbor county, the site suitabilities for land uses, which are categorized into residential, commercial, industrial and green, were analyzed using the overlay method based upon the database constructed for this study. In the process, assessment criteria which include environmental factors and relative weights were determined and also the land use/cover map and NDVI map which were generated through satellite image processing were included in the database. The suitability maps by four function spaces were derived according to the grade and compared with the present land use state and the land use concept map of urban master plan. For more accurate analysis, practical developing plan, land price data, soil data should be included. Also if the demand estimation data by each land use had been added, the reliability of location allocation could have been raised.

• Journal of Oral Medicine and Pain
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• v.41 no.3
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• pp.85-90
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• 2016

Purpose: The aim of this study was to develop an automated software to extract tooth and pulpal area from sectional cone-beam computed tomography (CBCT) images, which can guarantee more reproducible, objective and time-saving way to measure pulp/tooth volume ratio. Methods: The software program was developed using MATLAB (MathWorks). To determine the optimal threshold for the region of interest (ROI) extraction, user interface to adjust the threshold for extraction algorithm was added. Default threshold was determined after several trials to make the outline of extracted ROI fitting to the tooth and pulpal outlines. To test the effect of starting point location selected initially in the pulpal area on the final result, pulp/tooth volume ratio was calculated 5 times with different 5 starting points. Results: Navigation interface is composed of image loading, zoom-in, zoom-out, and move tool. ROI extraction process can be shown by check in the option box. Default threshold is adjusted for the extracted tooth area to cover whole tooth including dentin, cementum, and enamel. Of course, the result can be corrected, if necessary, by the examiner as well as by changing the threshold of density of hard tissue. Extracted tooth and pulp area are reconstructed three-dimensional (3D) and pulp/tooth volume ratio is calculated by voxel counting on reconstructed model. The difference between the pulp/tooth volume ratio results from the 5 different extraction starting points was not significant. Conclusions: In further studies based on a large-scale sample, the most proper threshold to present the most significant relationship between age and pulp/tooth volume ratio and the tooth correlated with age the most will be explored. If the software can be improved to use whole CBCT data set rather than just sectional images and to detect pulp canal in the original 3D images generated by CBCT software itself, it will be more promising in practical uses.

• Journal of the Korean Institute of Landscape Architecture
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• v.30 no.1
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• pp.1-10
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• 2002

The purpose of this article is to examine land use change in the fringe area of a metropolitan city through multi-temporal data analysis. Change detection has been regarded as one of the most important applications for utilization of remotely sensed imageries. Conventionally, two images were used for change detection, and Arithmetic calculators were generally used on the process. Meanwhile, multi-temporal change detection for a large number of images has been carried out. In this paper, a digital land-use map and three Landsat TM data were utilized for the multi-temporal change detection Each urban area map was extracted as a base map on the process of multi-temporal change detection. Each urban area map was converted to bit image by using boolean logic. Various urban change types could be obtained by stacking the urban area maps derived from the multi-temporal data using Geographic Information System(GIS). Urban change type map was created by using the process of piling up the bit images. Then the urban change type map was compared with each land cover map for the change detection. Dalseo-gu of Daegu city and Hwawon-eup of Dalsung-gun, the fringe area of Daegu Metropolitan city, were selected for the test area of this multi-temporal change detection method. The districts are adjacent to each other. Dalseo-gu has been developed for 30 yeais and so a large area of paddy land has been changed into a built-up area. Hwawon-eup, near by Dalseo-gu, has been influenced by the urbanization of Dalseo-gu. From 1972 to 1999, 3,507.9ha of agricultural area has been changed into other land uses, while 72.7ha of forest area has been altered. This agricultural area was designated as a 'Semi-agricultural area'by the National landuse Management Law. And it was easy for the preserved area to be changed into a built-up area once it would be included as urban area. Finally, the method of treatment and management of the preserved area needs to be changed to prevent the destruction of paddy land by urban sprawl on the urban fringe.