• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.5
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• pp.12-20
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• 2010

The purpose of this study is to evaluate human thermal comfort by spatial structure and to explore solutions to improve the thermal environment of a small urban space. The study site was Korea University campus. Thermal conditions were measured to evaluate the quality of the thermal environment in each type of space within the study site. Micrometeorology measurements, analysis of space characteristics for using fish-eye lens photography, and thermal comfort modeling through the use of collected meteorological data, such as temperature and humidity, were performed. Results showed that the level of thermal comfort for humans differs depending on the types of space within the study site. Thermal comfort is better in open spaces than enclosed in the aspect of radiative mean temperature, Predicted Mean Vote(PMV), and Physiologically Equivalent Temperature(PET). This fact is probably due to shadows or buildings or trees that may block solar radiation. Thus, it is necessary to consider the spatial arrangements of buildings and trees to enhance openness and ventilation in the space. Paving materials and exterior building materials should also be selected to lower the radiant temperature. Given these results, a quantitative evaluation on human thermal comfort could propose a way to plan user comfortable small urban spaces. Study methods used and results provided in the study can promote a better way for urban space planning direction to improve environmental quality.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.139-145
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• 2006

The advantage of the lidar data is in fast acquisition and process time as well as in high accuracy and high point density. However lidar data itself is difficult to classify the earth surface because lidar data is in the form of irregularly distributed point clouds. In this study, we investigated land cover classification using both lidar data and optical image through a supervised classification method. Firstly, we generated 1m grid DSM and DEM image and then nDSM was produced by using DSM and DEM. In addition, we had made intensity image using the intensity value of lidar data. As for optical images, the red, blue, green band of CCD image are used. Moreover, a NDVI image using a red band of the CCD image and infrared band of IKONOS image is generated. The experimental results showed that land cover classification with lidar data and optical image together could reach to the accuracy of 74.0%. To improve classification accuracy, we further performed re-classification of shadow area and water body as well as forest and building area. The final classification accuracy was 81.8%.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.1
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• pp.155-163
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• 2010

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on-board the NASA's Terra spacecraft provides along-track digital stereo image data at 15m resolution with a base-height ratio 0.6. Automated stereocorrelation procedure was implemented using the ENVI 4.1 software to derive DEMs with $15m{\times}15m$ in 43km long and 50km wide area using the ASTER stereo images. The accuracy of DEMs was analyzed in comparison with those which were obtained from digital topographic maps of 1:25,000 scale. Results indicate that RMSE in elevation between ${\pm}7$ and ${\pm}20m$ could be achieved. Excluding cloud, water and building areas as the factors which make RMSE value exceeding 10m, the accuracy of DEMs showed RMSE of ${\pm}5.789m$. Therefore for the purpose of elevating accuracy of topographic information, we intended to detect the cloud areas and shadow areas by a landcover classification method, remove those areas on the ASTER DEM and then replace with those areas detached from the cartographic DEM by band math.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.22-29
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• 2006

In this paper, we propose a block-based real-time people counting system that can be used in various environments including showing mall entrances, elevators and escalators. The main contributions of this paper are robust background subtraction, the block-based decision method and real-time processing. For robust background subtraction obtained from a number of image sequences, we used a mixture of K Gaussian. The block-based decision method was used to determine the size of the given objects (moving people) in each block. We divided the images into $6{\times}12$ blocks and trained the mean and variance values of the specific objects in each block. This was done in order to provide real-time processing for up to 4 channels. Finally, we analyzed various actions that can occur with moving people in real world environments.

• Korean Journal of Remote Sensing
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• v.28 no.2
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• pp.203-214
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• 2012

The physical environment of urban areas covered mostly by concrete and asphalt is the main cause of the urban heat island effect, primarily becoming apparent through increased land surface temperature. This study examined the effect of different urban land cover types on the land surface temperature using MODIS, Landsat ETM+ and RapidEye satellite data. As a result, the remote sensing based land surface temperature showed a marked difference according to the land use pattern in the case study of Ilsan new city. The high-rise apartment residential districts with less building-to-land ratio and higher green area ratio revealed lower land surface temperature than the low-story single-family housing districts characterized by relatively high building-to-land ratio and low green area ratio. From the view of climate zone and land cover types, there is a strong linear correlation between the impervious land cover ratio and the land surface temperature; the land surface temperature increases as the impervious built-up areas expand. In contrast, vegetation;water and shadow areas affect the decrease of land surface temperature. There is also a negative (-) correlation between NDVI and land surface temperature but the seasonal variation of NDVI can be hardly corrected.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.1-7
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• 2019

When using conventional 3D image scanning methods, it is common for image scanning to be done manually, which is labor-intensive. Scanning a space made up of complicated equipment or scanning a narrow space that is difficult for the user to enter, is problematic, resulting in quality degradation due to the presence of shadow areas. This paper proposes a method to scan an image using a rover equipped with a scanner in areas where it is difficult for a person to enter. To control the scan path precisely, the 3D image remote scan automation method based on the rover move rule definition is described. Through the study, the user can automate the 3D scan plan in a desired manner by defining the rover scan path as the rule base.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.21 no.6
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• pp.1-13
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• 2018

Mapping radiation heat flux of urban area is essential for urban design and landscape planning. Because controlling urban geometry and generating green space are important urban design strategies for reducing urban heat, urban planner and designer need to recognize the micro urban heat distribution for adequate urban planning. This study suggests a new methodology for mapping urban radiation heat flux in a micro scale considering buildings and trees' shade. For doing that, firstly, we calculate net radiation for each urban surfaces (building, road (not shaded, building shaded, tree shaded), ground (not shaded, building shaded, tree shaded), tree (not shaded, building shaded)). Then, by multiplying the area ratio of surfaces to the net radiation, we can obtain the radiation heat flux in micro-scale. The estimated net radiation results were found to be robust with a $R^2$ of 90%, which indicates a strong explanatory power of the model. The radiation heat flux map for 12h $17^{th}$ August explains that areas under the building and tree have lower net radiation heat flux, indicating that shading is a good strategy for reducing incident radiation. This method can be used for developing thermal friendly urban plan.

• Journal of Broadcast Engineering
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• v.26 no.1
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• pp.14-25
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• 2021

Change detection, which finds changes in remote sensing images of the same location captured at different times, is very important because it is used in various applications. However, registration errors, building displacement errors, and shadow errors cause false positives. To solve these problems, we propose a novle deep convolutional network called CADNet (Change Attention Dense Siamese Network). CADNet uses FPN (Feature Pyramid Network) to detect multi-scale changes, applies a Change Attention Module that attends to the changes, and uses DenseNet as a feature extractor to use feature maps that contain both low-level and high-level features for change detection. CADNet performance measured from the Precision, Recall, F1 side is 98.44%, 98.47%, 98.46% for WHU datasets and 90.72%, 91.89%, 91.30% for LEVIR-CD datasets. The results of this experiment show that CADNet can offer better performance than any other traditional change detection method.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.2
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• pp.1-22
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• 2022

The modification effects of street trees on outdoor thermal comfort in summertime according to tree planting types and road direction were analyzed using a computer simulation program, ENVI-met. With trees, the air temperature and wind speed decreased, and the relative humidity increased. In the case of mean radiant temperature (T_mrt) and human thermal sensation, physiological equivalent temperature (PET) and universal thermal climate index (UTCI), there was a decrease during the daytime. The greatest change among the meteorological factors by trees happened in Tmrt, and PET and UTCI showed similar patterns with T_mrt·The most effective tree planting type on thermal comfort modification was low tree height, wide tree crown, high leaf area index, and narrow planting interval (LWDN). T_mrt, PET and UTCI showed a large difference depending on shadow patterns of buildings and trees according to solar altitude and azimuth angles, and building locations. When the building shade areas increased, the thermal modification effect by trees decreased. In particular, results on the east and west sidewalks showed a large deviation over time. When applying the LWDN, the northwest, west and southwest sidewalks showed a significant reduction of 8.6-12.3℃ PET and 4.2-4.5℃ UTCI at 10:00, and the northeast, east and southeast sidewalks showed 8.1-11.8℃ PET and 4.4-5.0℃ UTCI at 16:00. On the other hand, when the least effective type (high tree height, narrow tree crown, low leaf area index, and wide planting interval) was applied, the maximum reduction was up to 1.8℃ PET and 0.9℃ UTCI on the eastern sidewalks, and up to 3.0℃ PET and 0.9℃ UTCI on the western ones. In addition, the difference in modification effects on T_mrt, PET and UTCI between the tree planting types was not significant when the tree effects were reduced by the effects of buildings. These results can be used as basic data to make the most appropriate street tree planting model for thermal comfort improvement in urban areas in summer.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.5
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• pp.363-371
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• 2015

Feature extraction is one of the main goals in many remote sensing analyses. After high-resolution imagery became more available, it became possible to extract more detailed and specific features. Thus, considerable image segmentation algorithms have been developed, because traditional pixel-based analysis proved insufficient for high-resolution imagery due to its inability to handle the internal variability of complex scenes. However, the individual segmentation method, which simply uses color layers, is limited in its ability to extract various target features with different spectral and shape characteristics. Spectral indices can be used to support effective feature extraction by helping to identify abundant surface materials. This study aims to evaluate a feature extraction method based on a segmentation technique with spectral indices. We tested the extraction of diverse target features-such as buildings, vegetation, water, and shadows from eight band WorldView-2 satellite image using decision tree classification and used the result to draw the appropriate spectral indices for each specific feature extraction. From the results, We identified that spectral band ratios can be applied to distinguish feature classes simply and effectively.