• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.4
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• pp.469-476
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• 2009

The new laser scanning technology allows to attain 3D information faster with higher accuracy on surface ground, vegetation and buildings of the earth surface. This acquired information can be used in many areas after modifying them appropriately by users. The contour production for accurate landform is an advanced technology that can reveal the mountain area landscapes hidden by the trees in detail. However, if extremely precise LiDAR data is used in constructing the contour, massive-sized data intricates the contour diagram and could amplify the data size inefficiently. This study illustrates the algorithm producing contour that is filtered in stages for more efficient utilization using the LiDAR contour produced by the detailed landscape data. This filtering stages allow to preserve the original landscape shape and to keep the data size small. Point Filtering determines the produced contour diagram shape and could minimize data size. Thus, in this study we compared experimentally filtered contour with the current digital map(1:5,000).

• Korean Journal of Environment and Ecology
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• v.24 no.2
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• pp.186-193
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• 2010

In order to examine the traits of sluice gate water control, halophyte community formation and their inter-relations in Saemangeum, both water level condition and halophyte community formation were analyzed periodically and spatially on the topographic map with Surfer, Saemageum Spatial Analysis System, and related field reports. The traits of water level condition are that average water level in the growing period of halophytes was similar to annual average water level, annual low level and high level appeared in the growing period, and water level was usually maintained within a range of -1.0m~0.5m above mean sea level, but it has changed more frequently year by year. Routine water level control, natural disaster prevention, construction, and civil appeal took major percentages of the reasons for sluice gate's opening and shutting. Since 2007, not only the overall control frequency of sluice gate but also its control frequency for construction and natural disaster prevention have increased outstandingly. Halophyte community had formed at a rate of 1,209ha/year in the 4,315 ha land in 2008, 6.3 times larger than in 2005, and 2,382 ha above around 1.0m was estimated to be artificially vegetated, 89.1 % of the 2,673ha-size sown area. High water level was found to be a more possible determinant than average water level or low water level in halophyte community formation and it was thought to be secondary factors whether tillage was conducted or/and whether surface sealing formed.

• Journal of Korean Society of Forest Science
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• v.78 no.3
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• pp.263-273
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• 1989

Accurate and cost-effective classification of forest vegetation is the primary goal for forest management and utilization of forest resources. Aerial photograph and remote sensing are the most frequent and effective method in forest resources inventories. TM and MSS are the principal observing instruments on the Landsat-4 and -5 earth observing satellite. Especially TM has considerably greater spatial, spectral, and radiometric resolution power than MSS, that is, the IFOV of TM at a nadir is 30m compared to 80m for MSS. In this study, we used TM data to classify forest types and compared the result with forest type map manufactured by interpretation of B/W infrared photographs. As a result, land use types were well defined with TM data. But classifying forest types was a little difficult and indistinct. However, the spectral signatures of forest in every season and growing stages remained as problems to be solved, and also the most effective selection and combination method of bands for differentiating the spectral plots among classes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.289-297
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• 2009

In the paper, we propose the methodology to extract training dataset automatically for supervised classification of road networks. For the preprocessing, we co-register the airborne photos, LIDAR data and large-scale digital maps and then, create orthophotos and intensity images. By overlaying the large-scale digital maps onto generated images, we can extract the initial training dataset for the supervised classification of road networks. However, the initial training information is distorted because there are errors propagated from registration process and, also, there are generally various objects in the road networks such as asphalt, road marks, vegetation, cars and so on. As such, to generate the training information only for the road surface, we apply the Expectation Maximization technique and finally, extract the training dataset of the road surface. For the accuracy test, we compare the training dataset with manually extracted ones. Through the statistical tests, we can identify that the developed method is valid.

• Journal of The Geomorphological Association of Korea
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• v.15 no.2
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• pp.85-94
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• 2008

This study is to construe spatio-temporal characteristics of temperature in cities and changes of climatical regions in analyzing a change of Korea Peninsular climate. We used daily mean air temperature data which was collected in South and North Korea for the past 34 years from 1974 to 2007. We created temperature map of 500m resolution using Inverse Distance Weight in application with adiabatic lapse rate per month in linear relation with height and temperature. In the urbanization area, the data analyzed population in comparison with temperature changes by the year. An annual rising rate of temperature was calculated $0.0056^{\circ}C$, and the temperature was increased $2.14^{\circ}C$ from 1974 to 2107. The south climate region in Korea by the Warmth index was expanded to the middle climate region by the latitude after 1990s. A rise of urban area in mean temperature was $0.5-1.2^{\circ}C$, Seoul, metropolitan and cities which were high density of urbanization and industrialization with the population increase between 1980s and 1990s. In case of North Korea, Cities were Pyeongyang, Anju, Gaecheon, Hesan. A rise in cities areas in mean temperature has influence on vegetation, especially secondary growth such as winter buds of pine trees appears built-up area and outskirts in late Autumn. Finally, nowaday we confront diverse natural events over climatical changes, We need a long-term research to survey and analyze an index on the climatical changes to present a systematic approach and solution in the future.

• Journal of the Korean earth science society
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• v.40 no.2
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• pp.119-134
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• 2019

In order to analyze the observational environment of solar radiation stations operated by the Korea Meteorological Administration (KMA), we used the digital elevation model (DEM) and the solar radiation model to calculate a topographical shading, sky view factor (SVF) and solar radiation by surrounding terrain. The sky line and SVF were calculated using high resolution DEM around 25 km of the solar stations. We analyzed the topographic effect by analyzing overlapped solar map with sky line. Particularly, Incheon station has low SVF whereas Cheongsong and Chupungryong station have high SVF. In order to validation the contribution of topographic effect, the solar radiation calculated using GWNU solar radiation model according to the sky line and SVF under the same meteorological conditions. As a result, direct, diffuse and global solar radiation were decreased by 12.0, 5.6, and 4.7% compared to plane surface on Cheongsong station. The 6 stations were decreased amount of mean daily solar radiation to the annual solar radiation. Among 42 stations, eight stations were analyzed as the urgent transfer stations or moving equipment quickly and more than half of stations (24) were required to review the observational environment. Since the DEM data do not include artifacts and vegetation around the station, the stations need a detail survey of observational environment.

• Journal of Convergence for Information Technology
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• v.11 no.1
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• pp.136-142
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• 2021

Open-pit mine development requires continuous management because of topographical changes and there is a risk of accidents if the current status survey is performed directly in the process of calculating the earthwork. In this study, the application of UAV photogrammetry, which can acquire spatial information without direct human access, was applied to open-pit mines development area and analyzed the accuracy, earthwork, and mountain restoration plan to determine its applicability. As a result of accuracy analysis at checkpoint using ortho image and Digital Surface Model(DSM) by UAV photogrammetry, Root Mean Square Error(RMSE) is 0.120 m in horizontal and 0.150 m in vertical coordinates. This satisfied the tolerance range of 1:1,000 digital map. As a result of the comparison of the earthwork, UAV photogrammetry yielded 11.7% more earthwork than the conventional survey method. It is because UAV photogrammetry shows more detailed topography. And result of monitoring mountain restoration showed possible to determine existence of rockfall prevention nets and vegetation. If the terrain changes are monitored by acquiring images periodically, the utility of UAV photogrammetry will be further useful to open-pit mine development.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.225-236
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• 2022

Urbanization due to population growth and regional development can cause various environmental problems, such as the urban heat island phenomenon. A planned city is considered an appropriate study site to analyze changes in urban climate caused by rapid urbanization in a short-term period. In this study, changes in land cover and surface heat island phenomenon were analyzed according to the development plan in Sejong City from 2013 to 2020 using Landsat-8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) satellite imagery. The surface temperature was calculated in consideration of the thermal infrared band value provided by the satellite image and the emissivity, and based on this the surface heat island effect intensity and Urban Thermal Field Variance Index (UTFVI) change analysis were performed. The level-2 land cover map provided by the Ministry of Environment was used to confirm the change in land cover as the development progressed and the difference in the surface heat island intensity by each land cover. As a result of the analysis, it was confirmed that the urbanized area increased by 15% and the vegetation decreased by more than 28%. Expansion and intensification of the heat island phenomenon due to urban development were observed, and it was confirmed that the ecological level of the area where the heat island phenomenon occurred was very low. Therefore, It can suggest the need for a policy to improve the residential environment according to the quantitative change of the thermal environment due to rapid urbanization.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.597-608
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• 2022

Remotely sensed data have been used in various fields, such as disasters, agriculture, urban planning, and the military. Recently, the demand for the multitemporal dataset with the high-spatial-resolution has increased. This manuscript proposed an automatic image matching algorithm using a deep learning technique to utilize a multitemporal remotely sensed dataset. The proposed deep learning model was based on High Resolution Net (HRNet), widely used in image segmentation. In this manuscript, denseblock was added to calculate the correlation map between images effectively and to increase learning efficiency. The training of the proposed model was performed using the multitemporal orthophotos of the National Geographic Information Institute (NGII). In order to evaluate the performance of image matching using a deep learning model, a comparative evaluation was performed. As a result of the experiment, the average horizontal error of the proposed algorithm based on 80% of the image matching rate was 3 pixels. At the same time, that of the Zero Normalized Cross-Correlation (ZNCC) was 25 pixels. In particular, it was confirmed that the proposed method is effective even in mountainous and farmland areas where the image changes according to vegetation growth. Therefore, it is expected that the proposed deep learning algorithm can perform relative image registration and image matching of a multitemporal remote sensed dataset.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.883-896
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• 2023

As human activities in Korea are spread throughout the mountains, forest fires often affect residential areas, infrastructure, and other facilities. Hence, it is necessary to detect fire-damaged areas quickly to enable support and recovery. Remote sensing is the most efficient tool for this purpose. Fire damage detection experiments were conducted on the east coast of Korea. Because this area comprises a mixture of forest and artificial land cover, data with low resolution are not suitable. We used Sentinel-2 multispectral instrument (MSI) data, which provide adequate temporal and spatial resolution, and the k-nearest neighbor (kNN) algorithm in this study. Six bands of Sentinel-2 MSI and two indices of normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as features for kNN classification. The kNN classifier was trained using 2,000 randomly selected samples in the fire-damaged and undamaged areas. Outliers were removed and a forest type map was used to improve classification performance. Numerous experiments for various neighbors for kNN and feature combinations have been conducted using bi-temporal and uni-temporal approaches. The bi-temporal classification performed better than the uni-temporal classification. However, the uni-temporal classification was able to detect severely damaged areas.