• Journal of Korean Society for Atmospheric Environment
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• v.25 no.5
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• pp.432-449
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• 2009

In this study, the effects of high-resolution land cover on the simulation of near-surface meteorological fields were evaluated in two different coastal regions using Weather Research and Forecasting (WRF) model. These analyses were performed using the middle classification land cover data upgraded by the Korean Ministry of Environment (KME). For the purpose of this study, two coastal areas were selected as follows: (1) the southwestern coastal (SWC) region characterized by complex shoreline and (2) the eastern coastal (EC) region described a high mountain and a simple coastline. The result showed that the application of high-resolution land cover were found to be notably distinguished between the SWC and EC regions. The land cover improvement has contributed to generate the realistic complex coastline and the distribution of small islands in the SWC region and the expansion of urban and built-up land along the sea front in the EC region, respectively. The model study indicated that the improvement of land cover caused a temperature change on wide areas of inland and nearby sea for the SWC region, and narrow areas along the coastal line for the EC region. These temperature variations in the two regions resulted in a decrease and an increase in land-breeze and sea-breeze intensity, respectively (especially the SWC region). Interestingly, the improvement of land cover can contribute large enough to change wind distributions over the sea in coastal areas.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1858-1872
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• 2023

With the advance of radar technologies, the availability of synthetic aperture radar (SAR) images increases. To improve application of SAR images, a management system for SAR images is proposed in this paper. The system provides trainable land cover classification module and display of SAR images on the map. Users of the system can create their own classifier with their data, and obtain the classified results of newly captured SAR images by applying the classifier to the images. The classifier is based on convolutional neural network structure. Since there are differences among SAR images depending on capturing method and devices, a fixed classifier cannot cover all types of SAR land cover classification problems. Thus, it is adopted to create each user's classifier. In our experiments, it is shown that the module works well with two different SAR datasets. With this system, SAR data and land cover classification results are managed and easily displayed.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.580-583
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• 2007

Various matching methods have been introduced by investigators to improve digital elevation model (DEM) accuracy of satellite imagery. This study proposed an area-based matching method according to land cover property using correlation coefficient of pixel brightness value between the two images for DEM generation from IKONOS stereo imagery. For this, matching line (where "matching line" implies straight line that is approximated to complex nonlinear epipolar geometry) is established by exterior orientation parameters to minimize search area. The matching is carried out based on this line. Land cover classes are divided off into water, urban land, forest and agricultural land. Matching size is selected using a correlation-coefficient image in the four areas. The selected sizes are $81{\times}81$ pixels window, $21{\times}21$ pixels window, $119{\times}119$ pixels window and $51{\times}51$ pixels window in the water area, urban land, forest land and agricultural land, respectively. And hence, DEM is generated from IKONOS stereo imagery using the selected matching sizes and land cover map on the four types.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.2
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• pp.77-86
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• 2012

This study was aim to predict future land-cover changes and to analyze regional land-cover changes in irrigation areas and agricultural reservoir watersheds under climate change scenario. To simulate the future land-cover under climate change scenario - A1B of the SRES (Special Report on Emissions Scenarios), Dyna-CLUE (Conversion of Land Use Change and its Effects) was applied for modeling of competition among land-use types in relation to socioeconomic and biophysical driving factors. For the study areas, 8 agricultural reservoirs were selected from 8 different provinces covering all around nation. The simulation results from 2010 to 2100 suggested future land-cover changes under the scenario conditions. For Madun reservoir in Gyeonggi-do, total decrease amount of paddy area was a similar amount of 'Base demand scenario' of Water Vision 2020 published by MLTMA (Ministry of Land, Transport and Maritime Affairs), while the decrease amounts of paddy areas in other sites were less than the amount of 'High demand scenario' of Water Vision 2020. Under A1B scenario, all the land-cover results showed only slight changes in irrigation areas of agricultural reservoirs and most of agricultural reservoir watersheds will be increased continuously for forest areas. This approach could be useful for evaluating and simulating agricultural water demand in relation to land-use changes.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.165-168
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• 2005

In this study, emissivity and land surface temperature (LST) were retrieved using the previously developed algorithms and Aqua/MODIS data. And sensitivity of estimated emissivity and LST to the predefined values, such as land cover, normalized difference vegetation index (NOVI) and spectral emissivity were investigated. The methods used for emissivity and LST were vegetation cover method (VCM) and four different split-window algorithms. The spectral emissivity retrieved by VCM was not sensitive to the NOVI error but more sensitive to the land cover error. The comparison of LST showed that the LST was systematically different without regard to the land cover and season. And the LST was very sensitive to the emissivity error excepting the Uliveri et al. This preliminary result indicates that more works are needed for the retrieval of reliable LST from satellite data.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.508-510
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• 2003

Land cover change has been recognized as one of the most important factors influencing the occurrence of rainfall-triggered landslides. Satellite remote sensing provides detailed information regarding the spatial distribution and extent of land cover/use changes. This study describes the land cover changes in Nagasaki City, Japan and Kangnung City, South Korea. The former has been suffered from rainfall-triggered disasters for long term and latter was damaged by Typhoon Rusa in 2002. The results obtained from both study areas clearly show that land cover changes have occurred in the last decade as a result of both natural forces and human activities.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.242-242
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• 2015

Monitoring the land cover changes in Nakdong River Basins using the multi-temporal remote sensing datasets is necessary for preserving properties in the river basins and monitoring the environmental changes in the river basins after the 4 major river restoration project. This research aims to monitor the land cover changes using the multi-temporal Landsat imageries and the airborne topographic LiDAR data. Firstly, the river basin boundaries are determined by using the LiDAR data, and the multiple river basin imageries are generated from the multi-temporal Landsat imageries by using the river basin boundaries. Next the classification method is employed to identify the multiple land covers in the generated river basin imageries. Finally, monitoring the land cover changes is implemented by comparing the differences of the same clusters in the multi-temporal river basin imageries.

• Spatial Information Research
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• v.2 no.1
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• pp.47-51
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• 1994

The purpose of the study is to establ ish models of land Cover (use) prediction system for development and management of land resources using remotely sensed data as well as ancillary data in the context of multi-dis¬ciplinary approach in the application to CheJoo Island. The model adopts multi-date processing techniques and is a spatial/temporal land-Cover projection strategy emerged as a synthesis of the probability tra-nsition model and the discrimnant-analys is model. A discriminant modelis applied to all pixels in CheJoo landscape plane to predict the most likely change in land Cover. The probability transition model provides the number of these pixels that will convert to different land Cover in a given future time increment. The syntheric model predicts the future change in land Cover and its volume of pixels in the landscape plane.

• Journal of Forest and Environmental Science
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• v.39 no.3
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• pp.167-179
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• 2023

The extent of change in the Land use/Land cover (LULC) of Okomu National Park (ONP) and fringe communities was evaluated. High resolution Landsat imagery was used to identify the major vegetation cover/land use systems and changes around the national park and fringe communities while field visits/ground truthing, involving the collection of coordinates of the locations was carried out to ascertain the various land cover/land use types identified on the images, and the extent of change over three-time series (2000, 2010 and 2020). The change detection was analyzed using area calculation, change detection by nature and normalized difference vegetation index (NDVI). The result of the classification and analysis of the LULC Change of ONP and fringe communities revealed an alarming rate of encroachment into the protected area. All the classification features analyzed had notable changes from 2000-2020. The forest, which was the dominant LULC feature in 2000, covering about 66.19% of the area reduced drastically to 36.12% in 2020. Agricultural land increased from 6.14% in 2000 to 34.06% in 2020 while vegetation (degraded land) increased from 27.18% in 2000 to 38.89% in 2020. The magnitude of the change in ONP and surroundings showed the forest lost -247.136 km² (50.01%) to other land cover classes with annual rate change of 10%, implying that 10% of forest land was lost annually in the area for 20 years. The NDVI classification values of 2020 indicate that the increase in medium (399.62 km² ) and secondary high (210.17 km² ) vegetation classes which drastically reduced the size of the high (38.07 km² ) vegetation class. Consequent disappearance of the high forests of Okomu is inevitable if this trend of exploitation is not checked. It is pertinent to explore other forest management strategies involving community participation.

• Journal of Environmental Science International
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• v.19 no.9
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• pp.1103-1108
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• 2010

This study was conducted to be used as basic data of environmental friendly construction planning by comparing and analyzing thermal environment, find particles and biotope area rate according to land cover types of outside space of schools located in Chung-ju. When meteorological factors were analyzed according to land cover types, for temperature planting area and paved area showed low-and high-temperature ranges, respectively, and relative humidity was negatively related with temperature as low-and high-temperature ranges corresponded to high-and low-humidity ranges, respectively. For Wet Bulb Globe Temperature Index (WBGT) by land cover types, it was observed to be artificial grass> bare land> natural grass. Find particles were different according to land cover types of playground with being bare land> artificial grass> natural grass in the order. Bare land playground, where there were artificial factors and no absorption of fine particles through stomata of leaves as a function of natural circulation, recorded the highest level of $39.8\;{\mu}g/m^3$ and the level was relatively higher compared to the levels by season in Chung-ju. Biotope area rate showed the order of M elementary school> K elementary school> C commercial high school. That was considered to be caused by the difference of land cover type of school playground accounting for a large part of a school.