• Ecology and Resilient Infrastructure
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• v.3 no.1
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• pp.46-53
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• 2016

This study was conducted to analyze the effect of the different land covers of an urban park (Hyowon park) in downtown Suwon on the urban thermal variations during a hot summer. The effect of the air temperature reduction in the urban park was 4.4%-4.5% for the downtown residence (Maetan-dong). This value was about 0.8% lower than that of the outskirts residence (Sanggwanggyo-dong). The daily mean temperature, daily maximum temperature, summer day and heat wave frequency were measured under the different land covers (cement-block, grass, pine-grass, shading area and mixed forest) showed these values generally decreased under natural land cover types. Daily minimum temperature and tropical night frequency didn't seem to correlate with the land cover types. Means of thermal comfort indices (wet bulb globe temperature, heat index and discomfort index) in the shading area, mixed forest and the pine-grass types were lower than those of cement block and grass types. However the levels of those indices were equal to 'very high' or 'caution' levels in the afternoon (13:00-15:00). In the morning (06:00-08:00), thermal comfort indices of the urban park didn't correlate with land cover types. Therefore, to reduce heat stress and to improve the thermal comfort in urban parks, an increase in the area of natural land cover such as grass, forest and open spaces is required.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.553-563
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• 2006

This study aims to produce land-cover maps of Korean peninsula using multi-temporal MODIS (Moderate Resolution Imaging Spectroradiometer) imagery. To solve the low spatial resolution of MODIS data and enhance classification accuracy, Linear Spectral Mixture Analysis (LSMA) was employed. LSMA allowed to determine the fraction of each surface type in a pixel and develop vegetation, soil and water fraction images. To eliminate clouds, MVC (Maximum Value Composite) was utilized for vegetation fraction and MinVC (Minimum Value Composite) for soil fraction image respectively. With these images, using ISODATA unsupervised classifier, southern part of Korean peninsula was classified to low and mid level land-cover classes. The results showed that vegetation and soil fraction images reflected phenological characteristics of Korean peninsula. Paddy fields and forest could be easily detected in spring and summer data of the entire peninsula and arable land in North Korea. Secondly, in low level land-cover classification, overall accuracy was 79.94% and Kappa value was 0.70. Classification accuracy of forest (88.12%) and paddy field (85.45%) was higher than that of barren land (60.71%) and grassland (57.14%). In midlevel classification, forest class was sub-divided into deciduous and conifers and field class was sub-divided into paddy and field classes. In mid level, overall accuracy was 82.02% and Kappa value was 0.6986. Classification accuracy of deciduous (86.96%) and paddy (85.38%) were higher than that of conifers (62.50%) and field (77.08%).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_2
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• pp.587-597
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• 2007

This study determines matching size for digital elevation model (DEM) production according to land cover property from IKONOS Geo-level stereo image. 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 to minimize search area, the matching is carried out based on this line. The experiment 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, matching size is selected using a correlation-coefficient image and parallax image. As the results, optimum matching size of the images was selected as $81{\times}81$ 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.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.2
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• pp.107-118
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• 2010

The purpose of this study was to set the boundary of the coastal sand dunes and to analyze the change characteristics of land cover types using aerial photographs on Osan and Dongho coastal sand dunes in Yangyang. The boundaries of sand dunes were established using digital soil map, and land cover maps were made for each year using aerial photographs. As results of analysis, both beach and farmland areas have been decreased, since 1974 and forest area was relatively increased due to planting and forest growth. Facilities and bare land have been greatly increased since 1992. Loss of wetland, and beach due to these changes had an impact on the ecosystem destruction of sand dunes.

• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.409-423
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• 2023

North Korea is carrying out reclamation activities in tidal flat areas distributed throughout the west coast. Previousremote sensing research on North Korean tidal flats either failsto reflect recent trends or focuses on identifying and analyzing tidal flats. Thisstudy aimsto quantify the impact of recent reclamation activitiesin North Korea's coastal areas and contribute knowledge useful for determining the best remote sensing methods for coastal areas with limited accessibility, such as those in North Korea. Using Landsat-8 OLI images from 2014-2022, we analyzed land cover changesin an area on the west coast of Pyeonganbuk-do where reclamation activities are underway. Unsupervised classification using the normalized difference water index and the random forest classification technique were each used to divide the study area into classification groups, and changes in their areas over time were analyzed. The resultsshow a clear decrease in the water area and a tendency to increase cultivated area,supporting the evidence that North Korea'sreclamation isfor agricultural land expansion.Along coasts behind seawalls, the water area decreased by nearly half, and the cultivated area increased by over 2,300%, indicating significant changes and highlighting the anthropogenic nature of the cover changes due to reclamation. Both methods demonstrated high accuracy, making them suitable for detecting cover changes caused by reclamation. It is expected that further quality research will be conducted through the use of high-resolution satellite images and by combining data from multiple satellites in the future.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2001.06a
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• pp.22-25
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• 2001

인간의 개발활동으로 인하여 자연적인 토지피복 및 식생, 토지이용형태의 변화가 일어나고 그로 인하여 과거 1차 생산 중심의 농업지역들이 공업 및 상업이 가미된 도시지역으로 발전하면서 토양유실량의 변화를 포함한 여러 수문 환경이 변화하고, 환경문제로도 대두되고 있다.(중략)

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2001.06a
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• pp.147-150
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• 2001

최근 넓은 지역을 대상으로 토지이용 및 식생분포 등을 조사하기 위하여 인공위성 원격탐사기술이 활발히 사용되고 있다. 위성화상자료를 이용한 토지이용분석 사례는 다양한 분야에서 발견되는데, 미국지질청(USGS)의 EROS 데이터센터, 네브라스카 대학, 유럽공동체에서는 NASA의 도움을 받아 전 지구의 지표피복을 1km 해상도로 분류한 바 있다(http://edcdaac.usgs.gov).(중략)

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2017.11a
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• pp.73-74
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• 2017

• Atmosphere
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• v.17 no.2
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• pp.159-169
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• 2007

A comparison of the three land cover data sets (United States Geological Survey: USGS, International Geosphere Biosphere Programme: IGBP, and University of Maryland: UMd), derived from 1992-1993 Advanced Very High Resolution Radiometer(AVHRR) data sets, was performed over the Asian continent. Preprocesses such as the unification of map projection and land cover definition, were applied for the comparison of the three different land cover data sets. Overall, the agreement among the three land cover data sets was relatively high for the land covers which have a distinct phenology, such as urban, open shrubland, mixed forest, and bare ground (>45%). The ratios of triple agreement (TA), couple agreement (CA) and total disagreement (TD) among the three land cover data sets are 30.99%, 57.89% and 8.91%, respectively. The agreement ratio between USGS and IGBP is much greater (about 80%) than that (about 32%) between USGS and UMd (or IGBP and UMd). The main reasons for the relatively low agreement among the three land cover data sets are differences in 1) the number of land cover categories, 2) the basic input data sets used for the classification, 3) classification (or clustering) methodologies, and 4) level of preprocessing. The number of categories for the USGS, IGBP and UMd are 24, 17 and 14, respectively. USGS and IGBP used only the 12 monthly normalized difference vegetation index (NDVI), whereas UMd used the 12 monthly NDVI and other 29 auxiliary data derived from AVHRR 5 channels. USGS and IGBP used unsupervised clustering method, whereas UMd used the supervised technique, decision tree using the ground truth data derived from the high resolution Landsat data. The insufficient preprocessing in USGS and IGBP compared to the UMd resulted in the spatial discontinuity and misclassification.

• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.671-680
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• 2018

Compared to the imagery produced by traditional satellites, PlanetScope satellite imagery has made it possible to easily capture remotely-sensed imagery every day through dozens or even hundreds of satellites on a relatively small budget. This study aimed to detect changed areas and update a land cover map using a PlanetScope image. To generate a classification map, pixel-based Random Forest (RF) classification was performed by using additional features, such as the Normalized Difference Water Index (NDWI) and the Normalized Difference Vegetation Index (NDVI). The classification result was converted to vector data and compared with the existing land cover map to estimate the changed area. To estimate the accuracy and trends of the changed area, the quantitative quality of the supervised classification result using the PlanetScope image was evaluated first. In addition, the patterns of the changed area that corresponded to the classification result were analyzed using the PlanetScope satellite image. Experimental results found that the PlanetScope image can be used to effectively to detect changed areas on large-scale land cover maps, and supervised classification results can update the changed areas.