• Korean Journal of Remote Sensing
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• v.35 no.6_4
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• pp.1403-1415
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• 2019

Urban population growth and consequent rapid urbanization involve some thermal environmental problems in the cities. Monitoring of thermal environments in urban areas such as hot spot analysis is required for effective actions to resolve these problems. This study selected 14 dongs and surrounding administrative districts of Sejong city as study areas and analyzed the characteristics of changes in surface temperature due to the urban expansion in the summer from 2013 to 2018. In the study, the surface temperature distributions in the study areas were plotted using surface temperature values from Landsat 8 and NDVI (Normalized Difference Vegetation Index) and NDBI (Normalized Difference Built-up Index) based on KOMPSAT 2/3 data, and the patterns of surface temperature changes with urban expansion were discussed using the estimated NDVI and NDBI. In particular, the distinct urbanization in the study areas were selected for case studies, and the cause of the changes in the hot spots in the regions was analyzed using high-resolution KOMPSAT images. This study results present that hot spots appeared in urbanized regions within the study areas, and it was plotted that the lower the NDVI values and the higher the NDBI values indicate the temperature values are high. The land surface temperature and satellite-based products were used to divide the study areas into continuously urbanized regions and rapidly urbanized regions and to identify the different characteristics depending on land covers. In the regions with distinct surface temperature changes by urbanization, the analysis using high-resolution KOMPSAT images as presented in this study could provide effective information for urban planning and policy utilization in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.3
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• pp.61-74
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• 2016

The purpose of this paper is to analyze the relationship between the location of the epicenter of a medium-sized earthquake(magnitude 4.8) that occurred on January 20, 2007 in the Odaesan area with lineament features using a shaded relief map(1/25,000 scale) and satellite images from LANDSAT-8 and KOMPSAT-2. Previous studies have analyzed lineament features in tectonic settings primarily by examining two-dimensional satellite images and shaded relief maps. These methods, however, limit the application of the visual interpretation of relief features long considered as the major component of lineament extraction. To overcome some existing limitations of two-dimensional images, this study examined three-dimensional images, produced from a Digital Elevation Model and drainage network map, for lineament extraction. This approach reduces mapping errors introduced by visual interpretation. In addition, spline interpolation was conducted to produce density maps of lineament frequency, intersection, and length required to estimate the density of lineament at the epicenter of the earthquake. An algorithm was developed to compute the Value of the Relative Density(VRD) representing the relative density of lineament from the map. The VRD is the lineament density of each map grid divided by the maximum density value from the map. As such, it is a quantified value that indicates the concentration level of the lineament density across the area impacted by the earthquake. Using this algorithm, the VRD calculated at the earthquake epicenter using the lineament's frequency, intersection, and length density maps ranged from approximately 0.60(min) to 0.90(max). However, because there were differences in mapped images such as those for solar altitude and azimuth, the mean of VRD was used rather than those categorized by the images. The results show that the average frequency of VRD was approximately 0.85, which was 21% higher than the intersection and length of VRD, demonstrating the close relationship that exists between lineament and the epicenter. Therefore, it is concluded that the density map analysis described in this study, based on lineament extraction, is valid and can be used as a primary data analysis tool for earthquake research in the future.

• Journal of the Korean Geographical Society
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• v.38 no.4
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• pp.630-639
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• 2003

This study aims to analysis the distribution and change of cropland and forest, the Onseong, Saebyeol, and Eundeok counties on the lower reach of Duman(Tumen) river, northeast Korea, using 1992 year Landsat TM data, 2000 year Landsat ETM data, and digital terrain elevation data(DTED). Land cover and land use of the study areas are classified into cropland, forest, village, and water body, using the supervised classification method including 1:50,000 DTED analysis, image band composition, and principal component analysis(PCA). Results of quantitative analysis present that each growth rate of cropland of Onseong and Eundeok are 22.8% and 14.7% corresponding to decreasing rates of forest, 8% and 13.6% during 8 years from 1992 to 2000. In Onseong, Saebyeol, and Eundeok, each values of mean elevations and slope gradients increased to 192m, 95m, and 91m from 157m, 85m, and 78m, and to 6.6$^{\circ}$, 3.0$^{\circ}$, and 4.4$^{\circ}$ from 5.2$^{\circ}$, 2.5$^{\circ}$, and 3.0$^{\circ}$. Especially, in case of newly developed cropland, the values of mean elevation and mean gradient have 225m, 122m, and 127m, and 9.4$^{\circ}$, 5.1$^{\circ}$, and 8.0$^{\circ}$, in above three regions. These new croplands were developing along to deeper valleys and toward lower hill and mountain slope up to knickpoint zone of gradient change. Deforested lands for cropland have formed irregular pattern of patch-type, and become sources for the sheet erosion, rilling and gulleying in mountain slope and sedimentation in local river channel. Though there were no field checking, analysis using landsat images and GIS mapping can help understand actual environmental problems relating to cropland development of mountain slope in North Korea.

• Korean Journal of Remote Sensing
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• v.8 no.2
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• pp.131-145
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• 1992

A low cost personal computer and image processing S/W were empolyed to derive Digtal Elevation Model(DEM) of tidal flat from multitemporal LANDSAT TM images, and to create three-dimensional(3D) perspective views of the tidel flat on Komso bay in west coasts of Korea. The method for generation of Digital Elevation Model(DEM) in tidal flat was considered by overlapping techniques of multitemporal LANDSAT TM images and interpolations. The boundary maps of tidal flat extracted from multitemporal images with different water high were digitally combined in x, y, z space with tide in formation and used as an inputcontour data to obtain an elevation model by interpolation using spline function. Elevation errors of less than $\pm$0.1m were achived using overlapping techniques and a spline interpolation approach, respectively. The derived DEM allows for the generation of a perspective grid and drape on the satellite image values to create a realistic terrain visualization model so that the tidal flat may be viewed from and desired direction. As the result of this study, we obtained elevation model of tidal flats which contribute to characterize of topography and monitoring of morphological evolution of tidal flats. Moreover, the modal generated here can be used for simulation of innudation according to tide and support other studies as a supplementary data set.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.81-88
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• 2015

Various satellite sensors having ranges of the visible, infrared, and thermal wavelengths have been launched due to the improvement of hardware technologies of satellite sensors development. According to the development of satellite sensors with various wavelength ranges, the fusion and integration of multisensor images are proceeded. Image matching process is an essential step for the application of multisensor images. Some algorithms, such as SIFT and SURF, have been proposed to co-register satellite images. However, when the existing algorithms are applied to extract matching points between optical and thermal images, high accuracy of co-registration might not be guaranteed because these images have difference spectral and spatial characteristics. In this paper, location of control points in a reference image is extracted by SURF, and then, location of their corresponding pairs is estimated from the correlation of the local similarity. In the case of local similarity, phase correlation method, which is based on fourier transformation, is applied. In the experiments by simulated, Landsat-8, and ASTER datasets, the proposed algorithm could extract reliable matching points compared to the existing SURF-based method.

• Korean Journal of Remote Sensing
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• v.8 no.2
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• pp.79-91
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• 1992

With recent development in spaceborne imaging radar system, there are growing interests using satellite synthetic aperture radar(SAR) data in various applications. This study attempted to identify the relationships between several forest stand characteristics and radar backscatter, measured from space altitude altitude at three incidence angles. Shuttle Imaging Radar-B(SIR-B) data were collected over a forested area in northern Florida in October, 1984. By using various sources of reference data (forest type maps, inventory records, aerial photographs, and Landsat Thematic Mapper data), about 400 forest stands of known characteristics were carefully located in the radar data. Relative radar backscatter for the three incidence angles of SIR-B data were compared with known forest stand parameters such as mean tree height, diameter at breast height(DBH), stand density, biomass, and relative amount of understory vegetation. The results show that these stand parameters have statistically significant correlations with the radar backscatter. In addition, the SIR-B radar backscatter from a certain stand parameter turned out differently at the three different incidence angles. Finally, the types and characteristics of currently available satellite SAR data are discussed.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.125-137
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• 2008

This research aims to produce basic data for developing habitat suitability models on the breeding sites of Oriental White Storks(Ciconia boyciana) which will be reintroduced to the wild in the future. The habitat characteristics of ten historical nesting sites of the Oriental White Storks at Gyeonggi and Chungcheong provinces in South Korea were analyzed with 1970's land use maps and Landsat MSS. The range of altitude on nesting sites was 40~116.38m. The mean distance from nesting sites to rice fields, to 30m wider river, and to reservoirs was $54.8{\pm}84.48m$, $869.8{\pm}708.01m$, and $1721.2{\pm}906.05m$ respectively. Historical nesting sites were located close to human settlements, and the mean distance of nesting sites to human settlements was $144.1{\pm}182.97m$. The land types within 5km radius from ten historical nesting sites consisted of 53.7% forest, 28.3% rice fields, 16.7% grasslands, 0.8% water bodies, and 0.6% human settlements. The composition of four land types(forest, rice fields, grasslands, and human settlements) was significantly differed between 93 random points and 10 historical nesting sites.

• Korean Journal of Soil Science and Fertilizer
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• v.34 no.5
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• pp.342-349
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• 2001

This study was carried out to classify and evaluate the land cover map using Landsat TM data in Pyeongtaeg City. DGPS data, aerial photography, topographical map were used for selection the training sets and accuracy assessment. The overall accuracy and Kappa coefficient of the land cover classification map(using supervised classification with 13 classes) with Landsat TM data(16 June. 1997) were respectively, 86.8%, 85.4%, but the user's accuracy of urban/village and vinyl-house was below 60%, and the producer's accuracy of read and vinyl-house below 70%. Maybe it was caused the spectral reflectance characteristics, heterogeneity and small distribution area on the artificial things such as urban/village, vinyl_house and road, etc. And then, the agricultural land cover classification system using remote sensing data in Korea was to classify level I and II. Level I consisted of 5 classes such as agricultural land, forest land, water, barren land, urban and built-up land.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.401-410
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• 2020

Recently, many studies have been conducted on the changing phenology on the Korean Peninsula due to global warming. However, because of the geographical characteristics, research on plant season in autumn, which is difficult to measure compared to spring season, is insufficient. In this study, all leaves that maple and fallen leaves were defined as 'Decay leaves' and decay leaf detection was performed based on the Landsat-8 satellite image. The first threshold value of decay leaves was calculated by using NDVI and the secondary threshold value of decay leaves was calculated using by NDWI and the difference of spectral characteristics with green leaves. POD, FAR values were used to verify accuracy of the dry leaf detection algorithm in this study, and the results showed high accuracy with POD of 98.619 and FAR of 1.203.

• The Journal of Engineering Geology
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• v.31 no.3
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• pp.395-432
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• 2021

Groundwater recharge rates vary widely by location and with time. They are difficult to measure directly and are thus often estimated using simulations. This study employed frequency and regression analysis and a classification and regression tree (CART) algorithm in a machine learning method to estimate groundwater recharge. CART algorithms are considered for the distribution of precipitation by subbasin (PCP), geomorphological data, indices of the relationship between vegetation and landuse, and soil type. The considered geomorphological data were digital elevaion model (DEM), surface slope (SLOP), surface aspect (ASPT), and indices were the perpendicular vegetation index (PVI), normalized difference vegetation index (NDVI), normalized difference tillage index (NDTI), normalized difference residue index (NDRI). The spatio-temperal distribution of groundwater recharge in the SWAT-MOD-FLOW program, was classified as group 4, run in R, sampled for random and a model trained its groundwater recharge was predicted by CART condidering modified PVI, NDVI, NDTI, NDRI, PCP, and geomorphological data. To assess inter-rater reliability for group 4 groundwater recharge, the Kappa coefficient and overall accuracy and confusion matrix using K-fold cross-validation were calculated. The model obtained a Kappa coefficient of 0.3-0.6 and an overall accuracy of 0.5-0.7, indicating that the proposed model for estimating groundwater recharge with respect to soil type and vegetation cover is quite reliable.