• Journal of KIISE:Databases
• /
• v.30 no.3
• /
• pp.296-309
• /
• 2003

One of commercial applications of mobile computing is ATIS(Advanced Traveler Information Systems) in ITS(Intelligent Transport Systems). In ATIS, a primary mobile computing task is to compute the shortest path from the current location to the destination. In this paper, we have studied the shortest path re-computation problem that arises in the DRGS(Dynamic Route Guidance System) in ATIS where the cost of topological digital road map is frequently updated as traffic condition changes dynamically. Previously suggested methods either re-compute the shortest path from scratch or re-compute the shortest path just between the two end nodes of the edge where the cost change occurs. However, these methods we trivial in that they do not intelligently utilize the previously computed shortest path information. In this paper, we propose an efficient approximate shortest path re-computation method based on the dynamic window scheme. The proposed method re-computes an approximate shortest path very quickly by utilizing the previously computed shortest path information. We first show the theoretical analysis of our methods and then present an in-depth experimental performance analysis by implementing it on grid graphs as well as a real digital road map.

• Smart Structures and Systems
• /
• v.29 no.1
• /
• pp.1-16
• /
• 2022

Despite recent breakthroughs in deep learning and computer vision fields, the pixel-wise identification of tiny objects in high-resolution images with complex disturbances remains challenging. This study proposes a modified U-net for tiny crack segmentation in real-world steel-box-girder bridges. The modified U-net adopts the common U-net framework and a novel Self-Attention-Self-Adaption (SASA) neuron as the fundamental computing element. The Self-Attention module applies softmax and gate operations to obtain the attention vector. It enables the neuron to focus on the most significant receptive fields when processing large-scale feature maps. The Self-Adaption module consists of a multiplayer perceptron subnet and achieves deeper feature extraction inside a single neuron. For data augmentation, a grid-based crack random elastic deformation (CRED) algorithm is designed to enrich the diversities and irregular shapes of distributed cracks. Grid-based uniform control nodes are first set on both input images and binary labels, random offsets are then employed on these control nodes, and bilinear interpolation is performed for the rest pixels. The proposed SASA neuron and CRED algorithm are simultaneously deployed to train the modified U-net. 200 raw images with a high resolution of 4928 × 3264 are collected, 160 for training and the rest 40 for the test. 512 × 512 patches are generated from the original images by a sliding window with an overlap of 256 as inputs. Results show that the average IoU between the recognized and ground-truth cracks reaches 0.409, which is 29.8% higher than the regular U-net. A five-fold cross-validation study is performed to verify that the proposed method is robust to different training and test images. Ablation experiments further demonstrate the effectiveness of the proposed SASA neuron and CRED algorithm. Promotions of the average IoU individually utilizing the SASA and CRED module add up to the final promotion of the full model, indicating that the SASA and CRED modules contribute to the different stages of model and data in the training process.

• Journal of Korean Society of Environmental Engineers
• /
• v.22 no.7
• /
• pp.1331-1343
• /
• 2000

Through the integration of USLE and GIS, the methodology to estimate the soil loss was developed, and applicated to the Sacheon river in Gangrung. Using GIS, spatial analysis such as watershed boundary determination, flow routing. slope steepness calculation was done. Spatial information from the GIS application was given for each grid. With soil and land use map, information about soil classification and land use was given for each grid too. Based upon these data, thematic maps about the factors of USLE were made. We estimated the soil loss by overlaying the thematic maps. In this manner, we can assess the degree of soil loss for each grid using GIS. Annual average soil loss of Sacheon river watershed is 1.36 ton/ha/yr. Soil loss in forest, dry field, and paddy field is 0.15 ton/ha/yr, 27.04 ton/ha/yr, 0.78 ton/ha/yr respectively. The area of dry field, which is 4% of total area, is $2.4km^2$. But total soil loss of dry field is 6561 ton/yr, and it occupies 84.9 % of total soil loss eroded in Sacheon river watershed. Comparing with the 11.2 ton/ha/yr of an average soil loss tolerance for cropland, provision for the soil loss in dry field is necessary. Run-off and water quality of Sacheon river were measured two times in flood season: from July 24, 1998 to July 28 and from September 29 to October 1. As the run-off of the river increased, SS, TN, TP concentrations and pollutant loadings increased. SS, TN, TP loads of Sacheon river discharged during the 2 heavy rains were 21%, 39%, and 19% of the total pollutant loadings generated in the Sacheon river watershed for one year. We can see that much pollutants are discharged in short period of flood season.

• Journal of Korean Society of Forest Science
• /
• v.95 no.6
• /
• pp.663-671
• /
• 2006

This study was performed for exploring the spatial distribution pattern of Pinus densiflora and Quercus spp. in Korea. Firstly, the spatial distribution map of Pinus densiflora and Quercus spp. was prepared in grid of $100m{\times}100m$ at national level, using digital forest type map and actual vegetation map. And thematic maps for topography, climate, and soil were also prepared in the raster form of $100m{\times}100m$. Through GIS based spatial analysis of the digital distribution map of Pinus densiflora and Quercus spp. and thematic maps, the spatial characteristics of Pinus densiflora and Quercus spp. distribution was explored in relation to the environmental factors such as topography, climate, and soil. And the occurrence frequency models of Pinus densiflora and Quercus spp. were derived. Pinus densiflora occurs more often than Quercus spp. at low elevation, low slope gradient, and high temperature areas. In addition, Pinus densiflora is mainly distributed at shallow and well-drained loamy soil from igneous rocks. In contrast, Quercus spp. is more common at shallow and well-drained loamy soil from metamorphic rocks. As a result, the prediction model for the spatial distribution of Pinus densiflora and Quercus spp. by topographical variables has proven successful with high statistical significance. The result of this study can contribute to rational management of Pinus densiflora and Quercus spp. stand in Korea, considering environmental factors such as topography, climate, and soil.

• Journal of Environmental Science International
• /
• v.23 no.11
• /
• pp.1919-1927
• /
• 2014

In order to decide the location of appropriate onshore wind farm with higher potential wind energy, several decision processes using Geographic Information System (GIS) including Digital Elevation Map (DEM) were proposed and we also estimated the wind resources through the proposed decision process. Decision process consists with three steps. First step is excluding inappropriate location geographically using DEM data including SRTM (Shuttle Radar Topography Mission) terrain data, landslide, land-use, roadway, and forest road data. And the second step of decision process is consideration of the difficulty caused by the natural environmental problem. This step is carried out using ECVAM (Environmental Conservation Value Assessment Map) data. And final step is determination of the most suitable location through the Moving Suitability Identification Method (MSIM) based on the moving potentially estimated wind resources area. Proposed decision process was applied over the Korean Peninsula. Wind resource potential estimated by the first and the second step is cases shows 35.09 GW and 7.17 GW, respectively, and the total evaluated energy from the all proposed step were 0.43 GW and 1.87 GW for the 3 km and 1.5 km geographical grid size, respectively.

• Journal of Climate Change Research
• /
• v.8 no.4
• /
• pp.329-337
• /
• 2017

In this study, land-use changes from 1990 to 2010 in Jeju Island by different approaches were produced and compared to suggest a more efficient approach. In a sample-based method, land-use changes were analyzed with different sampling intensities of 2 km and 4 km grids, which were distributed by the fifth National Forest Inventory (NFI5), and their uncertainty was assessed. When comparing the uncertainty for different sampling intensities, the one with the grid of 2 km provided more precise information; ranged from 6.6 to 31.3% of the relative standard error for remaining land-use categories for 20 years. On the other hand, land-cover maps by a wall-to-wall approach were produced by using time-series Landsat imageries. Forest land increased from 34,194 ha to 44,154 ha for 20 years, where about 69% of total forest land were remained as forest land and 19% and 8% within forest lands were converted to grassland and cropland, respectively. In the case of grassland, only about 40% of which were remained as grassland and most of the area were converted to forest land and cropland. When comparing land-cover area by land-use categories with land-use statistics, forest areas were underestimated while areas of cropland and grassland were overestimated. In order to analyze land use change, it is necessary to establish a clear and consistent definition on the six land use classification.

• Economic and Environmental Geology
• /
• v.38 no.6 s.175
• /
• pp.607-622
• /
• 2005

This study was carried out in order to evaluate where the soil loss was mainly occurred, .and to verify how riverbed sediments in the tributaries of the Seomjin River were related to their source rocks distributed in Sunchang area. The study area including the Seomjin River with 4 tributaries of Kyeongcheon, Okgwacheon, Changjeong-cheon and Ipcheon was divided into 10 watershed. The RUSLE (Revised Universal Soil Loss Equation) was estimated for all the grids (10 m cells) in the corresponding watershed. The amount of soil loss per unit area was calculated as follows: dry fold (53,140.94 tons/ha/year), orchard (25,063.38 tons/ha/year), paddy field (6,506.7 tons/ha/year) and Idlest (6,074.36 tons/ha/year). The differences of soil loss per unit area appear to be depends on areas described earlier. Soil erosion hazard zones were generally distributed within dry fields. Several thematic maps such as land use maps, topographical maps and soil maps were used as a data to generate the RUSLE factors. The amount of soil loss, computed by using the RUSLE, showed that soil loss mainly occurred at the regions where possible source rocks were distributed along the stream. Based on the this study on soil loss and soil erosion hazard zone together with chondrite-normalized REE patterns that were previously analyzed in same study area, a closed relationship between riverbed sediments and possible source rocks is formed. Especially in the Okgwacheon that are widely distributed by various rocks, chondrite-normalized REE pattern derived from the riverbed sediments, source rock and soil is expected to have a closed relationship with the distribution of soil loss.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.19 no.3
• /
• pp.61-74
• /
• 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 Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.40 no.1
• /
• pp.51-66
• /
• 2022

SST (Sea Surface Temperature) is based on the atmosphere-ocean interaction, one of the most important mechanisms for the Earth system. Because it is a crucial oceanic and meteorological factor for understanding climate change, gap-free grid data at a specific spatial and temporal resolution is beneficial in SST studies. This paper examined the production of daily SST grid maps from 137 stations in 2020 through the ordinary kriging with variogram optimization and their accuracy assessment. The variogram optimization was achieved by WLS (Weighted Least Squares) method, and the blind tests for the interpolation accuracy assessment were conducted by an objective and spatially unbiased sampling scheme. The four-round blind tests showed a pretty high accuracy: a root mean square error between 0.995 and 1.035℃ and a correlation coefficient between 0.981 and 0.982. In terms of season, the accuracy in summer was a bit lower, presumably because of the abrupt change in SST affected by the typhoon. The accuracy was better in the far seas than in the near seas. West Sea showed better accuracy than East or South Sea. It is because the semi-enclosed sea in the near seas can have different physical characteristics. The seasonal and regional factors should be considered for accuracy improvement in future work, and the improved SST can be a member of the SST ensemble around South Korea.

• Journal of the Korean association of regional geographers
• /
• v.12 no.5
• /
• pp.614-630
• /
• 2006

Improved estimates of populations at risk for quick and effective response to natural and man-made disasters require spatial disaggregation of zonal population data because of the spatial mismatch problem in areal units between census and impact zones. This paper implements a dasymetric surface model to facilitate spatial disaggregation of the population of a census block group into populations associated with each constituent pixel and evaluates the performance of the surface-based spatial disaggregation model visually and statistically. The surface-based spatial disaggregation model employed geographic information systems (GIS) to enable dasymetric interpolation to be guided by satellite-derived land use and land cover data as additional information about the geographic distributor of population. In the spatial disaggregation, percent cover based empirical sampling and areal weighting techniques were used to objectively determine dasymetric weights for each grid cell. The dasymetric population surface for the Atlanta metropolitan area was generated by the surface-based spatial disaggregation model. The accuracy of the dasymetric population surface was tested on census counts using the root mean square error (RMSE) and an adjusted RMSE. The errors related to each census track and block group were also visualized by percent error maps. Results indicate that the dasymetric population surface provides high-precision estimates of populations as well as the detailed spatial distribution of population within census block groups. The results also demonstrate that the population surface largely tends to overestimate or underestimate population for both the rural and forested and the urban core areas.