• Health Policy and Management
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• v.30 no.3
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• pp.335-344
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• 2020

Background: The purpose of this study was to identify factors inhibiting access of people with disability to health check-ups as well as identify pertinent solutions for improvement. Methods: Twenty-three people with disability older than the age of 19 who took respective health check-ups within the last 3 years were selected as participants. For the data collection, the 1:1 intensive interview was used. The data were analyzed by the grounded theory by Corbin and Strauss. Results: The results comprised nine categories, 23 subcategories, and 179 concepts. The central phenomenon was 'failure to obtain check-ups.' Causal conditions were observed as a 'lack of communication method,' 'physical difficulties,' and 'staff unfamiliar with people with disability,' Interventional conditions comprised 'physical accessibility,' 'staffs' competency,' and 'assistant manpower.' The active strategy was included 'to investigate the professional medical institution,' 'to find the medical institution of convenient traffic accessibility,' 'to overcome communication difficulties through equipment,' and 'to overcome linguistic barriers through sufficient communication.' Whereas, 'utilization of ancillary equipment,' 'the education of staffs on people with disability,' 'universal design manual,' and 'customized check-ups' were included in the passive strategy. Such processes arose in the contextual conditions of 'lack of expectations for daily lives' and 'lack of government support.' As a consequence, the subjects participated experienced the 'disadvantages,' 'discrimination,' and 'reduced reliability of the health check-ups.' Conclusion: The subjects who participated in this study emphasized 'staffs familiar with people with disability' and 'systems customized for people with disability' are mandatory to secure complete health check-ups for people with disability.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.4
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• pp.24-34
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• 2002

The purpose of this study is to estimate the ecological effect of DMZ for development and conservation of this area. Because of the political reason, field research and estimation of the ecological effect using field data is very difficult. Then we carried out the estimation of the ecological effect using Landsat ETM+ and ancillary data of digital maps. Because of military disturbance and agricultural activity of common people, NDVI of DMZ was very low value except the interior area of DMZ. According to the distance of DMZ, the variance of NDVI didn't show the logistic curve. This result has the reason as follows. The developing force at level plane of west and middle area reached to DMZ and we could concluded in that case of east area had been effect of regular cutting for view.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.6
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• pp.15-24
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• 2014

The implementation of HACCP(Hazard Analysis and Critical Control Point) which is a systematic preventive approach to food safety is increasing in school feed or food manufacture. Thus, there are several automatic systems to assist HACCP management, however the most of existing systems are one of computer programs or correcting sensor data programs as ancillary means. Therefore, to be applied to efficiently automate HACCP system, the HACCP supporting computer system should be easy usability of the personnel involved in the HACCP operations and must be able to manage in real time the various HACCP data. In this paper, we develop a web-based HACCP automatic system operating freely available from any Internet computing environments. This system can be used as the management system of all the processes of HACCP and make possible to manage a broad range of operating information through the web server. So, the results from operation of the proposed automatic HACCP system can be consistently systematic.

• Geophysics and Geophysical Exploration
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• v.7 no.1
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• pp.93-98
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• 2004

The sand-covered Muweilah archaeological site in the United Arab Emirates (UAE) is a unique Iron Age site, and has been subject to intensive investigations. However, excavations are time consuming and may require twenty years to complete. Thus geophysical surveys were undertaken with the objective of characterising the site more expeditiously. This paper presents preliminary results of these surveys. Ground penetrating radar (GPR) was tested as a primary imaging tool, with an ancillary shallow time domain EM (MetalMapper) system. Dense 3D GPR datasets were migrated to produce horizontal (plan view) depth slices at 10 cm intervals, which is conceptually similar to the archaeologists' excavation methodology. The objective was to map all features associated with anthropogenic activity. This required delineating extensive linear and planar features, which could represent infrastructure. The correlation between these and isolated point reflectors, which could indicate anthropogenic activity, was then assessed. Finally, MetalMapper images were used to discriminate between metallic and non-metallic scatterers. The moderately resistive sand cover allowed GPR depth penetration of up to 5 m with a 500 MHz system. GPR successfully mapped floor levels, walls, and isolated anthropogenic activity, but crumbling walls were difficult to track in some cases. From this study, two possible courtyard areas were recognised. The MetalMapper was less successful because of its limited depth penetration of 50 cm. Despite this, the system was still useful in detecting modem-day ferruginous waste and bronze artefacts. The results (subject to ongoing ground-truthing) indicated that GPR was optimal for sites like Muweilah, which are buried under a few metres of sand. The 3D survey methodology proved essential to achieve line-to-line correlation for tracking walls. In performing the surveys, a significant improvement in data quality ensued when survey areas were flattened and de-vegetated. Although MetalMapper surveys were not as useful, they certainly indicated the value of including other geophysical data to constrain interpretation of complex GPR features.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.40-44
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• 2002

Precision correction is the process of geometrically aligning images to a reference coordinate system using GCPs(Ground Control Points). Many applications of remote sensing data, such as change detection, mapping and environmental monitoring, rely on the accuracy of precision correction. However it is a very time consuming and laborious process. It requires GCP collection, the identification of image points and their corresponding reference coordinates. At typical satellite ground stations, GCP collection requires most of man-powers in processing satellite images. A method of automatic registration of satellite images is demanding. In this paper, we propose a new algorithm for automatic precision correction by GCP chips and RANSAC(Random Sample Consensus). The algorithm is divided into two major steps. The first one is the automated generation of ground control points. An automated stereo matching based on normalized cross correlation will be used. We have improved the accuracy of stereo matching by determining the size and shape of match windows according to incidence angle and scene orientation from ancillary data. The second one is the robust estimation of mapping function from control points. We used the RANSAC algorithm for this step and effectively removed the outliers of matching results. We carried out experiments with SPOT images over three test sites which were taken at different time and look-angle with each other. Left image was used to select UP chipsets and right image to match against GCP chipsets and perform automatic registration. In result, we could show that our approach of automated matching and robust estimation worked well for automated registration.

• Korean Journal of Remote Sensing
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• v.11 no.1
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• pp.65-80
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• 1995

Remote Sensing data with ancillary ground-based meteorological data provides the capalility of computing threeof the four surface energy balance components(i.e. net radiation, soil heat flux and sensible heat flux) at different spatial and temporal scales. As a result, this enablis the estimation of the remaining term, latent heat flux. One of the practical applications with this approach is to produce evapotranspiration maps over large areas. This results could estimate and reproduce areal evapotranspiration over large area as much as several hundred sequare kilometers. Moreover, some calculating simulations for the effects of the land use change on the surface heat flux has been made by this method, which is able to estimate evapotranspiration under arbitracy presumed condition. From the simulation of land use change, the results suggests that the land use change in study area can be produce the significant changes in surface heat flux. This preliminary research suggests that the future research should involve development of methods to account for the variability of meteorological parameters brought about by changes in surface conditions and improvements in the modeling of sensible heat transfer across the surface atmosphere interface for partical canopy conditions using remote sensing information.

• Journal of Korea Spatial Information System Society
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• v.3 no.1 s.5
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• pp.117-126
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• 2001

We have developed the Mobile Multi Sensor System(MMSS) for the data construction of 4S application and for basic technology acquisition of mobile mapping system in Korea. Using this MMSS, we will collect the information of road and road facilities for DB creation and also construct the Digital Elevation Model(DEM) as ancillary data in urban area. The MMSS consist of the integrated navigation sensor, DGPS & IMU, and digital CCD camera set. In the S/W aspect, we developed the post-processing components for extracting the 3D coordinate information (Spatial Information) and the client program for the MMSS user group. In this paper, we will overview the MMSS constitution and post-processing program, and introduce the utilization plan of MMSS.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1407-1419
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• 2020

Long time-series gridded data is crucial for the analyses of Earth environmental changes. Climate reanalysis and satellite images are now used as global-scale periodical and quantitative information for the atmosphere and land surface. This paper examines the feasibility of DCT-PLS (penalized least square regression based on discrete cosine transform) for the spatial gap filling of gridded data through the experiments for multiple variables. Because gap-free data is required for an objective comparison of original with gap-filled data, we used LDAPS (Local Data Assimilation and Prediction System) daily data and MODIS (Moderate Resolution Imaging Spectroradiometer) monthly products. In the experiments for relative humidity, wind speed, LST (land surface temperature), and NDVI (normalized difference vegetation index), we made sure that randomly generated gaps were retrieved very similar to the original data. The correlation coefficients were over 0.95 for the four variables. Because the DCT-PLS method does not require ancillary data and can refer to both spatial and temporal information with a fast computation, it can be applied to operative systems for satellite data processing.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.449-459
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• 2015

The conventional National Forest Inventory(NFI)-based forest carbon stock estimation method is suitable for national-scale estimation, but is not for regional-scale estimation due to the lack of NFI plots. In this study, for the purpose of regional-scale carbon stock estimation, we created grid-based forest carbon stock maps using spatial ancillary data and two types of up-scaling methods. Chungnam province was chosen to represent the study area and for which the $5^{th}$ NFI (2006~2009) data was collected. The first method (method 1) selects forest type map as ancillary data and uses regression model for forest carbon stock estimation, whereas the second method (method 2) uses satellite imagery and k-Nearest Neighbor(k-NN) algorithm. Additionally, in order to consider uncertainty effects, the final AGB carbon stock maps were generated by performing 200 iterative processes with Monte Carlo simulation. As a result, compared to the NFI-based estimation(21,136,911 tonC), the total carbon stock was over-estimated by method 1(22,948,151 tonC), but was under-estimated by method 2(19,750,315 tonC). In the paired T-test with 186 independent data, the average carbon stock estimation by the NFI-based method was statistically different from method2(p<0.01), but was not different from method1(p>0.01). In particular, by means of Monte Carlo simulation, it was found that the smoothing effect of k-NN algorithm and mis-registration error between NFI plots and satellite image can lead to large uncertainty in carbon stock estimation. Although method 1 was found suitable for carbon stock estimation of forest stands that feature heterogeneous trees in Korea, satellite-based method is still in demand to provide periodic estimates of un-investigated, large forest area. In these respects, future work will focus on spatial and temporal extent of study area and robust carbon stock estimation with various satellite images and estimation methods.

• Journal of Korea Water Resources Association
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• v.54 no.2
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• pp.81-91
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• 2021

Synthetic Apreture Radar (SAR) is attracting attentions with its possibility of producing high resolution data that can be used for soil moisture estimation. High resolution soil moisture data enables more specific observation of soil moisture than existing soil moisture products from other satellites. It can also be used for studies of wildfire, landslide, and flood. The SAR based soil moisture estimation should be conducted considering vegetation, which affects backscattering signals from the SAR sensor. In this study, a SAR based soil moisture estimation at regions covered with various vegetation types on the middle area of Korea (Cropland, Grassland, Forest) is conducted. The representative backscattering model, Water Cloud Model (WCM) is used for soil moisture estimation over vegetated areas. Radar Vegetation Index (RVI) and in-situ soil moisture data are used as input factors for the model. Total 6 study areas are selected for 3 vegetation types according to land cover classification with 2 sites per each vegetation type. Soil moisture evaluation result shows that the accuracy of each site stands out in the order of grassland, forest, and cropland. Forested area shows correlation coefficient value higher than 0.5 even with the most dense vegetation, while cropland shows correlation coefficient value lower than 0.3. The proper vegetation and soil moisture conditions for SAR based soil moisture estimation are suggested through the results of the study. Future study, which utilizes additional ancillary vegetation data (vegetation height, vegetation type) is thought to be necessary.