Search

The operational rainfall rate algorithm developed for the Advanced Meteorological Imager (AMI) onboard the GEO-KOMPSAT-2A (GK-2A) launched in 2018 uses the a-priori information including the microwave rainfall data from low-earth orbiting satellites and infrared (IR) brightness temperatures from geostationary satellites. The algorithm may better perform with a variety of a-priori information describing all possible precipitating systems. In addition, separation of physically different precipitating systems likely to improve the accuracy of retrieval process. However, it has been well known that such the separation can be hardly achieved based on the measurements of cloud top temperatures. This algorithm tried to utilize the radiative characteristics observed differently for different wavelengths in IR spectral regions. The characteristics include the different emissivity as a function of wavelength and cloud thickness. Using the brightness temperature difference (BTD) between IR channels the algorithm determines the thresholds of the BTDs discriminating five types of precipitating clouds: shallow, non-shallow-tall-cold, non-shallow-tall-colder, non-shallow-taller-cold, and non-shallow-taller-colder clouds. The algorithm also uses databases classified by latitudinal bands. The bands are separated with four latitudinal zones. The separation of database based on latitudes may have an effect of distinguishing the cloud types that can occur regionally. As an alternative approach for cloud classification, a machine learning algorithm with Gaussian mixture models (GMMs) has been developed. The GMMs separate four cloud types. This study compares rainfall retrievals based on two different cloud classification methods.

Satellite-based microwave sensors that respond to the vertical distribution of hydrometeors have been continuously employed in the investigation of precipitation systems characteristics. Rain/no-rain classification (RNC) methods often are either applied before retrieving precipitation information from a number of algorithms based on passive microwave measurements or adopted to build the precipitation event-based databases. As a simple rain indicator, the polarized corrected temperature (PCT) at 89-GHz (PCT89) method using the global precipitation measurement (GPM) microwave imager (GMI) has been employed by many researchers, because it can estimate the scattering intensity while minimizing the effects of the surface emissivity at high resolution. This article presents a new consideration using the PCT89-based RNC method through statistical verification. Precipitating clouds were subdivided into 11 types (three stratiform types and four convective types) by the GPM dual frequency precipitation radar (DPR) precipitation classification algorithm. Quantitative comparison of verification results was performed in the tropics from January to December 2015 and major sources of uncertainty were analyzed from the perspective of the precipitation mechanism. Results showed a tendency of false identification for stratiform types except for those located near the convective core, and thus the method was susceptible to failure in the identification of convective types. Consequently, this method leads to an increase of 70% and 54% in the number of two significant stratiform types compared to DPR, while the convective types decreased by up to 53%. This article suggests that the precipitations identified by the PCT89 have features that enhance the bias toward the stratiform type.

The accuracy of a physically based passive microwave precipitation retrieval algorithm is affected by the quality of the a priori knowledge it employs, which indicates the relationship between the precipitation information obtained from cloud-resolving models (CRMs) and the simulated brightness temperatures (TBs) from radiative transfer models. As various microphysical assumptions reflecting a wide variety of sophisticated microphysical properties are applied to the CRMs, the TBs simulated based on the model-driven 3-D precipitation fields are determined by the selected microphysical assumption. In this article, we developed a prototype precipitation retrieval algorithm that incorporates various cloud microphysics schemes in its a priori knowledge (i.e., databases). In the retrieval process, a specific a priori database is selected for every target precipitation scene by comparing the similarities of the simulated and observed microwave emission and scattering signatures. The prototype algorithm was tested through application to precipitation retrieval for tropical cyclones at various intensity stages, which occurred over the northwestern Pacific region in 2015. The a priori databases constructed using the weather research and forecasting double-moment (WDM6) and Thompson Aerosol Aware schemes are superior when used for weak-to-moderate rainfall systems, whereas the databases constructed with the other schemes are superior within strong rain rate regions. The retrieval results obtained using the best-performing database are generally superior for all rain rate regions. Furthermore, we confirm that the database quality is more important than the number of databases. In comparison with the data from the dual-precipitation radar, the retrieval’s correlations, bias, and root mean square are 0.75, 0.14, and 5.62, respectively.

The world experiences disasters caused by natural and industrial accidents. Various products have been developed and applied for manpower rescue and risk removal at disaster sites. However, in order to move debris and other obstacles generated after cutting and destroying operations to remove hazards at a disaster site, a mechanical device that can safely grasp various target objects is required. In this study, we developed a gripper that can be attached to a cutting machine typically used at disaster sites. The gripper proposed in this study can be attached and detached to the hydraulic cutter, and can stably hold a 100 kg object using the force generated from the hydraulic motor. In addition, a mechanism that can safely grip target objects regardless of shape has been applied. The gripper proposed in this study was verified through mathematical analysis and MFBD simulation. Finally, the gripper was actually manufactured and grip tested successfully.

The number of elderly people has increased as life expectancy increases. As muscle strength decreases with aging, it is easy to feel tired while walking, which is an activity of daily living (ADL), or suffer a fall accident. To compensate the walking problems, the terrain environment must be considered, and in this study, we developed the locomotion mode recognition (LMR) algorithm based on the gaussian mixture model (GMM) using inertial measurement unit (IMU) sensors to classify the five terrains (level walking, stair ascent/descent, ramp ascent/descent). In order to meet the walking conditions of the elderly people, the walking speed index from 20 to 89 years old was used, and the beats per minute (BPM) method was adopted considering the speed range for each age groups. The experiment was conducted with the assumption that the healthy people walked according to the BPM rhythm, and to apply the algorithm to the exoskeleton robot later, a full/individual dependent model was used by selecting a data collection method. Regarding the full dependent model as the representative model, the accuracy of classifying the stair terrains and level walking/ramp terrains is BPM 90: 98.74%, 95.78%, BPM 110: 99.33%, 95.75%, and BPM 130: 98.39%, 87.54%, respectively. The consumption times were 14.5, 21.1, and 14 ms according to BPM 90/110/130, respectively. LMR algorithm that satisfies the high classification accuracy according to walking speed has been developed. In the future, the LMR algorithm will be applied to the actual hip exoskeleton robot, and the gait phase estimation algorithm that estimates the user’s gait intention is to be combined. Additionally, when a user wearing a hip exoskeleton robot walks, we will check whether the combined algorithm properly supports the muscle strength.

Spaceborne passive microwave sensors have been developed to improve the knowledge of precipitation systems based on channels that interact directly with hydrometeors in clouds. In particular, understanding the global distribution of precipitation is one of the main missions. Prior to these precipitation studies, many researchers tend to implement the rain/no-rain classification (RNC) procedure. As a simple way, the polarized corrected temperature at 89 GHz (PCT89) from passive microwave radiometry has been widely used to identify rain pixels. The PCT89 can estimate the scattering intensity accompanied by precipitating clouds while minimizing the effects of the surface at high resolution, however, the diversity of the hydrometeor distributions can be a problem in the use of a consistent cut-off threshold. Therefore, the purpose of this study is to evaluate differences in the accuracy of the PCT-based RNC method induced by the various hydrometeor distributions and to present a new perspective to users so that it can be used appropriately. Precipitation data observed by the global precipitation measurement (GPM) microwave imager (GMI) for the period from January to December of 2015 in the tropics were used in the study. Based on the classification algorithm of the GPM dual precipitation radar (DPR), the precipitation data were subdivided into 11 types (3 stratiform types, 4 convective types, and others), and then a statistical verification was attempted to ensure that the cut-off threshold was appropriate. The PCT89-based RNC method leads to an increase of 70% and 54% in the number of two significant stratiform types compared to the DPR precipitation flag. On the other hand, the convective types decreased by up to 53%. Although regional diversity could lead to systematic differences in the verification, they did not exceed magnitudes of the difference between precipitation types. Therefore, this study suggests that the precipitations identified by the PCT89-based RNC method have features that enhance the bias toward the stratiform type.

Within recent years, enormously increasing open government data, smart devices, and location-based service requires several new approaches and solutions, incapable in the conventional geo-spatial information technology. Many endeavors in public and private sectors try to overcome the inherent deficiency of conventional Geographic Information System (GIS) by integrating Big Data and geo-spatial technology into Geo-Spatial Big Data platform. To secure technology to store, manage, analyze, and deliver service efficiently for Geo-Spatial Big Data (GSBD) with high volume in size, this study interprets GSBD platform as 7V characteristics and suggests 7V-based implementation strategy for GSBD service system. Especially, the concept and characteristics of GSBD were examined from the GSBD service perspective, based on which, a framework for GSBD service was suggested, with a plan to implement a 7V-based GSBD service system. Finally, a service scenario was set to analyze the changes in South Korea territory, with a pilot system for a GSBD service supporting it being implemented and substantiated.

Passive microwave radiometric signatures are affected by microphysical properties and hydrometeor distributions. Various microphysical properties of hydrometeors assumed in numerical simulations of...

This study attempts to establish prototype-leveled patent fusion data based on collecting structured and unstructured geo-spatial big data (GSBD) patent information, to distinguish GSBD technical ecosystems into their spatial and non-spatial aspects, and to propose a method to analyze visualizations in a multi-dimensional way. Spatially, we visualize the patent citation data among applicants for a patent at local and national levels, and implement a visualization analysis of the competitive relations for the locational traits of applicants for patent and technology innovation by comparing technology dependence and technology impacts in GSBD technology. Non-spatially, we analyzed the trend of time series of GSBD technology innovation activities based on Industry Classification and technology keywords. We establish the related networks among industry classification, IPC patent classification and technology keywords and implement a visualization analysis of convergence structure in element technologies through graph network analysis and Venn diagram analysis. We extracted issues related with the establishment of patent fusion data and interpretation of visualization analysis through the examination of research methodology and analysis results and discussed future research tasks to solve these problems.

A novel method was proposed to detect low stratus and fog (LSF) at dawn during the summertime using near-simultaneous observations from dual geostationary-orbit satellites (GEOs): the Korean Communication, Ocean and Meteorological Satellite (COMS; 128.2°E) and the Chinese Feng-Yun-2D (FY-2D; 86.5°E). The orbital positions of the GEOs provided a large difference (~46.5°) in the viewing zenith angle (VZA) in the study region (122–132°E, 32.5–42.5°N) and high contrast observations at dawn. Numerical simulations were carried out to derive the optical properties of the LSF and the radiative differences between the GEOs due to both the VZA and spectral response function (SRF). The conventional threshold method, which used the visible reflectance at 0.67 μm (R0.67) and the brightness temperature difference between 3.7 μm and 11 μm (BTD3.7–11), had limitations in detecting LSF at dawn due to weak visible light and fast night-to-day transition. We utilized the observed stereo differences (ΔR0.67, ΔBTD3.7–11) between the two GEOs to improve LSF detection. The dual-satellite observations were verified with ground-based data from 45 stations in South Korea co-located with each GEO pixel. The ΔR0.67 threshold value showed better accuracy (78% vs. 67%) than the conventional R0.67 threshold method. In addition, the ΔBTD3.7–11 threshold was better (55% vs. 38%) than the BTD3.7–11 threshold. The dual-satellite method allowed more reliable LSF detection using the combination of ΔR0.67 and R0.67, particularly for LSF without cumuliform or high clouds. Our method is applicable to multiple geostationary satellites for continuous LSF monitoring.

South Korea has recently been suffering from damage caused by typhoons and floods. To reduce repetitive damage, the government has drawn up a trace of flood damage through surveys. However, due to the number of hours of time, cost and manpower, only major areas are being made. Therefore, the purpose of this study is to create 3D simulation that is relatively easy to make and identify areas of flood risk using open government data. The study area is the Taehwa river basin in Ulsan, which was influenced by typhoon ‘Chaba’ in last year. The stages of River level were set up by examining the actual rainfall and the river level. River basin were simulated in 3D at each river level using 1/1000 digital map. The result of this study can be used as references for disaster prevention planning and impact assessment of pre-disaster at the national level and for maintenance of facilities and the selection of shelters against typhoons and floods at the local government level.

The purpose of this study is to verify whether the introduction of smart city service is affected by geographically adjacent local governments and to analyze how the local governments that introduced smart city services are clustered empirically. For this purpose, this study surveyed 226 primary local governments nationwide regarding whether they introduced smart city service or not and the introduction date of smart city service in the field of safety and urban management. Next, the introduction degree of smart city service is divided into the first Smart City Comprehensive Plan and the second Smart City Comprehensive Plan period and compared. The empirical analysis was conducted to examine spatial autocorrelation of the introduction degree of smart city service in the field of safety and urban management. As an analytical method, data mapping, Moran’s I statistic of spatial autocorrelation, LISA (local indicators of spatial association) were used. As a result, first, before the second Smart City Comprehensive Plan was established, smart city services were introduced mainly in urban management fields such as facility management rather than safety fields. Second, the introduction of smart city services of the primary local governments showed a positive autocorrelation and it revealed that the area where the degree of introduction of the smart city service in the unit area and the adjacent area are both high and the low areas are clustered respectively. The results of this study can be used as the basic data for policy direction of central government for further introduction of smart city service.

In Global intensifying competition, each government takes an effort to improving public services through between government department. Based on business association between ‘Ministry of Land, Infrastructure and Transport (MOLIT)’ and ‘National Police Agency (NPA)’, this study develop to “CCTV Video provide service” and verify a significance of service. For service realize, this study reviewed the “U-City Center” and “112 emergency call system”. Also through interview within U-City center, MOLIT and NPA, made service functional structure. According to Interview, police can get a detailed information of field, through providing CCTV video which built by local government. So functional structure are based interviewer opinion and GIS. Service development after, for operating test put service at U-City center and Deajeon-si local police agency. Significance of service is verified through user satisfaction survey. Survey result, necessity and satisfaction are recognized good. Also another opinion is that service needed which spreading to other local governments. When this service spread to other local government and police agency, it could provide efficient public service with citizen, based on department collaboration.

The aim of this study is to derive the evaluation criteria that can be applied in common to the local government in selecting a U-service and then to analyze priority of evaluation criteria based on the type of service. This study reviewed evaluation items for selecting ubiquitous services in 25 local government and conducted a survey and factor analysis for common evaluation criteria. 5 common evaluation criteria and the priority of evaluation criteria for each type of ubiquitous services were derived by analytical hierarchy process survey method. Following is five common evaluation criteria: economic and technical factor, basic and institutional factor, linkage and expandable factor, recipient satisfaction factor, usability factor. Following is the most critical evaluation criteria: basic and institutional factor in case of basic services, recipient satisfaction factor in case of special services, usability factor in case of operation services, linkage and expandable factors in case of linkage services, economic and technical factor in case of profit services, basic and institutional factor in case of nonprofit services. The result is expected to use for local government to make a choice for the most useful type of ubiquitous service in U-City planning.

The aim of this study was to propose technology developments and policy directions for the future geospatial information open platform, the so-called V-World. For this study, it was to compare and analyze the level of element technologies between Korea and foreign geospatial platforms. In addition, the expert survey and interview were performed to extract the current utilization of geospatial information in the different industrial sectors. Based on this analysis, this study constructed the basic configuration of the future V-World and proposed the policy and technological counterplan to realize it. It was judged that these results could be contributed not only to get the core technology related to geospatial platform but also to establish policies for the national geospatial information platform and the national information plan.

Vertically and horizontally inhomogeneous distributions of hydrometeors are often observed in precipitating clouds. The 3-D characteristics can then cause errors in the passive microwave rainfall measurements with the current off-nadir viewing sensors' specifications. This result is due to the fact that the same surface rainfall could be associated with different amounts of hydrometeors depending on the sensors' viewing paths. In this paper, we confirmed that the plane-parallel radiative treatment to the atmosphere leaves a notable deficiency in the microwave radiometric signatures, particularly at the higher frequency channels for different viewing directions when largely inhomogeneous precipitating clouds are accompanied by significant ice particles. The mean differences between the two brightness temperature fields with two opposite azimuthal viewing directions were up to approximately 40 °K for the vertically polarized channel at 85.5 GHz in the case study. The impact of the 3-D effect on the passive microwave rainfall estimations was also examined by synthetic retrievals employing a Bayesian methodology. The results showed that the uncertainty in the rainfall estimations due to the 3-D effect depended on the viewing directions considered in the a priori information. It was also found that taking more viewing angles or the azimuth angles in the a priori information into consideration tended to moderate the retrieval difference that resulted from the different viewing directions. In addition, the retrieval uncertainty related to the 3-D effect appeared to be more significant for heavy rainfall cases with large amounts of ice particles, as expected.

Urban facilities are becoming more diverse and complex with urban expansion and population growth. To efficiently utilize the information about intelligent urban facility, sensors to acquire information should be first popularized, and measures to combine and utilize different kinds of information should be studied. This study intends to suggest measures to connect and utilize urban facility sensors for information collection and collected sensor information. To study set a range, the range of ‘Urban facilities’ as spatial range is set based on a review of Special Act on the Safety Control of Public Structures and National Land Planning and Utilization Act. The range of sensors is set according to common classification and the classifications under international agreements. Based on the range set above, information connectivity for urban facilities, individual sensor list for urban facilities and information connectivity for sensors are derived using expert survey and suggested the methods for utilizing the established information of urban facility sensors. The sensor information will help to manage individual urban facilities and also help to respond effectively to disasters and accidents, through information sharing.

We studied an activation plan of park and green space management system using geographic information system for an effective management of urban parks managed by local government. First, we reviewed research concerning a park management system, but we could not find the research suggesting an activation plan of park management system. After analyzing legal system and guidelines, there was no article mentioning a park management system. Total seven local governments developed park management system in Korea. In Japan, there were more than ten park management systems developed by private sector and Japanese public agencies used the system. We interviewed the seven local governments in Korea and local governments in Gyeonggi-do to find out reasons of low usage of the system. We verified that the activation was poor due to no legal basis to establish a park management system, and financial difficulties of local governments. To verify activation factors, we investigated similar GIS to the park management system. After comparison, we found that there were legal obligations of government expenditures and GIS systems were activated by state spending. Based on the results, we suggested two regulation improvements and financial support to activate the GIS for a park management. With the regal improvements and the state’s financial support, we expected that the park management system would be activated. As a result, there would be reducing resources of work forces and cost, and efficient work performances.

This study was conducted with the purpose of suggesting the role of Geo-Spatial Big Data (GSBD) and its utilization by defining the GSBD concept, and also developing useful applications of GSBD application technology that will actively emerge in future. In this study, Geo-Spatial Big Data is defined as “a series of application system that will serve to extract meaningful information through resources managing, analyzing and servicing by structured, semi-structured and unstructured type of big data and spatial information” This study also suggested seven characteristics that GSBD possesses, namely, Volume, Variety, Velocity, Veracity, Visualization, Versatility and Value. It suggested the role and scope of GSBD as well by examining changes in the environment and future trends. Finally, the study proposed application methods of GSBD at public and private sector for each of the human, social, environmental, economic, political, technological and fusion areas by piecing together case studies and changes in trends.

This study was conducted with the purpose of suggesting the improvement plan of political for activating the Geo-Spatial Big Data Services. To this end, we were review the previous research for Geo-Spatial Big Data and analysis domestic and foreign Geo-Spatial Big Data propulsion system and policy enforcement situation. As a result, we have deduced the problem of insufficient policy of reaction for future Geo-Spatial Big Data, personal information protection and political basis service activation, relevant technology and policy, system for Geo-Spatial Big Data application and establishment, low leveled open government data and sharing system. In succession, we set up a policy direction for solving derived problems and deducted 5 policy issues : setting up a Geo-Spatial Big Data system, improving relevant legal system, developing technic related to Geo-Spatial Big Data, promoting business supporting Geo-Spatial Big Data, creating a convergence sharing system about public DB.

In this paper, we introduce a cloud top-height (CTH) retrieval algorithm using simultaneous observations from the Himawari-8 and FengYun (FY)-2E geostationary (GEO) satellites (hereafter, dual-GEO CTH algorithm). The dual-GEO CTH algorithm estimates CTH based on the parallax, which is the difference in the apparent position of clouds observed from two GEO satellites simultaneously. The dual-GEO CTH algorithm consists of four major procedures: (1) image remapping, (2) image matching, (3) CTH calculation, and (4) quality control. The retrieved CTHs were compared with other satellite CTHs from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and the Cloud-Profiling Radar (CPR), on three occasions. Considering the geometric configuration and footprint sizes of the two GEO satellites, the theoretical accuracy of the dual-GEO CTH algorithm is estimated as ±0.93 km. The comparisons show that the retrieval accuracy generally tends to fall within the theoretical accuracy range. As the dual-GEO CTH algorithm is based on parallax, it could be easily applied for the estimation of the height of any elevated feature in various fields.