• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.991-1005
• /
• 2022

Satellite imaging is an effective supplementary data source for detecting and verifying nuclear activity. It is also highly beneficial in regions with limited access and information, such as nuclear installations. Time series analysis, in particular, can identify the process of preparing for the conduction of a nuclear experiment, such as relocating equipment or changing facilities. Differences in the semantic segmentation findings of time series photos were employed in this work to detect changes in meaningful items connected to nuclear activity. Building, road, and small object datasets made of KOMPSAT 3/3A photos given by AIHub were used to train deep learning models such as U-Net, PSPNet, and Attention U-Net. To pick relevant models for targets, many model parameters were adjusted. The final change detection was carried out by including object information into the first change detection, which was obtained as the difference in semantic segmentation findings. The experiment findings demonstrated that the suggested approach could effectively identify altered pixels. Although the suggested approach is dependent on the accuracy of semantic segmentation findings, it is envisaged that as the dataset for the region of interest grows in the future, so will the relevant scope of the proposed method.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.25 no.4
• /
• pp.210-221
• /
• 2022

In order to promptly respond to disasters, the era of new spaces has opened where satellite images with various characteristics can be used. As the number of satellites in operation at home and abroad increases and the characteristics of satellite sensors vary, it is necessary to find satellite images optimized for disaster types. Disaster types were divided into typhoons, heavy rains, droughts, forest fires, etc., and the optimal satellite images were selected for each type of disaster considering satellite orbits, active/passive sensors, spatial resolution, wavelength bands, and revisit cycles. Each satellite orbit TLE (Two Line Element) information was applied to the SGP4 (Simplified General Perturbations version 4) model to develop a satellite orbit simulation algorithm. The developed algorithm simulated the satellite orbit at 10-second intervals and selected an accurate observation area by considering the angle of incidence of each sensor. The satellite orbit simulation algorithm was applied to the case of Typhoon Mitag in 2019 and compared with the actual satellite list. Through the analyzed results, the time and area of the captured image and the image to be recorded were analyzed within a few seconds to select the optimal satellite image according to the type of disaster. In the future, it is intended to serve as a basis for building a system that can promptly request and secure satellite images in the event of a disaster.

• Management & Information Systems Review
• /
• v.37 no.3
• /
• pp.27-47
• /
• 2018

In this study, we examine how land use zoning affects the land price controlling other variables such as road-facing condition of the land, land form, land age after its development and land size. We employ geographically weighted regression analysis which reflects spatial dependency as methodology with a data sample of land transaction price data of Jangyu, a new town, in Korea. The results of our empirical analysis show that the respective coefficients of traditional regression and geographically weighted regression are not significantly different. However, after calculating Moran's Index with residuals of both OLS and GWR models, we find that Moran's Index of GWR decreases around 26% compared to that of OLS model, thus improving the problem of spatial autoregression of residuals considerably. Unlike our expectation, though, in both traditional regression and geographically weighted regression where residential exclusive area is used as a reference variable, the dummy variable of the residential land for both housing and shops shows a negative sign. This may be because the residential land for both housing and shops is usually located in the level area while the residential exclusive area is located at the foot of a mountain or on a gentle hill where the residents can have good quality air and scenery. Although the utility of the residential land for both housing and shops is higher than its counterpart's since it has higher floor area ratio, amenity which can be explained as high quality of air and scenery in this study seems to have higher impact in purchase of land for housing. On the other hand, land for neighbourhood living facility seems to be valued higher than any other land zonings used in this research since it has much higher floor area ratio than the two land zonings above and can have a building with up to 5 stories constructed on it. With regard to road-facing condition, land buyers seem to prefer land which faces a medium-width road as expected. Land facing a wide-width road may have some disadvantage in that it can be exposed to noise and exhaust gas from cars and that entrance may not be easy due to the high speed traffic of the road. In contrast, land facing a narrow road can be free of noise or fume from cars and have privacy protected while it has some inconvenience in that entrance may be blocked by cars parked in both sides of the narrow road. Finally, land age variable shows a negative sign, which means that the price of land declines over time. This may be because decline of the land price of Jangyu was bigger than that of other regions in Gimhae where Jangyu, a new town, also belong, during the global financial crisis of 2008.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.24 no.3
• /
• pp.247-262
• /
• 2022

In domestic tunnels, it is mandatory to install CCTVs in tunnels longer than 200 m which are also recommended by installation of a CCTV-based automatic accident detection system. In general, the CCTVs in the tunnel are installed at a low height as well as near by the moving vehicles due to the spatial limitation of tunnel structure, so a severe perspective effect takes place in the distance of installed CCTV and moving vehicles. Because of this effect, conventional CCTV-based accident detection systems in tunnel are known in general to be very hard to achieve the performance in detection of unexpected accidents such as stop or reversely moving vehicles, person on the road and fires, especially far from 100 m. Therefore, in this study, the region of interest is set up and a new concept of inverse perspective transformation technique is introduced. Since moving vehicles in the transformed image is enlarged proportionally to the distance from CCTV, it is possible to achieve consistency in object detection and identification of actual speed of moving vehicles in distance. To show this aspect, two datasets in the same conditions are composed with the original and the transformed images of CCTV in tunnel, respectively. A comparison of variation of appearance speed and size of moving vehicles in distance are made. Then, the performances of the object detection in distance are compared with respect to the both trained deep-learning models. As a result, the model case with the transformed images are able to achieve consistent performance in object and accident detections in distance even by 200 m.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.18 no.1
• /
• pp.159-172
• /
• 2023

The purpose of this study is to explore a collaborative start-up space(Co-Space) configuration plan in terms of university-regional linkage through demand analysis on the composition of university-regional linkage startup space. To this end, a survey was conducted for request analysis, and the collected data were analyzed through the t-test, The Lotus for Focus model. In addition, FGI was implemented for entrepreneurs, and the direction of the composition of the university-region Co-Space was derived from various aspects. The results of this study are as follows. First, as a result of the analysis of the necessity of university-community Co-Space, the necessity of opening up the start-up space recognized by local residents and the necessity of building the start-up space in the region were high. In addition, men recognized the need to build a space for start-ups in the community more highly than women did women. Second, as a result of analysis of demands for university-regional Co-Space, the difference between current importance and future necessity of university-regional Co-Space was statistically significant. Third, as a result of analysis on the composition of the startup space by cooperation between universities and regions, different demands were made for composition of the startup space considering openness and closeness, and for composition of the startup space size. The implications of the study are as follows. First, Co-Spaces need to be constructed in conjunction with universities in accordance with the demands of start-up companies in the region by stage of development. Second, it is necessary to organize a customized Co-Space that takes into account the size and operation of the start-up space. Third, it is necessary to establish an experience-based open space for local residents in the remaining space of the university. Fourth, it is necessary to establish a Co-Space that enables an organic network between local communities, start-up investment companies, start-up support institutions, and start-up companies. This study is significant in that it proposed the regional startup ecosystem and the cooperative start-up space structure for strengthening start-up sustainability through cooperation between universities and local communities. The results of this study are expected to be used as useful basic data for Co-Space construction to build a regional start-up ecosystem in a trend emphasizing the importance of start-up space, which is a major factor affecting start-up companies.