• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.777-786
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• 2018

This study propose a new method to detect Cochlodinium polykrikoides on satellite images using logistic regression and decision tree. We used spectral profiles(918) extracted from red tide, clear water and turbid water as training data. The 70% of the entire data set was extracted and used for model training, and the classification accuracy of the model was evaluated by using the remaining 30%. As a result of the accuracy evaluation, the logistic regression model showed about 97% classification accuracy, and the decision tree model showed about 86% classification accuracy.

• Journal of the Korean housing association
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• v.25 no.3
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• pp.85-92
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• 2014

The purpose of this study is to explore the relationship between housing types and crime and to suggest the appropriate strategies and interventions of housing policies for crime prevention. For spatial analysis of crime data, spatial autocorrelation is tested by Moran's I Test. A Ordinary Least Squares-based regression model is employed because crime data used in this study fails to show spatial autocorrelation. Results show that housing type variables except non-residential housing type are not associated with crime. Among land-use characteristics, the percentage of commercial areas is likely to better explain crime occurrence rather than housing types. It is surprising that residents' satisfaction to housing environment has a positive direction in its relationship with crime even though it cannot have a statistical significance. However, fear of crime shows a negative direction with crime although it fails to have a statistical significance. The findings of this study can contribute to understand the association between housing types and crime when setting housing policies for crime prevention.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.1
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• pp.51-60
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• 2020

The purpose of this study is to determine the spatial and temporal resolutions that can represent land surface characteristics comprised of various land use using Landsat/AMSR2-based soil moisture data. We estimated the Landsat (30 m×30 m)-based soil moisture values using the soil moisture regression model. Then, the Landsat (30 m×30 m)-based soil moisture (reference values) were resampled to the relatively coarse resolutions from 1 km to 4 km, respectively. Comparing the reference values to the resampled soil moisture values, we confirmed that uncertainties were increased with the spatial resolutions of 2 km~4 km indicating that the spatial resolution of 1 km×1 km is required to represent the complicated land surface. Also, the AMSR2 soil moisture values have less uncertainties compared to SMAP data with the temporal resolution of 1~2 days. Thus, our findings can be useful for various areas such as agriculture, hydrology, forest, etc.

• Geomechanics and Engineering
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• v.13 no.3
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• pp.475-488
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• 2017

Geotechnical data contributes substantially to the cost of engineering projects due to increasing cost of site investigations. Existing information in the form of soil maps can save considerable time and expenses while deciding the scope and extent of site exploration for a proposed project site. This paper presents spatial interpolation of data obtained from soil investigation reports of different construction sites and development of soil maps for geotechnical characterization of Multan area using ArcGIS. The subsurface conditions of the study area have been examined in terms of soil type and standard penetration resistance. The Inverse Distance Weighting method in the Spatial Analyst extension of ArcMap10 has been employed to develop zonation maps at different depths of the study area. Each depth level has been interpolated as a surface to create zonation maps for soil type and standard penetration resistance. Correlations have been presented based on linear regression of standard penetration resistance values with depth for quick estimation of strength and stiffness of soil during preliminary planning and design stage of a proposed project in the study area. Such information helps engineers to use data derived from nearby sites or sites of similar subsoils subjected to similar geological process to build a preliminary ground model for a new site. Moreover, reliable information on geometry and engineering properties of underground layers would make projects safer and economical.

• Journal of KIBIM
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• v.11 no.2
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• pp.43-53
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• 2021

The 'public agency oil joint purchase system' was introduced to lower public sector oil prices and contribute to the stability of the overall consumer oil market. The present study used spatial regression to analyze the factors affecting domestic gasoline price, focusing on the impact of potential implicit collusion among gas stations in determining domestic gasoline prices. Also, this study investigated the effect the location characteristics of the market convention gas stations and government offices on the pressure of price competition in the market and the gasoline price at general gas stations. To summarize the results of the spatial lag model (SLM), the individual characteristics of gas stations such as convenience stores (+), self-fuelling (-), commercial areas (+), subway stations (+), population density (-), and sales (-) are correlated to gasoline prices at gas stations, and the institutional location factors of gas stations (+) affected the average of 9 won per liter, 11 won per liter. In order to solve these problems, the establishment of a monitoring system reflecting the location characteristics of the region and the ongoing review of the system should be carried out. In addition, separate, expanded and promotional measures should be prepared for the convenience of general and public oil buyers.

• Journal of Environmental Impact Assessment
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• v.3 no.2
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• pp.47-56
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• 1994

AGNPS model is an event-based model to analyze nonpoint-source and to examine potential water quality problems from agricultural watershed. This model uses a square grid-cell system to represent the spatial variability of watershed conditions, and simulates runoff, sediment, and nutrient transport for each cell. AGNPS model was applied on Yeonwha watershed, and the test results were compared with the measured data for runoff volume, peak runoff rate, suspended solids, and phosphorus concentration. The watershed of 278.8 ha was divided into 278 cells, each of which was 1 ha in size. The coefficients of determination for runoff volume and peak flow were (0.893 and 0.801 respectively from regression of the estimated values on the measured values. The concentration of suspendid solid was increased but decreased that of phosphate with runoff volume.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1353-1364
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• 2018

This study proposed a method to detect Cochlodinium polykrikoides red tide pixels in satellite images using a logistic regression model of machine learning technique under Imbalanced data. The spectral profiles extracted from red tide, clear water, and turbid water were used as training dataset. 70% of the entire data set was extracted and used for as model training, and the classification accuracy of the model was evaluated using the remaining 30%. At this time, the white noise was added to the spectral profile of the red tide, which has a relatively small number of data compared to the clear water and the turbid water, and over-sampling was performed to solve the unbalanced data problem. As a result of the accuracy evaluation, the proposed algorithm showed about 94% classification accuracy.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.29-37
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• 2017

It has gradually become important to estimate a forest stand volume utilizing LiDAR data. Recently, various statistical models including a linear regression model has been introduced to estimate a forest stand volume using LiDAR data. One of limitations of the current approaches is in that the accuracy of observed forest stand volume data, which is used as a response variable, is questionable unstable. To overcome this limitation, we consider a spatial structure for a forest stand volume. In this research, we propose a hierarchical model for applying a spatial structure to a forest stand volume. The proposed model is applied to the LiDAR data and the forest stand volume for Bonghwa, Gyeongsangbuk-do.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.64-78
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• 2019

This paper explores key factors affecting taxi travel using global positioning system(GPS) data in Seoul, Korea, considering spatial dependence. We first analyzed the travel characteristics of taxis such as average travel time, average travel distance, and spatial distribution of taxi trips according to the time of the day and the day of the week. As a result, it is found that the most taxi trips were generated during the morning peak time (8 a.m. to 9 a.m.) and after the midnight (until 1 a.m.) on weekdays. The average travel distance and travel time for taxi trips were 5.9 km and 13 minutes, respectively. This implies that taxis are mainly used for short-distance travel and as an alternative to public transit after midnight in a large city. In addition, we identified that taxi trips were spatially correlated at the traffic analysis zone(TAZ) level through the Moran's I test. Thus, spatial regression models (spatial-lagged and spatial-error models) for taxi trips were developed, accounting for socio-demographics (such as the number of households, the number of elderly people, female ratio to the total population, and the number of vehicles), transportation services (such as the number of subway stations and bus stops), and land-use characteristics (such as population density, employment density, and residential areas) as explanatory variables. The model results indicate that these variables are significantly associated with taxi trips.

• Land and Housing Review
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• v.13 no.1
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• pp.1-9
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• 2022

In 1991, the United Nations World Tourism Organization (UNWTO) declared "tourism accessible for all" recommending the practice of the right to enjoy tourism. According to the Ministry of Health and Welfare of Korea (2019), the disabled, who are the most vulnerable in tourism, accounted for 5.1% of the total population, and the number of the elderly over 65 is expected to increase to 20.3% by 2025. In particular, the need for customized policies has been raised as the proportion of disabled people among the elderly aged 65 and over continues to increase. Thus, this study identified the spatial characteristics of Universal Design (UD) tourist destinations considering the tourism vulnerable groups. Administrative units (425 dongs) in Seoul were used as spatial units for analysis. As a research method, first, a spatial model was specified through LM verification, and then spatial regression analysis was performed. As a result of the analysis, the spatial characteristics of UD tourist destinations were found to have positive (+) effects on the number of universally certified businesses, the number of restaurants, and the number of bus stops that were available to the vulnerable. It was confirmed that there are a large number of universal certified businesses, restaurants, and bus stops in dongs with UD tourist destinations. The findings will provide policy implications when promoting the right to enjoy tourism in the future and improving Korean universal design quality.