• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.164-171
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• 2007

This research used GIS spatial analysis model and Huff probability model and achieved trade area analysis of area center. we constructed basic maps that were surveyed according to types of business, number of households etc. using a land registration map of LMIS(Land Management Information System) in Bokdae-dong, Cheongju-si. Kernel density function and NNI(Nearest Neighbor Index) was used to estimate store distribution center area in neighborhood life zones. The center point of area and scale were estimated by means of the center area. Huff probability model was used in abstracting trade areas according to estimated center areas, those was drew map. Therefore, this study describes method that can apply in Huff probability model through kernel density function and NNI of GIS spatial analysis techniques. A trade area was abstracted more exactly by taking advantage of this method, which will can aid merchant for the foundation of small sized enterprises.

• Journal of Korea Water Resources Association
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• v.46 no.5
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• pp.439-447
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• 2013

The applicability of the parameter map of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) model for the Korean Peninsula was assessed from the perspective of flood prediction. The design rainfalls estimated from the MBLRP model were smaller than those from observed values by 5% to 40%, and the degree of underestimation of design rainfall increases with the increase of the recurrence interval of the design rainfall. The design floods at a virtual watershed estimated using the simulated rainfall time series based on MBLRP model were also smaller than those derived from the observed rainfall time series by 20% to 45%. The degree of underestimation of design flood increases with the increase of the recurrence interval of the design flood.

• Korean Journal of Remote Sensing
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• v.21 no.6
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• pp.493-503
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• 2005

In this study, the weight of evidence(WofE) technique based on GIS was applied to spatially estimate the groundwater yield characteristics at the Pocheon area In Gyunggi-do. The groundwater preservation depends on many hydro-geologic factors that include hydrologic data, land-use data, topographic data, geological map and other natural materials collected at the site, even with man-made things. All these data can be digitally processed and managed by GIS database. In the applied technique of WofE, the prior probabilities were estimated as the factors that affect the yield on lineament, geology, drainage pattern or river system density, landuse and soil. We calculated the value of the weight values, W+ and W-, of each factor and estimated the contrast value of it. Results by the groundwater yield characteristic computation using this scheme were presented feasibility map in the form of the posterior probability to the consideration of in-situ samples. It is concluded that this technique is regarded as one of the effective techniques for the feasibility mapping related to the estimation of groundwater-bearing potential zones and its spatial pattern.

• Water for future
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• v.19 no.3
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• pp.249-258
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• 1986

The purpose of this study is to estimate the PMP frequency factor for evaluation of the Probable Maximum Precipitation (PMP) in Korea. The value of PMP is the criterion of the determination of design rainfall in Planning and designing hydraulic structures, and water resources management. To obtain the object, 12 key stations were selected in which have the automatic rain0recording paper of 20 years, and the annual maximum rainfall values were calculated for each 7 durations(10 min., 1, 2, 4, 6, 12, 24 hr.). The statistics(mean, standard deviation)were estimated, and diagram which shows the relationship between mean annual maximum rainfall($$) and frequency factor for each durations were drawn. PMP was estimated by statistical method using the PMP frequency factor obtained from the diagram and statistics($$, Sn). The PMP-Duration Equation was derived from the envelope curve in order to obtain the PMP for an arbitrary duration. The isohyetal map of 24 hours PMP and PMP. DAD curve for the whole of Korea were drawn in accordance with the point PMP values.

• Korean Journal of Ecology and Environment
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• v.56 no.4
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• pp.330-338
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• 2023

To investigate the impact of forestry projects on the carbon stocks of forests, we estimated the carbon stock change of above-ground and soil before and after forestry projects using forest type maps, forestry project information, and soil information. First, we selected six map sheet with large areas and declining age class based on forest type map information. Then, we collected data such as forest type maps, growth coefficients, soil organic matter content, and soil bulk density of the estimated areas to calculate forest carbon storage. As a result, forest carbon stocks decreased by about 34.1~70.0% after forestry projects at all sites. In addition, compared to reference studies, domestic forest soils store less carbon than the above-ground, so it is judged that domestic forest soils have great potential to store more carbon and strategies to increase carbon storage are needed. It was estimated that the amount of carbon stored before forestry projects is about 1.5 times more than after forestry projects. The study estimated that it takes about 27 years for forests to recover to their pre-thinning carbon stocks following forestry projects. Since it takes a long time for forests to recover to their original carbon stocks once their carbon stocks are reduced by physical damage, it is necessary to plan to preserve them as much as possible, especially for highly conservative forests, so that they can maintain their carbon storage function.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.8-17
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• 2011

Recently, fusion camera systems that consist of depth sensors and color cameras have been widely developed with the advent of a new type of sensor, time-of-flight (TOF) depth sensor. The physical limitation of depth sensors usually generates low resolution images compared to corresponding color images. Therefore, the pre-processing module, such as camera calibration, three dimensional warping, and hole filling, is necessary to generate the high resolution depth map that is placed in the image plane of the color image. However, the result of the pre-processing step is usually inaccurate due to errors from the camera calibration and the depth measurement. Therefore, in this paper, we present a depth map upsampling method robust these errors. First, the confidence of the measured depth value is estimated by the interrelation between the color image and the pre-upsampled depth map. Then, the detailed depth map can be generated by the modified kernel regression method which exclude depth values having low confidence. Our proposed algorithm guarantees the high quality result in the presence of the camera calibration errors. Experimental comparison with other data fusion techniques shows the superiority of our proposed method.

• Journal of Korean Society of Forest Science
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• v.99 no.6
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• pp.827-835
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• 2010

Reliable forest statistics provides important information to meet the UNFCCC. In this respect, the national forest inventory has played a crucial role to provide the reliable forest statistics for several decades. However, the previous forest statistics calculated by administrative district has not provided spatial information in a small scale. Thus, this study focused on developing models to estimate an explicit spatial distribution of forest growing stock. For this, first, stand volume model by stand types was developed using National Forest Inventory(NFI) data. Second, forest type map was integrated with this model. NFI data were used to calculate plot-level stand volume and basal area. The stand types of NFI plot including the species composition, age class, DBH class and crown density class are very crucial data to be connected with forest type map. Finally, polygonlevel stand volume map was developed with spatial uncertainty map. Average stand volume was estimated at 85.7 $m^3$/ha in the study area, and at 95% significance interval it was ranged from 79.7 $m^3$/ha to 91.8 $m^3$/ha.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1133-1148
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• 2019

Tree growth and vitality in forest shows seasonal changes. So, in order to detect forest damage accurately, we have to use satellite images before and after damages taken at the same season. However, temporal resolution of high or medium resolution images is very low,so it is not easy to acquire satellite images of the same seasons. Therefore, in this study, we estimated spectral information of the same DOY using time-series Landsat images and used the estimates as reference values to assess forest damages. The study site is Hwasun, Jeollanam-do, where forest damage occurred due to hail and drought in 2017. Time-series vegetation index (NDVI, EVI, NDMI) maps were produced using all Landsat 8 images taken in the past 3 years. Daily normal vegetation index maps were produced through cloud removal and data interpolation processes. We analyzed the difference of daily normal vegetation index value before damage event and vegetation index value after event at the same DOY, and applied the criteria of forest damage. Finally, forest damage map based on daily normal vegetation index was produced. Forest damage map based on Landsat images could detect better subtle changes of vegetation vitality than the existing map based on UAV images. In the extreme damage areas, forest damage map based on NDMI using the SWIR band showed similar results to the existing forest damage map. The daily normal vegetation index map can used to detect forest damage more rapidly and accurately.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.19 no.5
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• pp.11-17
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• 2016

The purposes of this research are to estimate area of greenable roof and to monitor maintaining of green roofs using World-View 2 images. The contents of this research are development of World-View 2 application technologies for estimation of green roof area and development of monitoring and maintaining of green roofs using World-View 2 images. The available green roof areas in Gwangjin-gu Seoul, a case for this study, were estimated using digital maps and World-View 2 images. The available green roof area is approximately 12.17% ($2,153,700m^2$) of the total area, and the roof vegetation accounts for 0.46% ($80,660m^2$) of the total area. For verification of the extracted roof vegetation, Vworld 3D Desktop map service was applied. The study results may be used as a decision-making tool by the government and local governments in determining the feasibility of green roof projects. In addition, the project implementer may periodically monitor to see whether roof greening has maintained for efficient management of projects, and a vast amount of World-View 2 images may be regularly used before and after the projects to contribute to sharing of satellite images information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2657-2675
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• 2013

A novel neighbor selection-based fingerprinting algorithm using matrix correlation (MC) for Wi-Fi localization is presented in this paper. Compared with classic fingerprinting algorithms that usually employ a single received signal strength (RSS) sample, the presented algorithm uses multiple on-line RSS samples in the form of a matrix and measures correlations between the on-line RSS matrix and RSS matrices in the radio-map. The algorithm makes efficient use of on-line RSS information and considers RSS variations of reference points (RPs) for localization, so it offers more accurate localization results than classic neighbor selection-based algorithms. Based on the MC algorithm, an error estimation method using artificial neural network is also presented to fuse available information that includes RSS samples and localization results computed by the MC algorithm and model the nonlinear relationship between the available information and localization errors. In the on-line phase, localization errors are estimated and then used to correct the localization results to reduce negative influences caused by a static radio-map and RP distribution. Experimental results demonstrate that the MC algorithm outperforms the other neighbor selection-based algorithms and the error estimation method can reduce the mean of localization errors by nearly half.