• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.367-378
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• 2021

Field compost is a representative non-point pollution source for livestock. If the field compost flows into the water system due to rainfall, nutrients such as phosphorus and nitrogen contained in the field compost can adversely affect the water quality of the river. In this paper, we propose a method for detecting field compost using unmanned aerial vehicle images and deep learning-based semantic segmentation. Based on 39 ortho images acquired in the study area, about 30,000 data were obtained through data augmentation. Then, the accuracy was evaluated by applying the semantic segmentation algorithm developed based on U-net and the filtering technique of Open CV. As a result of the accuracy evaluation, the pixel accuracy was 99.97%, the precision was 83.80%, the recall rate was 60.95%, and the F1-Score was 70.57%. The low recall compared to precision is due to the underestimation of compost pixels when there is a small proportion of compost pixels at the edges of the image. After, It seems that accuracy can be improved by combining additional data sets with additional bands other than the RGB band.

• Journal of Korean Society of Forest Science
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• v.100 no.3
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• pp.455-465
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• 2011

In order to assess and mitigate climate change, the role of forest biomass as carbon sink has to be understood spatially and quantitatively. Since existing forest statistics can not provide spatial information about forest resources, it is needed to predict spatial distribution of forest biomass under an alternative scheme. This study focuses on developing an upscaling method that expands forest variables from plot to landscape scale to estimate spatially explicit aboveground biomass(AGB). For this, forest stand variables were extracted from National Forest Inventory(NFI) data and used to develop AGB regression models by tree species. Dominant/codominant height and crown density were used as explanatory variables of AGB regression models. Spatial distribution of AGB could be estimated using AGB models, forest type map and the stand height map that was developed by forest type map and height regression models. Finally, it was estimated that total amount of forest AGB in Danyang was 6,606,324 ton. This estimate was within standard error of AGB statistics calculated by sample-based estimator, which was 6,518,178 ton. This AGB upscaling method can provide the means that can easily estimate biomass in large area. But because forest type map used as base map was produced using categorical data, this method has limits to improve a precision of AGB map.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.415-418
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• 2004

The Studying is on developing precision of the moisture information on a soil. We used the data of AQUA AMSR-E which were obtained by Direct Receiving System in Korea Meteorological Administration(KMA). Although we know the Soil Moisture Information(SMI) helps the numerical weather model to produce the realistic results, we couldn't do it for the problem on a spatial resolution of the data is too low to apply. So we've tried to develop in a spatial resolution by using the AMSR-E data with a Digital Elevation Model(DEM) and Normal Difference Vegetation Index(NDVI) from AQUA MODIS and compared the difference between their information in statics. The result is more precise than the simple algorithm by a polarization ratio, and we could get the better result to use in forecast practically, if it's apply to get more detail in the vegetation temperature.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.195-201
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• 2019

The Outgoing Longwave Radiation (OLR) is an important satellite-driven variable for understanding the Earth's energy budget balance. The geostationary OLR retrievals require angular and spectral integration using an empirical equation for irradiance flux-to-OLR from a regression analysis, which determines the accuracy of the narrowband satellite-based OLR. We selected homogeneous pixels which is satisfied less temporal-spatial variability of cloud, on three infrared channels (6.7, 10.8, $12.0{\mu}m$) of the first multipurpose geostationary satellite in Korea, namely the Communication, Ocean and Meteorological Satellite/Meteorological Imager (COMS/MI). Multiple regression analysis was performed to retrieve OLR with improved accuracy using selected parameters based on theoretical and physical significance. This algorithm yielded retrieval with higher accuracy than broadband-based OLR retrieval: RMSE of 10.54 to $3.81W\;m^{-2}$, and bias of -8.49 to $-0.07W\;m^{-2}$.

• Spatial Information Research
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• v.23 no.6
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• pp.89-98
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• 2015

In this study, The criteria for assessing the security-related functions and services using spatial information is deduced, and orders of priority a priority for the applicable alternatives of functions/services of intelligent security service application based on spatial information are suggested by calculating relative importance. Also this study suggested connection plan about service implementation of national security services by government ministry & local government. And, the intelligent security app service model which has possible substantiation and commercialization is proposed. This study performed the AHP as the final assessment criterions by 3 item in 1st class and 12 item in 2nd class. And, tried to implementation methods of the intelligent security service application(ex. control of emergency and the crime opportunity, real-time location tracking of protector, the device for missing child & dementia patient, user participation & provision of information).

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.41-53
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• 2020

The production of near- and off-shore fisheries in South Korea is decreasing due to rapid changes in the fishing environment, particularly including higher sea temperature in recent years. To improve the competitiveness of the fisheries, it is necessary to provide fish catch information that changes spatiotemporally according to the sea state. In this study, artificial intelligence models that predict the CPUE (catch per unit effort) of mackerel, anchovies, and squid (Todarodes pacificus), which are three major fish species in the near- and off-shore areas of South Korea, on a 15-km grid and daily basis were developed. The models were trained and validated using the sea surface temperature, rainfall, relative humidity, pressure,sea surface wind velocity, significant wave height, and salinity as input data, and the fish catch statistics of Suhyup (National Federation of Fisheries Cooperatives) as observed data. The 10-fold blind test results showed that the developed artificial intelligence models exhibited accuracy with a corresponding correlation coefficient of 0.86. It is expected that the fish catch models can be actually operated with high accuracy under various sea conditions if high-quality large-volume data are available.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.7A
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• pp.515-522
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• 2009

In this paper, a novel transmission scheme with spatial modulation is proposed for coded orthogonal frequency division multiplexing (OFDM). The multiple-input multiple-output (MIMO) technique, so-called spatial modulation (SM), divides input data into antenna index and data signals, transmitting data signals through the specific antenna chosen by the antenna index. In order to retrieve data stream at the receiver, SM needs to detect the antenna index which means that data signals are transmitted via a certain antenna. For this reason, it should be guaranteed that channel matrix is orthogonal. For the real environment, a MIMO channel has difficulty in maintaining orthogonality due to spatial correlation. Moreover, the receiver of the conventional SM is operated by hard decision, so that this scheme has a limit to be adopted for practical systems. Therefore, soft-output demappers for the conventional and proposed schemes are derived to detect antenna index and data stream by soft decision, and a novel transmission scheme combined with spatial modulation is proposed to improve the bit error rate (BER) performance of the conventional scheme.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1141-1150
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• 2006

In this study, we performed spatial cluster analysis which considered spatial information using earthquake data for Korean peninsula occurred on 1978 year to 2005 year. Also, we look into how to be clustered for regions using earthquake magnitude and frequency based on spatial scan statistic. And, on the basis of the results, we constructed earthquake map by earthquake outbreak risk and gave a possible explanation for the results of spatial cluster analysis.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.12 no.2
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• pp.50-60
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• 2009

A spatial decision making process is needed when a local government tries to make polices and plans for eco-tourism in urban and regional site scale. This study aimed to suggest an assessment model to support spatial decision making on planning and making polices for eco-tourism. The model composes 6 stages of 'setting up ecogeographic territories'. 'value analysis method as ecotourism resources' 'synthetic assessing', 'grading values', 'selecting main resources for ecotourism' and 'spatial decision making support'. Applying the model to Shiheung city in Kyounggi province, validity was secured. By using the model, it was possible to make some decisions effectively such as selection of ecotourism resources, decision of the priorities of polices for ecotourism, and setting up the type of ecotourism to be introduced. In addition, by visualizing high valued resources and areas for ecotourism it w possible to support to make plans and policies effectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.800-802
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• 2016

In these days, the profitability of cadastral survey for national spatial information is getting worse. In order to reinforce the structure of the profitability, there exists the necessity to launch new and various businesses except the cadastral survey. In manipulating national spatial data effectively, it is necessary to design a platform for spatial information. Against this backdrop, we propose a platform for spatial data on the basis of Big Data in this paper.