• Journal of Environmental Impact Assessment
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• v.32 no.2
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• pp.61-71
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• 2023

As differences in the impact of each species on a spatial scale occur, analysis at the landscape scale is necessary to evaluate the impact of a development project. In previous studies, the Incidence Function Model (IFM) based on meta population theory was used to analyze the impact of species on the environment that changes according to urban development. However, since the model was required at least 10 occupied areas, it is difficult to use it for species that are difficult to monitor such as endangered species. Therefore, we proposed the Incidence Function Model (IFM) using species distribution model to fill the species data. In addition, we reviewed whether the developed model can be used in environmental impact assessment. As a result of the analysis, the minimum occupancy of Prionailurus bengalensis on urban development decreased to 56.5% and the possibility of survival to 28.7%. We confirmed that It rapidly decreased from the reference points of 230 and 70habitats through analysis of the meta-population capacity according to the decrease in the number of habitats. These results can be assessing the environment impact of each species on habitat loss. And it can support decision-making on the minimum number and area of habitat for species protection. This study is expected to be used as basic data for environment impact assessment on before and after development projects and mitigation measures plans, thereby increasing the effectiveness of reduction plans.

• Journal of Cadastre & Land InformatiX
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• v.53 no.2
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• pp.19-37
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• 2023

This study empirically analyzed the determinants of the assessment ratio (hereinafter 'AR') based on a total of 2,129 sales cases of forests in Gwangju, Gyeonggi-do. The main findings of this study through multiple regression analysis are summarized as follows. First, this study shows that regional characteristics have significantly different effects on the AR of forest land prices. Specifically, there was a significant difference in the AR depending on the location of the parcel by sub-region and the ratio of residential area, and the higher the number of development plans in progress, the more likely the officially assessed land price will be formed close to the sale price. Second, this study analyzed that location characteristics such as the proximity of the inner and outer center of the jurisdiction and traffic accessibility had a significant influence on the determination of the AR. Third, this study identified significant differences in AR depending on detailed factors such as planning management areas, production management areas, conservation areas for mountain, conservation areas for nature, and restricted development areas as land use and regulatory characteristics of forest lands. Fourth, this study found that land characteristics are a significant factor influencing the AR as an individual factor in forest land.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.467-480
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• 2011

Spatial and temporal variabilities of NPP(Net Primary Production) retrieved from two satellite instruments, AVHRR(Advanced Very High Resolution Radiometer, 1981-2000) and MODIS(MODerate-resolution Imaging Spectroradiometer, 2000-2006), were investigated. The range of mean NPP from A VHRR and MODIS were estimated to be 894-1068 $g{\cdot}C/m^2$/yr and 610-694.90 $g{\cdot}C/m^2$/yr, respectively. The discrepancy of NPP between the two instruments is about 325 $g{\cdot}C/m^2$/yr, and MODIS product is generally closer to the ground measurement than AVHRR despite the limitation in direct comparison such as spatial resolution and vegetation classification. The higher NPP values over South Korea are related to the regions with higher biomass (e.g., mountains) and higher annual temperature. The interannual NPP trends from the two satellite products were computed, and both mean annual trends show continuous NPP increase; 2.14 $g{\cdot}C/m^2$/yr from AVHRR(1981-2000) and 6.08 $g{\cdot}C/m^2$/yr from MODIS (2000-2006) over South Korea. Specifically, the higher increasing trends over the Southwestern region are likely due to the increasing productivity of crop fields from sufficient irrigation and fertilizer use. The retrieved NPP shows a closer relationship between monthly temperature and precipitation, which results in maximum correlation during summer monsoons. The difference in the detection wavelength and model schemes during the retrieval can make a significant difference in the satellite products, and a better accuracy in the meterological and land use data and modeling applications will be necessary to improve the satellite-based NPP data.

• Journal of Korea Water Resources Association
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• v.47 no.6
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• pp.501-511
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• 2014

The effects of initial conditions and input values of the rainfall-runoff model were studied in the applications of a lumped concept model for flood event data extension. For the initial conditions of the rainfall-runoff model, baseflow effects and spatial distributions of saturation points ($R_{sa}$) for the storage function methods (SFM) were analyzed. In addition, researches on the effects of rainfall data conditions as input values for the rainfall-runoff model were performed. The Chungju Dam watershed was selected and divided into 3 catchments including smaller size of 22 sub-catchments. The observed discharge and inflow amounts at Yeongwol 1, Chungju Dam, and Yeongwol 2 water level stations were individually operated as criteria for flood data extension in 30 flood events from 1993 to 2009. Direct and base flow were distinguished from a stream flow. In order to test capability of flood data extension, obtained base flow was applied to the rainfall-runoff model for three water level stations. When base flow was adopted in the model, the Nash-Sutcliffe Efficiency(NSE) was increased. The numbers of over satisfaction for model performance (>0.5) were increased over 10%. Saturation points ($R_{sa}$) which strongly influence the runoff amount when rainfall starts were optimized based on the runoff amount at three water level stations. The sizes of saturation points for three locations were similar which means saturation point size is not depending on the runoff amount. The effects of rainfall information for flood runoff were tested at 2002ev1 and 2008ev1. When increased the amount of rainfall information, the runoff simulations were closer to the simulations with full of rainfall information. However, the size of improvement was not substantial on rainfall-runoff simulations in terms of the size of total amount of rainfall.

• Journal of the Korean Geographical Society
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• v.28 no.4
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• pp.312-320
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• 1993

Along with the fade out of the Cold War the world is undergoing a fundamental restructuring. The process is generally refered to regionalization and globalization. In this context, the Paper presents a geopolitical perspective on the future of Northeast Asia. To meet the global trend, it is expected that the countries in the area organize an economically cooperative unity, the concept of which the author calls the northeast Asian Rim (NEAR). With its huge potentials to become the largest economic area in the world and with its rather complicated historical and social background, the Rim is tentatively supposed to have a loose and soft organization, to be flexible in dealing with the intra-and interregional relations. The idea underlying the view is that the former area of confrontation between the land power and the sea power is, under the new world environment, going to recover its proper locational attributes and develop into a merging area, a new core. As a physical framework of the Rim a spatial structurc is assumed to consist of two-subrims and two development axes with four development centers.

• Korean Journal of Environment and Ecology
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• v.23 no.2
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• pp.208-219
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• 2009

This study is to establish a management method for conservation through comparison and analysis on vegetation structures of Pinus densiflora forest around Beopjusa area for past 17-year. The spatial range of the study was $3.6km^2$ from maintenance office to Beopjusa area. The analysis results of the actual vegetation showed that the ratio of vegetation were composed of 64.7% of Pinus densiflora forest, 3.2% of mixed forest of P. densiflora and deciduous broadleaf trees and 5.9% of deciduous broadleaf tree community out of overall area, 360ha. The type of P. densiflora forest were categorized into four communities; community having high potential of succession, community having low potential of it, the community being in the process of succession and community being in the process of natural selection. The succession tendency was in order of the community having low potential of succession(P. densiflora forest), having high potential of it(P. densiflora forest which is deciduous broadleaf trees are dominating in sub-canopy layer), being in the process of succession(P. densiflora-Prunus sargentii and P. densiflora-Quercus serrata community) and being in the process of natural selection(Q. serrata-P. densiflora and Q. aliena-P. densiflora community). In terms of vegetation management, P. densiflora forest having high potential of succession was needed to remove deciduous broadleaf trees in the sub-canopy layer and the community being in the process of succession was required to be pruning the branch in the canopy layer. Lastly, the community being in the process of natural selection was suggested to let it be in succession, since it is hard to be in the status of P. densiflora Forest.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.215-231
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• 2020

Forest landscape models (FLMs) can be used to investigate the complex interactions of various ecological processes and patterns, which makes them useful tools to evaluate how environmental and anthropogenic variables can influence forest ecosystems. However, due to the large spatio-temporal scales in FLMs studies, parameterization and validation can be extremely challenging when applying to new study areas. To address this issue, we focused on the parameterization and application of a spatially explicit forest landscape model, LANDIS-II, to Mt. Gyebang, South Korea, with the use of the National Forest Inventory (NFI) and long-term ecological research (LTER) site data. In this study, we present the followings for the biomass succession extension of LANDIS-II: 1) species-specific and spatial parameters estimation for the biomass succession extension of LANDIS-II, 2) calibration, and 3) application and validation for Mt. Gyebang. For the biomass succession extension, we selected 14 tree species, and parameterized ecoregion map, initial community map, species growth characteristics. We produced ecoregion map using elevation, aspect, and topographic wetness index based on digital elevation model. Initial community map was produced based on NFI and sub-alpine survey data. Tree species growth parameters, such as aboveground net primary production and maximum aboveground biomass, were estimated from PnET-II model based on species physiological factors and environmental variables. Literature data were used to estimate species physiological factors, such as FolN, SLWmax, HalfSat, growing temperature, and shade tolerance. For calibration and validation purposes, we compared species-specific aboveground biomass of model outputs and NFI and sub-alpine survey data and calculated coefficient of determination (R²) and root mean square error (RMSE). The final model performed very well, with 0. 98 R² and 8. 9 RMSE. This study can serve as a foundation for the use of FLMs to other applications such as comparing alternative forest management scenarios and natural disturbance effects.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.2
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• pp.80-98
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• 2023

This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.481-493
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• 2023

In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

• Korean Journal of Heritage: History & Science
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• v.56 no.3
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• pp.174-193
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• 2023

Korea is surrounded by the sea and has rivers connecting to it throughout the inland areas, which has been a geographical characteristic since ancient times. As a result, there have been exchanges and conflicts with various countries through the sea, and rivers have facilitated the transportation of ships carrying grain, goods paid for by taxes, and passengers. Since the past, the sea and rivers have had a significant impact on the lives of Koreans. Consequently, it is expected that there are many cultural heritages submerged in the sea and rivers, and continuous efforts are being made to discover and preserve them. Underwater cultural heritage is difficult to discover due to its location in the sea or rivers, making direct visual observation and exploration challenging. To overcome these limitations, various geophysical survey techniques are employed. Geophysical survey methods utilize the physical properties of elastic waves, including their reflection and refraction, to conduct surveys such as bathymetry, underwater topography and strata. These techniques detect the physical characteristics of underwater objects and seafloor formation in the underwater environment, analyze differences, and identify underwater cultural heritage located on or buried in the seabed. Bathymetry uses an echo sounder, and an underwater topography survey uses a side-scan sonar to find underwater artifacts lying on or partially exposed to the seabed, and a marine shallow strata survey uses a sub-bottom profiler to find underwater heritages buried in the seabed. However, the underwater cultural heritage discovered in domestic waters thus far has largely been accidental findings by fishermen, divers, or octopus hunters. This study aims to analyze and summarize the latest research trends in equipment used for underwater cultural heritage exploration, including bathymetric surveys, underwater topography surveys and strata surveys. The goal is to contribute to research on underwater cultural heritage investigation in the domestic context.