• Journal of Korean Society for Geospatial Information Science
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• v.20 no.3
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• pp.11-18
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• 2012

Increasing concern about biodiversity has lead to a rise in demand on the spatial assessment of biological resources such as biodiversity assessment, protected area selection, habitat management and restoration in Korea. The purpose of this study is to create species richness map through data collection and modeling techniques for wildlife habitat assessment. The GAM (Generalized Additive Model) is easy to interpret and shows better relationship between environmental variables and a response variable than an existing overlap analysis and GLM (Generalized Linear Model). The study area delineated by a large watershed contains Jirisan national park, Mt. Baekun and Sumjin river with three kinds of protected areas (a national park, a landscape ecology protected area and an otter protected area). We collected the presence-absence data for wildlife (mammals and birds) using a stratified random sampling based on a land cover in the study area and implemented natural and socio-environmental data affecting wildlife habitats. After doing a habitat use analysis and specifying significant factors for each species, we built habitat suitability models using a presence-absence model and created habitat suitability maps for each species. Biodiversity maps were generated by taxa and all species using habitat suitability maps. Significant factors affecting each species habitat were different according to their habitat selection. Although some species like a water deer or a great tit were distributed at the low elevation, most potential habitats for mammals and birds were found at the edge of a national park boundary or near a forest around the medium elevation of a mountain range. This study will be used for a basis on biodiversity assessment and proected area selection carried out by Ministry of Environment.

• Journal of Environmental Impact Assessment
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• v.33 no.2
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• pp.53-63
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• 2024

Biodiversity holds significant importance within the framework of environmental impact assessment, being utilized in site selection for development, understanding the surrounding environment, and assessing the impact on species due to disturbances. The field of environmental impact assessment has seen substantial research exploring new technologies and models to evaluate and predict biodiversity more accurately. While current assessments rely on data from fieldwork and literature surveys to gauge species richness indices, limitations in spatial and temporal coverage underscore the need for high-resolution biodiversity assessments through species richness mapping. In this study, leveraging data from the 4th National Ecosystem Survey and environmental variables, we developed a species distribution model using Random Forest. This model yielded mapping results of 24 mammalian species' distribution, utilizing the species richness index to generate a 100-meter resolution map of species richness. The research findings exhibited a notably high predictive accuracy, with the species distribution model demonstrating an average AUC value of 0.82. In addition, the comparison with National Ecosystem Survey data reveals that the species richness distribution in the high-resolution species richness mapping results conforms to a normal distribution. Hence, it stands as highly reliable foundational data for environmental impact assessment. Such research and analytical outcomes could serve as pivotal new reference materials for future urban development projects, offering insights for biodiversity assessment and habitat preservation endeavors.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.4
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• pp.59-64
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• 2008

We need to use the strength of each Species Distribution Model(SDM) because presence location data were only collected due to time and economic limitations in Korea. This study investigated and compared GAM(Generalized Additive Model) which is one of presence-absence models with Maxent(Maximum Entropy Model) which is one of presence only models according to location data(presence/absence data). The target species was Fisher(Martes pennanti) which is an endangered species in California, USA. We implemented environmental data such as topography, climate and vegetation, and applied models to sub-regions and study area. The results of this study were as follows. Firstly, GAM which used real presence and absence data was better than GAM which used pseudo-absence data and Maxent which used presence-only data. Secondly, Maxent was better than GAM when presence-only data were used. Lastly, each model which applied to different regions didn't predict other area well due to the difference of habitat environment and over-predicted outside of study area. We need to select an optimal model to predict a suitable habitat according to the type and distribution of location data.

• Journal of Environmental Impact Assessment
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• v.24 no.3
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• pp.260-277
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• 2015

The object of this study was the climate change sensitivity assessment of Korean Fir and Khinghan Fir as a representative subalpine plant in South Korea. Using species distribution models, we predicted the probability of current and future species distribution. According to this study, potential distribution that have been predicted based on the threshold (MTSS) is, Khinghan Fir was higher loss rate than Korean Fir. And in the climate change sensitivity assessment using the scalar sensitivity weight ($W_{is}$), $W_{is}$ of Korean Fir was higher relatively than the sensitivity of Khinghan Fir. When using the species distribution models as shown in this study may vary depending on the probability of presence data and spatial variables. Therefore should be prior decision studies on the ecological environment of the study species. Based on this study, if it is domestic applicable climate change sensitivity assessment method is developed. it would be important decision-making to climate change and biological diversity of adaptation policy.

• Journal of Environmental Impact Assessment
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• v.25 no.6
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• pp.432-441
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• 2016

In this study, we predicted species distributions in Mt. Inwang and Mt. An as preceding research to build ecological corridor by considering connectivity of habitats which have been fragmented in the city. We analyzed species distributions by using Maxent (Maximum Entropy Approach) model with species presence. We used 23 points of mammals and 15 points of Titmouse (Parus major, P. palustris, P. varius) as target species from appearance points of species examined. We build 4 geography factors, 4 vegetation factors, and 2 distance factors as model variables In case of mammals, factors that affected species distribution model was Digital Elevation Model(DEM, 34%) followed by Distance from edge forest to interior (24.8%) and Species of tree (10%). On the other hand, in case of Parus species, factors that affected species distribution model were DEM (39.6%) followed by distance from road (35.4%) and Density-class (8.2%). Therefore, birds and mammals prefer interior of mountain, and this area needs to be protected.

• Korean Journal of Environment and Ecology
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• v.32 no.5
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• pp.469-477
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• 2018

Hanabusaya asiatica is an endemic species whose distribution is limited in the mid-eastern part of the Korean peninsula. Due to its narrow range and small population, it is necessary to protect its habitats by identifying it as Key Biodiversity Areas (KBAs) adopted by the International Union for Conservation of Nature (IUCN). In this paper, we estimated potential natural habitats for H. asiatica using maximum entropy model (MaxEnt) and identified candidate sites for KBA based on the model results. MaxEnt is a machine learning algorithm that can predict habitats for species of interest unbiasedly with presence-only data. This property is particularly useful for the study area where data collection via a field survey is unavailable. We trained MaxEnt using 38 locations of H. asiatica and 11 environmental variables that measured climate, topography, and vegetation status of the study area which encompassed all locations of the border region between South and North Korea. Results showed that the potential habitats where the occurrence probabilities of H. asiatica exceeded 0.5 were $778km^2$, and the KBA candidate area identified by taking into account existing protected areas was $1,321km^2$. Of 11 environmental variables, elevation, annual average precipitation, average precipitation in growing seasons, and the average temperature in the coldest month had impacts on habitat selection, indicating that H. asiatica prefers cool regions at a relatively high elevation. These results can be used not only for identifying KBAs but also for the reference to a protection plan for H. asiatica in preparation of Korean reunification and climate change.

• Journal of Environmental Impact Assessment
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• v.24 no.1
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• pp.35-50
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• 2015

The purposes of this study are to apply species distribution modeling in urban management planning for habitat conservation in non-urban area and to provide a detailed classification method for management zone. To achieve these objectives, Species Distribution Model was used to generate species richness and then to compare with the results from land suitability assessment. 59 species distribution models were developed by Maxent. This study used 15 model variables (5 topographical variables, 4 vegetation variables, and 6 distance variables) for Maxent models. Then species richness was created by sum of predicted species distributions. Land suitability assessment was conducted with criteria from type I of "Guidelines for land suitability assessment". After acquiring evaluation values from species richness and land suitability assessment, the results from these two models were compared according to the five grades of classification. The areas with the identical grade in Species richness and land suitability assessment are categorized and then compared each other. The comparison results are Grade1 10.92%, Grade2 37.10%, Grade3 34.56%, Grade4 20.89% and Grade5 1.73%. Grade1 and Grade5 showed the lowest agreement rate. Namely, development or conservation grade showed high disagreement between two assessment system. Therefore, the areas located between urban, agriculture, forest, and reserve have a tendency to change easily by development plans. Even though management areas are not the core area of reserve, it is important to provide a venue for species habitat and eco-corridor to protect and improve biodiversity in terms of landscape ecology. Consequently, adoption of species richness in three levels of management area classification such as conservation, production, planning should be considered in urban management plan.

• Journal of Environmental Impact Assessment
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• v.24 no.2
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• pp.175-189
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• 2015

The objective of this study was to analyze characteristics of distribution of amphibian species and the affecting ecological factors. For the study, habitat environment factors were determined and applied to a habitat suitability model for the data collected from the Seom River in Hoengseong County and Wonju City, Gangwon Province, Korea between March 2013 to October 2013. The analyzed amphibian species were Rana nigromaculata, Hyla japonica, Rana dybowski, and Rana rugosa Temminck and Schlegel, and a logistic regression model was used with the pseudo-absence data. The result of the model analysis suggests that the major factors for Rana nigromaculata are distance to vegetation and rock and that for Hyla japonica is waterway. Rana dybowski and Rana rugosa Temminck and Schlegel have similar habitat characteristics, but the latter is shown to be dominant due to its wider habitat preference. According to the species richness model, the analyzed amphibian species are shown to have tendency to move between valleys or streams. This study quantitatively analyzed habitat environment characteristics using species distribution model, however, there is a limitation in terms of analysis on food factor and connectivity with other species. Combined with additional density or habitat analysis on birds or fish, this study can lead to more comprehensive analysis on biological environment factors.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.488-488
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• 2023

유량에 따른 수치모형(Nays2D) 하상변동 모의 결과를 토대로 서식처 적합도 분석 모델(PHABSIM: Phsical Habtiat Suitability Model)의 입력자료로 활용하여, 유량에 따른 하상 지형변화와 그에 따른 어류 서식처 적합도 변화를 분석한다. 금강 2km를 대상으로 2차원 모형인Nays2D를 적용하여 부등류 흐름(댐 방류량, 2년 빈도 유량, 100년 빈도 유량 등)에 따른 하상변동모의를 실시하였고, 모의 결과값(단면 표고, 유속, 수위)을 물리적 서식처 평가 모델인 PHABSIM의 입력자료로 활용하였다. 피라미 서식을 위한 적정 유속과 수심의 서식처 적합도 지수를 이용하여 각 유량별 가중가용면적(WUA: Weighted Usable Area)을 산정하여 비교 분석하여, 유량에 따른 단면 구조의 변화가 WUA와 피라미 서식처 적합도에 어떻게 영향을 미치는지 검토한다. 본 연구는 2차원 수치 모의 결과에 따른 단면(혹은 지형) 변화 양상과, 그에 따라 피라미를 비롯한 다른 생물종(어류, 저서성대형무척추동물)의 분포 경향에 연관성이 있는지를 실제 유량 변화와 생물종 조사 결과(물환경정보시스템에서 제공하는 생물종 데이터 활용)와 연계하여 검토 및 검증해보고, PHAMSIM을 이용한 서식처 적합도 분석 시 고려해야할 변수 및 검증 방법 제언에 중점을 둔다.

• Journal of Environmental Impact Assessment
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• v.23 no.6
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• pp.453-465
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• 2014

Hotspots are top sites in terms of species diversity as the most threatened and most diverse sites which have been used to select priority areas for reserves. The purpose of this paper is to identify biodiversity hotspots through analyzing nationwide spatial patterns of species richness and rarity of Korean mammals. Four endangered mammals and eleven common mammals were selected as target species. Environmental variables as model input data were consisted of topography, distance, and vegetation structure etc. and Maxent was used to develop species distribution models for target species. Species richness and rarity were used as index of biodiversity. The results of this study were as follows. Firstly, hotspots of species richness for endangered mammals were in high elevation and steep mountain areas. However, species richness for whole mammals were high in low elevation of mountains. Secondly, distribution pattern of species rarity for endangered mammals were similar as richness. However, hotspots of species rarity for whole mammals were a little different from species richness. Species rarity was high in both low and high elevation of mountain areas. This study will provide the useful information for a biodiversity assessment, a habitat conservation, a national ecological network plan, and the management of protected areas.