• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.5
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• pp.99-112
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• 2020

This study aims to propose biotope field datasheet and biotope type classification based on habitat-based by analyzing the German biotope system. The German system began in 1976 and has established a habitat-based national biotope classification system. On the other hand, Korea institutionalized in 2018 to build a classification system based on land use and land cover, which is a classification system that does not fully reflect ecosystem in Korea. Germany operates 44 biotope classification systems and 40 biotope field datasheet. Korea uses a single biotope field datasheet regardless of the biotope type. This classification system may not reflect the characteristics of Korea's biotope ecological habitat. The biotope classification system of Korea was proposed by dividing it into five categories: mountain ecology, freshwater ecology, land ecology, coastal ecology, and development area to reflect ecosystem habitat. The biotope type was designed as a system of large-classification-middle-small classification and subdivided into medium-classification and subdivided in each biotope system. The major classifications were classified into 44 categories according to the mountainous biotope(11), freshwater biotope(8), terrestrial biotope (12), coastal biotope(6), and development biotope(7). Unlike Germany, Korea's biotope field datasheet was proposed in five ways according to the classification of major ecosystem types. The results of this study are expected to contribute to the policy suggestion and the utilization of ecosystem conservation because the biotope classification system is classified to reflect the characteristics of ecosystem habitats.

• Ecology and Resilient Infrastructure
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• v.8 no.2
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• pp.97-111
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• 2021

This study was conducted to develop a habitat type classification system and its map based on the ecological characteristics of species, spatial type, vegetation, topography, and geological conditions preferred by species. To evaluate the relationships between species and their habitats in Korean national parks, we prepared a classification standard table for systematic classification of habitat types. This classification system divides habitats into 6 low-level and 59 mid-level ecological classes based on habitat structure. The mid-level system divided forest ecosystems into 20 subtypes, stream and wetland ecosystems into 8 types, coastal ecosystems into 7 types, arable land into 6 types, development land into 9 types, and 1 type of marine ecosystem. A habitat classification map was drawn utilizing square images, detailed vegetation maps, and forest stand maps, based on the above habitat classification system, and it covered 1,461 plots spanning 21 national parks. The habitat classification system and survey protocol, which consider domestic habitat conditions, should be further developed and applied to habitat assessment, to enhance the utility of this study.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.575-587
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• 2015

The development in data collection techniques results in high dimensional data sets, where discrimination is an important and commonly encountered problem that are crucial to resolve when high dimensional data is heterogeneous (non-common variance covariance structure for classes). An example of this is to classify microbial habitat preferences based on codon/bi-codon usage. Habitat preference is important to study for evolutionary genetic relationships and may help industry produce specific enzymes. Most classification procedures assume homogeneity (common variance covariance structure for all classes), which is not guaranteed in most high dimensional data sets. We have introduced regularized elimination in partial least square coupled with QDA (rePLS-QDA) for the parsimonious variable selection and classification of high dimensional heterogeneous data sets based on recently introduced regularized elimination for variable selection in partial least square (rePLS) and heterogeneous classification procedure quadratic discriminant analysis (QDA). A comparison of proposed and existing methods is conducted over the simulated data set; in addition, the proposed procedure is implemented to classify microbial habitat preferences by their codon/bi-codon usage. Five bacterial habitats (Aquatic, Host Associated, Multiple, Specialized and Terrestrial) are modeled. The classification accuracy of each habitat is satisfactory and ranges from 89.1% to 100% on test data. Interesting codon/bi-codons usage, their mutual interactions influential for respective habitat preference are identified. The proposed method also produced results that concurred with known biological characteristics that will help researchers better understand divergence of species.

• Spatial Information Research
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• v.10 no.4
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• pp.501-513
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• 2002

Eurasian otter (Lutra lutra) is one of endangered wildlife species whose population size is declining in Korea. To manage and conserve habitat for Eurasian otter, it is crucial to understand which habitat components affect otter habitat qualities. The objectives of this study were to develop a habitat suitability model of Eurasian otter in Soraksan National Park, to validate the model in Odaesan National Park. The research methods of this study were as follows. First, trace data and characters of Eurasian otter habitat were collected with Geographic Information System (GIS) data and Global Positioning System (GPS) receivers between 2000 and 2002. Second, the habitat use factors were identified as habitat characteristics of Eurasian otter and classified with habitat use and availability analyses. Third, significant factors of habitat model were extracted by Chi-square test. The last, Eurasian Otter Habitat Suitability Model (EOHSM) was employed by logistic regression method. Otter habitat use was positively associated with the reeds and shrubs areas adjacent to streams, the size of boulders, and low human disturbance in Soraksan National Park by EOHSM. This model had a classification accuracy of 74.4% at cutoff value of 0.5. Model validation showed a classification accuracy of 86.6 % at cut off value of 0.5 for otter habitat in Odaesan National Park.

• Ocean and Polar Research
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• v.35 no.4
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• pp.395-405
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• 2013

The aim of this study is to suggest an optimal survey method for coastal habitat monitoring around Weno Island in Chuuk Atoll, Federated States of Micronesia (FSM). This study was carried out to compare and analyze differences between in situ survey (PHOTS) and high spatial satellite imagery (Worldview-2) with regard to the coastal habitat distribution patterns of Weno Island. The in situ field data showed the following coverage of habitat types: sand 42.4%, seagrass 26.1%, algae 14.9%, rubble 8.9%, hard coral 3.5%, soft coral 2.6%, dead coral 1.5%, others 0.1%. The satellite imagery showed the following coverage of habitat types: sand 26.5%, seagrass 23.3%, sand + seagrass 12.3%, coral 18.1%, rubble 19.0%, rock 0.8% (Accuracy 65.2%). According to the visual interpretation of the habitat map by in situ survey, seagrass, sand, coral and rubble distribution were misaligned compared with the satellite imagery. While, the satellite imagery appear to be a plausible results to identify habitat types, it could not classify habitat types under one pixel in images, which in turn overestimated coral and rubble coverage, underestimated algae and sand. The differences appear to arise primarily because of habitat classification scheme, sampling scale and remote sensing reflectance. The implication of these results is that satellite imagery analysis needs to incorporate in situ survey data to accurately identify habitat. We suggest that satellite imagery must correspond with in situ survey in habitat classification and sampling scale. Subsequently habitat sub-segmentation based on the in situ survey data should be applied to satellite imagery.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.1
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• pp.57-71
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• 2007

While a concept on biotop or the urgency of its classification systems have been under discussion recently, this study aims to examine outdoor biotop classification systems for environment-friendly community. To this end, the feasibility of creating a biotop in the community and application elements were generated and biotops were classified and categorized. Then, elements that can be applied in consideration of traditional Korean techniques were generated and biotop classification systems and specific components in residential areas were reviewed. As for the result of this study, based on a preliminary draft prepared through literature review, considerations for biotop classification systems were taken into account. Then, based on classification criteria for biotop formats, biotop functions and biotop types, a second-tier classification system was developed. Criteria for biotop formats included surfaces, lines and points while criteria for biotop functions were large cores, small bases, corridors, stepping stones and ecological islands. Criteria for habitat types were divided to include natural forest, developed green areas, lacustrine wetland, palustrine wetland, shrubs, grasslands, linear habitats, vacant plots and practical green areas, which were sub-categorized. As for the biotop classification system, macro-classification divided biotops into three types-space, line and point-based on biotop formats. Meso-classification had five groups and micro-classification had 21 groups based on habitat types. Future studies should focus on the ecological features of each biotop categories generated in this study and their creation and management techniques to find many practical methods to create, protect and manage outdoor biotop for environment-friendly community.

• Journal of Korean Society of Forest Science
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• v.78 no.2
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• pp.177-188
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• 1989

The habitat typing method of classification based on community has been developed on many forested areas in the ROCKY MOUNTAINS of WESTERN NORTH AMERICA, and is being used in providing an objective principle of guide for classification of forest sites, land classification, vertical distribution and multipurpose management of forest. I actually made a trial of forest habitat type classification - The methodology can be segmented into a number of tasks including reconnaissance, selection of stands to be sampled, location of plots, data gathering, preliminary and computer analysis, preparation of key- and map of habitat type and description for each habitat type in a view of forest management - on UNIVERSITY OF MONTANA FORESTS in order to examine whether its application is fit or not in korean forest circumstances : these are composed mainly of artificial forest and forest in the early stage of succession. The main results obtained from this study were summarized as follows 1. A hierarchical classification-Climax, Habitat type and Phases-of forest sites was developed using the habitat typing method of classification. 2. A diagnostic key is provided for field identification of the types based upon presence and number of indicator species, and forest managers could prepare a map of habitat type and classify forest habirat types by reference to it. 3. The classified habitat types were considered to be effective on providing an objective principle of guide for multipurpose management of forest including potential productivity for timber, feed productivity of forage and wildlife, selection of the right species in the right sites, application of method of treatment and so forth. 4. Forest habitat type classifications based upon extrapolation which used relict species and associated stands is considered to be suitable for korean forest circumstances and objective in studying potential vegetation, vertical and horizontal distribution of forest.

• Spatial Information Research
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• v.8 no.1
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• pp.85-99
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• 2000

Accurate information on habitat distribution of protected fauna is essential for the habitat management of Korea, a country with very high development pressure. The objectives of this study were to develop a habitat suitability model of wild boar based on GIS and logistic regression, and to create habitat distribution map, and to prepare the basis for habitat management of our country s endangered and protected species. The modeling process of this restudyarch had following three steps. First, GIS database of environmental factors related to use and availability of wild boar habitat were built. Wild boar locations were collected by Radio-Telemetry and GPS. Second, environmental factors affecting the habitat use and availability of wild boars were identified through chi-square test. Third, habitat suitability model based on logistic regression were developed, and the validity of the model was tested. Finally , habitat assessment map was created by utilizing a rule-based approach. The results of the study were as folos. First , distinct difference in wild boar habitat use by season and habitat types were found, however, no difference in wild boar habiat use by season and habitat types were found , however, ho difference by sex and activity types were found. Second, it was found, through habitat availability analysis, that elevation , aspect , forest type, and forest age were significant natural environmental factors affecting wild boar hatibate selection, but the effects of slope, ridge/valley, water, and solar radiation could not be identified, Finally, the habitat at cutoff value of 0.5. The model validation showed that inside validation site had the classification accuracy of 73.07% for total habitat and 80.00% for cover habitat , and outside validation site had the classification accuracy of 75.00% for total habitat.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.91-102
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• 2012

As the basis of the environmental ecological river management, this research developed a method of habitat classification using imagery information to understand a distribution characteristics of fish living in a natural river. First, topographic survey and investigation of discharge and water temperature were carried out to analyze hydraulic characteristics of fish habitat, and the unmanned aerial photography was applied to acquire river imagery at the observation time. Riffle, pool, and glide regions were selected as river habitat to analyze fish distribution characteristics. Analysis showed that the standard deviation of RGB on the riffle is higher than pool and glide because of fast stream flow. From the classification accuracy estimation on riffle region according to resolution and kernel size using the characteristics of standard deviation of RGB, the highest classification accuracy was 77.17% for resolution with 30cm and kernel size with 11. As the result of water temperature observation on pool and glide using infrared camera, they were $19.6{\sim}21.3^{\circ}C$ and $15.5{\sim}16.5^{\circ}C$ respectively with the differences of $4{\sim}5^{\circ}C$. Therefore it is possible to classify pool and glide region using the infrared photography information. The habitat classification to figure out fish distribution can be carried out more efficiently, if unmanned aerial photography system with RGB and infrared band is applied.

• Journal of Environmental Impact Assessment
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• v.26 no.6
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• pp.385-403
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• 2017

This study showed the national ecosystem classification for the spatial standards of ecosystems-based approaches to the risk assessments and adaptation plan. The characteristics of climate change risk assessment, implement national adaptation plans, and ecosystem/habitat classification status was evaluated. Focusing on the land cover classification widely utilized as spatial data for the assessments of biodiversity and ecosystem services in the UK and other countries in Europe, the applicability of the national land cover classification for climate change risk assessments was reviewed. Considering the ecosystem classification for climate change risk assessment and establishing adaptation measures, it is difficult to apply rough classification method to the land cover system because of lack of information on habitat trend by categorization. The results indicated that forest ecosystems and agro-ecosystem occupied 62.3% and 25.0% of land cover, respectively, of the entire country. Although the area is small compared with the land area, wetland ecosystem (2.9%), marine ecosystem (0.4%), coastal ecosystem (0.6%), and urban ecosystem (6.1%) can be included in the risk assessments. Therefore, it is necessary to subdivide below the medium classification for the forest and agricultural land, as well as Inland wetland, which has a higher proportion of habitat preference of taxa than land area, marine/coastal habitat, and transition areas such as urban and natural ecosystem.