본 연구는 강원도를 대상으로 산림복지 서비스의 유형을 객관적으로 구분하는 것을 목적으로 하였다. 군집분석을 위한 주요인자는 산림자원(산림비율(%), 임목축적(m3), 국유림비율(%)), 산림기반시설(트레킹길, 자연휴양림, 삼림욕장, 숲 야영장, 고요한마을·계곡(수)), 임업소득(임산물생산액, 산촌생태마을, 복합경영단지(수))을 선정하였다. 주요인자의 단위는 표준화를 실시하였으며, 계층적 군집분석과 비계층적 군집분석방법을 적용하여 유형구분을 실시하였다. 또한, 판별분석과 카이제곱 검정을 이용하여 통계적 검정 및 산림복지 서비스의 유형별 특성을 분석하였다. 군집분석 결과, 강원도는 4개의 군집으로 분류되었으며, 판별분석에 의한 분류 정확도는 비계층적 군집분석이 약77.8%로 계층적 군집분석보다 약 5.6% 높았다. 또한, 군집Ⅰ 과 군집Ⅳ 는 산림복지 서비스 실현을 위하여 가장 적합한 지역이었으며, 군집Ⅱ 는 산림복지 서비스를 향상을 위하여 산림관련 기반 구축이 요구되는 지역으로 판단된다.

This study aims to classify the type of forest welfare service by using the cluster analysis in Gangwon province. We selected three main factors to characterize the forest welfare services by counties and cities within the province; the amount of forest resources(forest area(%), growing stock(m3), national forest(%)), forest infrastructures(mountain trail(No.), national recreational forest(No.), forest bathing facility(No.), forest campground(No.), the mountain calm village and valley(No.)) and forestry-based income(forest production(won), mountain eco-village(No.), Agroforestry complex(No.). Data normalization was conducted and then the data was used to classify the type of forest welfare service using the hierarchical and non-hierarchical cluster analysis with discriminant analysis and chi-square test. Results showed that Gangwon province was grouped into 4 different types and the agreement rate by the discriminant analysis was 5.6% higher in the hierarchical clustering(77.8%) than in the non-hierarchical clustering(72.2%). In addition, group Ⅰ and Ⅳ were the most appropriate regions in that the those regions show great potential to directly apply the forest welfare services while group Ⅱ is necessaryThis study aims to classify the type of forest welfare service by using the cluster analysis in Gangwon province. We selected three main factors to characterize the forest welfare services by counties and cities within the province; the amount of forest resources(forest area(%), growing stock(m3), national forest(%)), forest infrastructures(mountain trail(No.), national recreational forest(No.), forest bathing facility(No.), forest campground(No.), the mountain calm village and valley(No.)) and forestry-based income(forest production(won), mountain eco-village(No.), Agroforestry complex(No.). Data normalization was conducted and then the data was used to classify the type of forest welfare service using the hierarchical and non-hierarchical cluster analysis with discriminant analysis and chi-square test. Results showed that Gangwon province was grouped into 4 different types and the agreement rate by the discriminant analysis was 5.6% higher in the hierarchical clustering(77.8%) than in the non-hierarchical clustering(72.2%). In addition, group Ⅰ and Ⅳ were the most appropriate regions in that the those regions show great potential to directly apply the forest welfare services while group Ⅱ is necessaryThis study aims to classify the type of forest welfare service by using the cluster analysis in Gangwon province. We selected three main factors to characterize the forest welfare services by counties and cities within the province; the amount of forest resources(forest area(%), growing stock(m3), national forest(%)), forest infrastructures(mountain trail(No.), national recreational forest(No.), forest bathing facility(No.), forest campground(No.), the mountain calm village and valley(No.)) and forestry-based income(forest production(won), mountain eco-village(No.), Agroforestry complex(No.). Data normalization was conducted and then the data was used to classify the type of forest welfare service using the hierarchical and non-hierarchical cluster analysis with discriminant analysis and chi-square test. Results showed that Gangwon province was grouped into 4 different types and the agreement rate by the discriminant analysis was 5.6% higher in the hierarchical clustering(77.8%) than in the non-hierarchical clustering(72.2%). In addition, group Ⅰ and Ⅳ were the most appropriate regions in that the those regions show great potential to directly apply the forest welfare services while group Ⅱ is necessaryThis study aims to classify the type of forest welfare service by using the cluster analysis in Gangwon province. We selected three main factors to characterize the forest welfare services by counties and cities within the province; the amount of forest resources(forest area(%), growing stock(m3), national forest(%)), forest infrastructures(mountain trail(No.), national recreational forest(No.), forest bathing facility(No.), forest campground(No.), the mountain calm village and valley(No.)) and forestry-based income(forest production(won), mountain eco-village(No.), Agroforestry complex(No.). Data normalization was conducted and then the data was used to classify the type of forest welfare service using the hierarchical and non-hierarchical cluster analysis with discriminant analysis and chi-square test. Results showed that Gangwon province was grouped into 4 different types and the agreement rate by the discriminant analysis was 5.6% higher in the hierarchical clustering(77.8%) than in the non-hierarchical clustering(72.2%). In addition, group Ⅰ and Ⅳ were the most appropriate regions in that the those regions show great potential to directly apply the forest welfare services while group Ⅱ is necessary