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ISSN : 1229-3857(Print)
ISSN : 2288-131X(Online)
Korean Journal of Environment and Ecology Vol.29 No.2 pp.236-249
DOI : https://doi.org/10.13047/KJEE.2015.29.2.236

Study on the Forest Watershed Classification Method for Forest Watershed Management1

Han Soo Kim2*, Yang Ju Lee2
2Dept. of Ecology & Environment, Gyeonggi Research Institute., Suwon, 440-290, Korea
Corresponding Author : Tel: +82-31-250-3536, Fax: +82-31-250-3113, kecoban@gmail.com
March 2, 2015 March 23, 2015 March 24, 2015

Abstract

The master plan of forest land management proposes forest watershed management that considers regional characteristics in order to overcome the problem of uniform forest land management. In order to manage the forest watersheds in Gyeonggi-do, this study classified 1,823 forest watersheds in Gyeonggi-do and attempted to understand their characteristics. It conducted a factor analysis and cluster analysis from the perspective of conservation value and development pressure using forest land indicators. In terms of conservation value, three factors were drawn: the topography factor, vegetation factor and public service factor, while in terms of development pressure, three factors were drawn: the easiness of development factor, economic benefits factor and development activity factor. Using these factors, forest watersheds were divided into three clusters in terms of conservation value while they were divided into three clusters in terms of development pressure. Using the results of the cluster analysis from a conservation-development perspective, the forest watersheds were classified into nine different types, and the characteristics were identified by each type. It is judged that the factors and clusters drawn as a result of the research accurately reflect the present conditions of Gyeonggi-do, and the nine types of forest watersheds have clear characteristics according to each type, which are judged to be utilized in forest management in the future.


초록


    INTRODUCTION

    1.Background and Purpose

    Recently, due to sudden changes in the natural environment caused by climate change, the importance of mountain management is becoming increasingly apparent in Korea where 64 % of its land is covered with mountains. While mountains and forests were recognized as places that produce wood in the past, they are now recognized for their role in carbon absorption, watershed conservation and disaster prevention, placing more emphasis on their various roles related to the quality of life (Kim and Gwon, 2013).

    According to the #Management of the Mountainous Districts Act,# as a basic principle of mountain management, mountains should be managed in the way that improves the productivity of forestry and the function of the public such as disaster prevention, water conservation, natural ecosystem conservation, natural landscape conservation and public health/recreation. However, profits are low in case the mountains are used for the purpose of forest product production, and the benefits are not as apparent when they are used as conservation areas for public interest. Therefore, there are cases in which mountains are used for other purposes in order to create developmental profits. Such a development has been carried out indiscriminately from national land, public land to private land, and this is a serious problem considering that 68 % of mountain areas are privately owned and of which are relatively easy to develop (Kim et al., 2014).

    An efficient and rational mountain management system is necessary to address high development pressure and rationally use mountains. However, Sohn et al. (2012) pointed out several problems with mountain management: discordance between mountain land classification and forest and classification on mountain management; a lack of consideration from the ecosystem connectivity perspective due to land unit-based management; uniform permission criteria which lacks the consideration for conditions by region, topography and location. Some other problems pointed out are the limitations of the system on land-use changes in mountain areas as it judges development possibilities based on only simple topography including altitude and slope; no development procedure was included in the Management of Mountainous Districts Act; and there was difficulty in follow-up management after development (Kim et al., 2012; No and Choi, 2013).

    Various efforts have been made to resolve the foregoing roblems, and in particular, the master plan of forest land management, which is an official plan based on the Management of Mountainous Districts Act, was established in 2013. This master plan of forest land management proposes a desirable management direction related to the comprehensive and rational conservation/use of mountain areas. In detail, it suggests a basic direction for the mountain ridge connectivity management system; eco-friendly mountain use/recovery system; green service; and efficient mountain information management system based on conservation forests and the comprehensive management of mountain landscape zones and forest watershed types (Korea Forest Service, 2013).

    The main purpose of the master plan for forest land management is to shift the focus from uniform mountain management to mountain management which takes into account regional characteristics. As a key concept for this, it is stated in the master plan that the classified spatial structures such as mountain landscape zones and forest watershed types will be used. Mountain landscape zones refer to 27 mountain zones nationwide that are classified according to mountain landscape, topography, ecology, economy, humanities and social science. This is a spatial structure that has been introduced for mountain management from the macroscopic viewpoint while maintaining the framework of forest ecosystems nationwide. In case of forest watershed types, the country is divided into small watersheds and they are classified into five types by comprehensively considering the urbanization ratio, accessibility to major mountain ridges and proximity to the coastline. Mountain watersheds that include or are adjacent to Baekdudaegan or Jeongmaek are classified as the major mountain ridge adjacent-type mountain; mountain watersheds adjacent to the coastline are called the coastal and insular-type mountain; places where the area ratio of build-up areas making up more than 35% are called city-type mountains; and places where the area ratio of build-up areas is 15 %~35 % are called city-neighboring type mountains. Efforts are being made to establish a detailed management strategy by connecting pending issues in relevant areas based on the classification of types (Korea Forest Service, 2013).

    The municipal governments have established a mountain management regional plan in 2014 in line with the direction of the master plan of forest land management. However, forest watershed types or the classification of nationwide forest watersheds into five types, was not practical to use because they are not detailed enough for local and municipal governments to use and are not reflected in the regional characteristics. In particular, because the most apparent and important issue is to solve problems that occur due to conflict between conservation value and development pressure, the necessity exists for the classification of spatial structures which has taken into account such characteristics.

    If we take a look at the preceding studies on mountain land classifications and forest watersheds, most of them focus on GIST application technologies and improvement plans for mountain land-use classifications and the validity of mountain land-use classifications in regards to conservation forests and semi-conservation forests stipulated in the Management of Mountainous Districts Act (Park et al., 2006; Park et al., 2009). Some municipal governments classified forest watersheds after taking into account local characteristics and tried to use their own classification of types. However, considering that mountain management based on the mountain management plan has only recently been implemented in Korea, there aren't enough study cases related to the methodologies for the classification of mountainous spatial structures.

    This study tried to review and select indices, which are related to various forest watersheds that are reflected in local characteristics at the municipal government level, that are applicable. Also, based on this, by using the factorial analysis and cluster analysis techniques, this study classified forest watersheds according to regional characteristics and set a management plan by type to use them as preliminary data for future mountain management.

    MATERIALS AND METHODS

    1.Study Site

    This study was carried out in Gyeonggi-do, Korea. In Gyeonggi-do, the mountain areas have been steadily decreasing due to a rapid increase in land-use changes in mountain areas. There are also having difficulties with mountain management owing to an increase in landslides, forest fires and forest diseases and pests caused by climate change. In particular, not only mountain situations but also the natural environment, humanities/social science, conservation/ semi-conservation forests and mountain-related issues are significantly different by city and county in Gyeonggi-do, which is composed of 31 cities and counties. Therefore, uniform management systems currently in use, such as slope and conservation/semi-conservation forests, do not fully correspond to reality any more. Accordingly, it was judged that Gyeonggi-do is an adequate study site for conducting research on the types of mountain watersheds when considering their characteristics. The study site is as shown in Figure 1.

    The mountain situation of Gyeonggi-do is as follows: 51.8 % of the total area is covered with mountains and the ratio of the mountain area to population is 43.7ha/ 1,000, 1/3 of the national average, due to a high density population. The ratio of the growing stock is 124.49m3/ha, which is similar to the national ratio and it is composed of broadleaf trees (38 %), coniferous trees (36 %) and mixed stand forests (26 %). In regards to the mountain classification, Gyeonggi-do is composed of semi-conservation forests (29.4 %) and conservation forests (70.6 %) (for forestry 43.5 %, for public use 27.1 %). 73.7 % of forest areas are privately owned, 7.8 % are public-owned forests and 18.5 % are national forests (Gyeonggi-do, 2014).

    The study site includes all mountain watersheds in Gyeonggi-do. However, some mountain areas in the northern part are restricted for civilians and were excluded due to the lack of information and accuracy.

    2.Setting of Forest Watersheds and Index

    In this study, there are forest watersheds that were used in the classification of mountain watershed types which are suggested in the master plan of forest land management. These forest watersheds are natural boundaries of which Sohn et al. (2011) reflected in the topographic characteristics of mountains in a spatial unit to overcome the limitations of mountain land management by land-use unit. Based on this, a forest watershed map for the establishment of the mountain management regional plan was created by the Korea Environmental Preservation Association, and this study used the Gyeonggi-do area in this forest watershed map.

    For the establishment of a detailed mountain management regional plan, the Korea Forest Service provides a mountainous index which provides information on mountain status by forest watershed. These mountainous indices are composed of a total of 36 indices: 15 mountainous land-based indices, 8 indices on mountainous land use for forestry purposes, 7 indices on mountainous land use for public purposes, 6 indices on mountainous land use for other purposes. Such mountainous indices helped us to identify the current situation of mountains and are used as a useful basis and a reference for the establishment of policies related to mountains.

    In this study, based on the 36 mountainous indices, seven indices, which are thought to be helpful in identifying the conservation value of mountains, and nine indices, which are thought to be helpful in identifying development pressure, were selected based on opinions from experts.

    4.Factor Analysis and Cluster Analysis Using the Mountain Indices

    There are many ways to classify multiple subjects of interest. In particular, factor analysis, which reflects the diverse characteristics of subjects and is conducted to classify types, and cluster analysis, which is carried out on factor scores, have been widely used. Cluster analysis is a technique of classifying multiple subjects of interest into groups after statistically identifying some of their characteristics when there is no appropriate criteria for classification (Lee, 2002). When classifying the subjects of interest using cluster analysis, instead of using indices as they are, the use of factor scores of indices that are obtained through principal component analysis allows for the precise classification of subjects.

    Cluster analysis is a statistical analysis method which classifies groups based on similarity, and inquires into similarity among individuals in the same group and dissimilarity with individuals in other groups. It is used to classify subjects with various characteristics into groups when there exists no clear criteria nor a set criteria to classify subjects. For a cluster analysis, the criteria to measure the similarity among subjects is necessary and the concept of distance is used most of the time. Based on index analysis results, subjects that are relatively close to each other are classified into the same group, and the core of cluster analysis is used to minimize changes within a group rather than changes among groups. Regarding the distance used at this time, there are Euclid distance, Mahalanobis distance, Minkowski distance and city-block distance according to calculation methods (Song and Jang, 2010).

    In this study, a cluster analysis was conducted which can reflect the regional characteristics at the municipal level to classify forest watersheds according to regional characteristics. To accomplish this, various indices related to forest watersheds were used; a factor analysis was conducted from the perspective of mountain conservation value and development pressure; the extracted factors were used. A principal component analysis (PCA) was conducted to identify the relationship among indices, and the Kaiser-Meyer-Oklin (hereinafter KMO) test and Bartlett's test of sphericity, which measure the appropriateness of samples, were carried out to identify whether the PCA was meaningful. As a result of KMO, the value of the seven indices on mountain conservation was 0.710, indicating that the variables selected for the PCA were useful. Also, as a result of Bartlett's test of sphericity, significance probability was 0.000, less than 0.05, implying that the use of PCA, which was carried out on the collected variables, is adequate. Also in case of the development pressure perspective, the variables were identified as good choices as the KMO value of the nine indices was 0.692, and the PCA was identified to be adequate for use as the significance probability was 0.000. Consequently, it was concluded that there were common factors among the variables.

    A verimax rotation, a method widely used to simplify factors, was performed. In this study, an above 0.40 was selected as an acceptance criterion for factor loading, which shows the degree of correlation among the factors of each variable. Also, an above 1.0 was selected as an eigen value, which shows how much explanation each factor can offer regarding total dispersion (Kim and oh, 2014).

    The cluster analysis was conducted through hierarchical clustering methods such as single linkage method, complete linkage method, average linkage method and ward's method. And K-means cluster analysis was performed based on the analysis results of the complete linkage method, which was judged to be most adequate, and the results were comprehensively deduced. At this time, hierarchial methods, cubic clustering criteria (CCC), pseudo F-statistic (PSF) and dendrogram, were referred to determine the adequate number of clusters.

    5.Classification of Forest Watersheds into Types

    Forest watersheds in Gyeonggi-do were classified into three clusters by conducting cluster analysis based on the three factors, which were deduced through factor analysis, from a conservative value perspective. Also, the forest watersheds were classified into three clusters based on the three factors deduced from the development pressure perspective. In order to comprehensively judge forest watershed characteristics from the perspectives of conservation value and development pressure, the clusters that were analyzed based on the two perspectives were classified into nine types using the matrix method. The attributes of clusters were analogized based on the average factor score of each factor of forest watershed that belongs to each cluster Also, a mountain management direction for each type was proposed after deducing the characteristics of the forest watershed types from the perspective of conservation and development through a comparative study with various spatial information data and the existing statistical data.

    RESULTS AND DISCUSSION

    1.Index Selection Results

    Among the 36 mountainous indices developed by the Korea Forest Service to analyze the characteristics of forest watersheds, this study selected indices that were judged to be useful in estimating mountain conservation value and development pressure.

    Seven indices were selected to estimate conservation value and they are shown in Table 1. R_top_side is an index which shows the area of the tops and the sides of mountains in the forest site map which classifies areas into five types of topography. The tops and the sides of mountains correspond to areas that are above three-tenths the height of a mountain and their necessity of special management was taken into account. Slope_ave is an index that shows the average slope of the relevant watershed, and it was judged to be necessary when considering natural disasters such as landslides and soil runoff. Height_ave was judged to be able to reflect conservation value from the perspective of unique landscape and vegetation. Age_ave and Diam_ave were selected as they present the quality of forest vegetation. R_S_Con was selected as it is directly connected with biodiversity and watershed soundness from the land ecological perspective, and was thought to be useful in evaluating the structural diversity of forests. R_Pub_Ctrl corresponds to forests for public use among conservation forests. This study considered that these areas, of which land-use is legally restricted due to their significant function of public interest, are highly valuable for conservation for public use.

    Nine indices were selected to evaluate development pressure and they are shown in Table 2. P_ave was judged to be the financial characteristics of forest watersheds. P_Lot_Mt considered the fact that demand for changes in land-use will increase to benefit from development when the gap between the appraised value of a site and mountain grows wider. R_private considered that the mountain management direction is different depending on who owns the area, and the development possibility of private forests is higher, for it is easier to development them compared to national forests. R_sem_pre considered that development pressure on semi-conservation forests is higher than conservation forests due to weaker regulations. R_Develop is an index that shows the area of development-induced districts and zones in the land use zoning of forest watersheds. It was selected as it enables the estimation of the current development situation and future development demand. Ct_Traffic was selected as it is an index that shows the current status of infrastructure for the development of highway IC and railway station within forest watersheds. Convert_form is an index that shows changes in mountain land use and was selected as it shows mountain development trends. Ar_Mt_U25 is an index which analyzed the area of mountains under a 25° slope considering that the average degree of slope used for land-use conversion is 25°. It shows areas where land-use conversion is possible. Ar_sem_U25 is an index which deduced the areas that can be developed from semiconservation forests, and it was selected, for it enables the possibility to estimate development.

    2.Factor Analysis Results

    The results of factor analysis conducted based on the seven indices that were judged to show conservation value are shown in Table 3. As the results of analyzing the seven variables after setting them as variables, there were three meaningful factors that had an eigen value of above 1.0.

    Factor 1 of the conservation value perspective explains four variables as one factor, and its eigen value was 3.595 and it had a variance explanation power of 51.354 %. Factor 1 of the conservation value perspective is composed of Slope_ave, Height_ave, R_S_Con and R_top_side, and was named as "topographic characteristic value" because it was judged to be able to offer an explanation on conservation value from the perspective of topographic characteristics of forest watersheds. In Factor 2 of the conservation value perspective, two variables are explained as one factor, and its eigen value was 1.407 and its variance explanation power was 20.097 %. It is composed of the Age_ave and Diam_ave of vegetation in mountains, and was named as "forest vegetation value" because it was judged to offer an explanation on conservation value from the perspective of forest vegetation. In Factor 3 of the conservation value perspective, one variable is explained as one factor, and its eigen value was 1.033 and its variance explanation power was 14.760 %. It is composed of R_Pub_Ctrl, and was named as a "public value" because it was judged to be able to offer an explanation on conservation value from the perspective of public interest. Factors 1, 2 and 3 were analyzed to have a total of 86.2% accumulated variance explanation power. These three factors are judged to be highly useful in explaining the characteristics of the conservation value of forest watersheds, and they were used for clustering.

    The results of factor analysis conducted based on the nine indices that were judged to show development pressure are shown in Table 4. Among them, a total of three factors meant that their eigen value was above 1.0. In Factor 1 of the development pressure perspective, four variables are explained as one factor, and its eigen value was 2.737 and variance explanation power was 30.145 %. It is compose of Ar_Mt_U25, Ar_sem_U25, R_private and R_sem_pre, and was named for "development ease" because it was judged to be able to offer an explanation on the ease of developing mountains. In Factor 2 of the development pressure perspective, three variables are explained as one factor, and its eigen value was 2.398 and variance explanation power was 26.646 %. It is compose of P_Lot_Mt, P_ave and Ct_Traffic, and was named as "financial benefits" because it was judged that it can offer an explanation on development pressure from the perspective of financial benefit from mountains. Factor 3 of the development pressure perspective, two variables are explained as one factor, and its eigen value was 1.095 and its variance explanation power was 12.172 %. It is composed of R_Develop and Convert_form, and was named as "development activity" because it was judged that it can offer an explanation on the degree of development activity in mountains. Factors 1, 2 and 3 were analyzed to have a total of 68.2 % accumulated variance explanation power. These three factors are judged to be highly useful in explaining the characteristics of the development pressure of forest watersheds, and they were used for clustering.

    3.Cluster Analysis Results

    The results of cluster analysis conducted based on the three factors that can explain conservation value are shown in Figure 2 and Figure 5. The average factor score by factor of each cluster was used to identify the characteristics of each cluster.

    The value of Cluster C-I is higher than other clusters from the perspective of topographic value and forest vegetation value, but its public value was low. Most of the forest watersheds that are located in the cities and the counties in Gapyeong, Yangpyeong and Yeoju belong to this cluster. There are a lot of large mountains located in these areas and their soundness of forest vegetation is high. However, because there aren't many build-up areas and the population density is low, few mountains are designated as the mountains for public use. The conservation value of forest watersheds that belong to this cluster is high from the perspective of mountain topography and vegetation in Gyeonggi-do.

    The topographic value factor and the public value factor of Cluster C-II is low, and the vegetation value factor was especially low. This is the forest watersheds that includes build-up areas in Yongin, Pyeongtaek, Goyang, Paju, Gwangju and Icheon. Most of the mountain watersheds are located in mountains that are fragmented due to build-up areas, roads and farmland, and the vegetation value is low because their vegetation is created by undergoing a secondary succession following some artificial disturbance. Also, the conservation value of mountains is low because the area designated as public forests is small.

    The topographic value factor of Cluster C-III is very low, but its vegetation value factor and public value factor are high. Many of the areas included in this cluster are located on the outskirts of Seoul, Uijeongbu, Guri, Hanam, Seongnam, Gwacheon, Suwon, Anyang, Gwangmyeong and Euiwang; and Hwanseong, Pyeongtaek, Siheong, Ansan and Kimpo of which include coastal areas. Also, the areas included in this cluster are judged to be the places where most of mountains are conserved for the quality of natural environment in those areas due to enhanced urbanization or coastal areas where outstanding forest vegetation is located. Although the topographic value of mountains in this cluster is low, the mountains are essential for the public interest, and the quality of their outstanding vegetation should also be maintained.

    The results of cluster analysis conducted based on the three factors that can explain development value are shown in Figure 3 and Figure 5. The average factor score by factor of each cluster was used to identify the characteristics of each cluster.

    In case of Cluster D-I, the development ease factor is very high, the financial benefit factor is low and the development activity factor is not high. Most of the forest watersheds that are located in Suwon, Osan, Gimpo, Goyang and Paju are covered with build-up areas or farmland, and these areas are covered with very small mountains and a lot of hills. Although the ease of development is high due to hilly areas, not much financial benefits can be expected as a lot of mountain areas are protected under regulation. It is judged that although not so high now, there is a high potential for development pressure in the future because there are many mountain areas that can be easily developed.

    In case of Cluster D-II, the development ease and the development activity factors are low and the financial benefit factor is high. Most of the forest watersheds, except the ones located in the outskirts of Seoul, belong to this cluster, and not much development has been achieved so far in those areas. There is a big difference between build-up areas and mountain areas, but the development is not active due to the shape of mountains and the high ecological value. Large-scale development is difficult due to the low easiness of land-use conversion, but development pressure is judged to be high in the boundaries of mountains and build-up areas due to the big difference.

    In case of Cluster D-III, development ease factor is high, financial benefit factor is slightly low and development activity is very high. Most of the mountain areas in Euijeongbu, Guri, Hanam, Seongnam, Gwacheon, Gwangmyeong, Bucheon, Yongin and Suwon, that are located in the outskirts of Seoul, belong to this cluster. The areas are easy to develop as most of the mountains are low or fragmented. Development projects are continuously in progress due to a rise in population. However, there is only a small gap between the land value of mountain areas and build-up areas due to increasing expectations for development. Development pressure is judged to be high in these areas because there are many mountains available for land-use conversion from a topographic perspective, and development projects are currently actively underway.Table5

    4.Classification of Forest Watersheds and the Consideration of Characteristics of Types

    Forest watersheds in Gyeonggi-do are classified into three clusters by using the conservation value indices, and three clusters by using the development pressure indices. Based on the clusters from the perspective of conservation value and development pressure, the matrix method was used to classify forest watersheds in the study site and it can be seen in Table 6. The current status of conservati on-development by type in the forest watersheds of Gyeonggi-do is shown in Table 7 and Figure 4.

    C-I & D-I types are places with high conservation value from the perspective of topography and vegetation, and their development ease factor is also high. Because not many places have all the characteristics that conflict with each other, there are few areas included among these types. As the results of confirmation on the current status of forest watersheds, there were many large resorts located in mountain areas that made use of outstanding landscape and vegetation. The conservation value of these types is high, but there is a high development possibility in these areas in order to utilize excellent forest resources (eg. large resorts) due to the high ratio of semi-conservation and private forests. Accordingly, it is necessary to devise a systematic measure that can encourage development projects to adopt eco-friendly business practices.

    C-I & D-II types are places with high conservation value from the perspective of topography and vegetation. Although the degree of development activity is low, the gap in land values is substantial. Well developed forests located in Pocheon, Gapyeong and Yangpyeong, and areas in the northeastern part of Gyeonggi-do, belong to these types. Implementing a large-scale development project is difficult in these areas due to the high conservation value and low development ease. However, steady supervision is required because small-scale development is expected for various purposes such as rural housing developments, leisure, recreation and land price increase and, in particular, illegal development in conservation areas.

    C-I & D-III types are places with high conservation value from the perspective of topography and vegetation, but development ease and the degree of development activity are also very high. The conflict between conservation value and development pressure is very intense in these areas but there aren't that many of them. As the results of confirming the current status of forest watersheds, most of the gradual slopes have undergone or are undergoing large-scale development projects, and the ratio of private and semi-conservation forests is high. A special caution is required when permitting land-use conversion because there aren't that many regulation means although the conservation value is high.

    C-II & D-I types are places with low conservation value from the perspective of topography and vegetation, and the degree of development activity is low. As the results of confirming the current status, areas in Suwon, Pyeongtaek and Goyang with a lot of build-up areas or farmland belong to these types, and the ratio of mountain areas is very low and most of them are semi-conservation forests. Most of the mountains in these watersheds are used to conserve water for the part of the fragmented forests in build-up areas or large-scale farmland. Because the coverage of mountains in these areas is very low, it is necessary to identify public value and reflect it in the mountain management.

    C-II & D-II types are places with low conservation value from the perspective of topography and vegetation. Their development ease and degree of development activity are low but their financial benefit factor is high. These areas in Gwangju, Yongin, Pyeongtaek, Anseong, Icheon, Yeoju, Paju and Yangju are under great pressure for the development of mountains due to land prices. Most of the forest watersheds of these types are located in the farmland and mountains, and development pressure is not so high at present, but the average land prices of land and farmland increased due to the development of neighboring areas. The development pressure is low at present, but there is a high development possibility in these areas due to the high ratio of semi-conservation and private forests. Accordingly, it is necessary to devise a systematic measure that can encourage development projects to adopt eco-friendly business practices. C-II &D-III types are places with low conservation value from the perspective of topography and vegetation, but development ease and the degree of development activity are high. These types are located in Yongin, Bucheon and Goyang. Most of the forest watersheds are located in highly developed build-up areas, and the mountains are left in a fragmented form. Because regulations are relatively weak compared to the intense development pressure, continuous unplanned development is expected in these areas. Accordingly, theses types require mountain management based on strong regulations to maintain the quality of the natural environment.

    C-III & D-I types are places with low conservation value from a topographic perspective, but high from the vegetation perspective and, in particular, their public value is high. Development ease is high but the degree of development activity is not so high. Forest watersheds that belong to theses types are located in Hwaseong, Yongin, Pyeongtaek and Goyang, and most of the area is covered with build-up areas. Also, these areas have high public value as some fragmented forests located within them improve the quality of life of residents. The degree of development ease of these types are high due to areas that are available for land-use conversion, but the degree of development activity is low because some have already undergone development or are regulated for the public purpose. The mountains in the relevant watersheds should be managed with consideration for public value, for they are important habitats and promote the quality of people's lives.

    C-III & D-II types are places with a low conservation value from the topographic perspective but high from the vegetation perspective. Also, development ease and the degree of development activity are low, but development pressure is high due to high financial benefits. Most of the area is covered with hills. The degree of development ease is low compared to low conservative value from the topographic perspective, because the value of vegetation and the function of public benefit is high. Although the degree of development activity is low at present, development pressure due to financial benefits will increase as the regulations weaken. Therefore, the management of the mountains that belong to these types needs to consider the possibility of unplanned development.

    C-III & D-III types are places with outstanding vegetation and low conservation value from the topographic perspective. Also, the degree of development ease and activity is high. Various development has been steadily undertaken in these areas in the past as there are many places available for development. However, the mountains in these areas are managed through public regulations because of the high population density and the significantly high public value. Detailed mountain management criteria is necessary, for there is an intense conflict between development pressure for build-up area expansion and conservation value.

    5.Comprehensive Discussion

    In the master plan of forest land management, management by forest watersheds with consideration for regional characteristics is proposed in order to overcome the problems of uniform mountain management. In this study, to manage forest watersheds with consideration of their characteristics, factor analysis and cluster analysis based on the mountainous indices were conducted and nine types of forest watersheds were deduced.

    Topographic factor, vegetation factor and public factor were deduced from the conservation value perspective, and development ease factor, financial benefit factor and development activity factor were deduced from development pressure value. They are judged to be useful in future relevant studies as they were deduced through a statistical analysis on various indices that enable one to identify the current status of forest watersheds. The forest watersheds, which were cluster-analyzed based on the foregoing factors, were classified into nine types. It was confirmed that the characteristics of watersheds differed according to their types based on the inquiry into the current forest watershed status. Also, it was judged that it is possible to set a mountain management direction suitable for each type.

    The implications and limits of the study results are as follows: 1) it was possible to confirm the forest watershed characteristics based on mountainous indices; 2) new factors can be deduced and used according to the interest of researchers based on mountainous indices and; 3) it was possible to classify forest watersheds based on the characteristics of conservation and development. These results can be used as preliminary data for studies on various analytic methods for mountain management. However, in case the ratio of mountains in a mountain watershed is too low, the mountainous indices may not be able to represent the mountain watershed's characteristics and mountain watersheds with different characteristics may be classified as the same type. Also, some forest watersheds of the same type were classified as different types because of their difference in shape, size and the location of the mountains. This was judged to be due to the lack of consideration for the characteristics of land-use and landscape ecology in forest watersheds. Accordingly, it was judged that further study on the methodology, which considers a land cover map and the landscape indices of landscape ecology along with the mountainous indices, is necessary.

    Figure

    KJEE-29-236_F1.gif

    The location of study sites

    KJEE-29-236_F2.gif

    Cluster analysis results from the view of conservation value indicator

    KJEE-29-236_F3.gif

    Cluster analysis results from the view of development pressure indicator

    KJEE-29-236_F4.gif

    Results of classifying the mountain watershed by using conservation value and development pressure

    Table

    Conservation value indicators for factor analysis

    Development pressure indicators for factor analysis

    Factor analysis result of conservation value indicators

    Factor analysis result of development pressure indicators

    Cluster analysis result of forest watersheds by using factor analysis results

    Matrix techniques to classify the mountain watershed by using the conservation value and development pressures

    Results of classifying the mountain watershed by using the conservation value and development pressure

    Reference

    1. Gyeonggi-do (2014) Regional Planning of Forest Land Management(2014-2017) , pp.-187
    2. Gwon SD (2015) The Analysis on Policy Trends for Korean and Overseas Forest Land Management, The Korea Forest Research Institute, pp.-25
    3. Korea Forest Service (2013) Master Plan of Forest Land Management In Korea (2013-2017), pp.-93
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