확률밀도함수를 이용한 목재수확조절법 연구

박정묵 ( Jung-mook Park ),이정수 ( Jung-soo Lee ),이호상 ( Ho-sang Lee ),박진우 ( Jin-woo Park ) 한국산림과학회(구 한국임학회) 2020 한국산림과학회지 Vol.109 No.4

본 연구는 확률밀도함수를 이용한 목재수확예측기법으로 면적가중치법(AW), 면적비율가중치법(ARW), 표본면적 변화율가중치법(SCRW)를 적용하여 전국 국유림의 산림경영계획 목표량 설정을 위한 벌채계획량을 추정하였다. 벌채계획량 추정을 위한 산림면적은 산림기본통계의 2010년, 2015년의 영급별 국유림면적을 이용하였으며, 5년간의 산림면적변화량을 벌채면적으로 가정하여 산출하였다. AW, ARW, SCRW를 이용한 벌기령의 평균은 각각 5.41, 5.56, 5.37로 Ⅴ~Ⅵ영급수준으로 산출되었다. 벌채면적은 각각 594,462 ha, 586,704 ha, 580,852 ha로 SCRW가 실제 면적변화량과 가장 유사하였으며, Chi-square 검정도 SCRW이 가장 안정적으로 분석되었다. 산림경영계획의 목재수확예측을 위한 방법으로 SCRW가 AW와 ARW보다 적합한 것으로 판단된다. This study estimated planned felling volumes to set targets for management planning of nationwide country-owned forests. Estimates were made using timber harvest prediction methods that use probability density functions, including area weighting (AW), area ratio weighting (ARW), and sample area change ratio weighting (SCRW). Country-owned forest areas in 2010 and 2015 were used to estimate planned felling volumes, as shown in basic forest statistics, and calculations were made assuming that the felling areas were the changes in the forest area over the 5-year period. For the age classes of Ⅴ-Ⅵ, the average felling ages for AW, ARW, and SCRW were 5.41, 5.56, and 5.37, respectively, and the felling areas were 594,462, 586,704, and 580,852 ha, respectively, with ARW reaching closest to the actual changes. The actual changes in the areas and chi-squared test results were most stable with the SCRW method. This study showed that SCRW was more adequate than AW and ARW as a method to predict timber harvests for forest management planning.

수치임상도 작업매뉴얼의 개선방안에 관한 연구

박정묵 ( Jeong-mook Park ),도미령 ( Mi-ryung Do ),심우담 ( Woo-dam Sim ),이정수 ( Jung-soo Lee ) 한국지리정보학회 2019 한국지리정보학회지 Vol.22 No.1

The objectives of this study were to examine the production processes and methods of “Forest Type Map Actualization Production (Database (DB) Construction Work Manual)”(Work Manual) identify issues associated with the production processes and methods, and suggest solutions for them by applying evaluation items to a 1:5k digital forest type map. The evaluation items applied to a forest type map were divided into zoning and attributes, and the issues associated with the production processes and methods of Work Manual were derived through analyzing the characteristics of the stand structure and fragmentation by administrative districts. Korea is divided into five divisions, where one is set as the area changed naturally and the other four areas set as the area changed artificially. The area changed naturally has been updated every five years, and those changed artificially have been updated annually. The fragmentation of South Korea was analyzed in order to examine the consistency of the DB established for each region. The results showed that, in South Korea, the number of patches increased and the mean patch size decreased. As a result, the degree of fragmentation and the complexity of shapes increased. The degree of fragmentation and the complexity of shapes decreased in four regions out of 17 regions (metropolitan cities and provinces). The results indicated that there were spatial variations. The “Forest Classification” defines the minimum area of a zoning as 0.1ha. This study examined the criteria for the minimum area of a zoning by estimating the divided object (polygon unit) in a forest type map. The results of this study revealed that approximately 26% of objects were smaller than the minimum area of a zoning. The results implied that it would be necessary to establish the definition and the regeneration interval of “Areas Changed Artificially and Areas Changed Naturally”, and improve the standard for the minimum area of a zoning. Among the attributes of Work Manual, “Species Change” item classifies terrain features into 52 types, and 43 types of them belong to stocking land. This study examined distribution ratios by extracting species information from the forest type map. It was found that each of 23 species, approximately 53% of species, occupied less than 0.1% of Forested land. The top three species were pine and other species. Although undergrowth on unstocked forest land are classified in the terrain feature system, their definition and classification criteria are not established in the “Forest Classification” item. Therefore, it will be needed to reestablish the terrain feature system and set the definitions of undergrowth.

시계열 고해상도 항공영상을 이용한 소나무재선충병 감염목 탐지 - 강원대학교 학술림 일원을 대상으로 -

박정묵 ( Jeong-mook Park ),최인규 ( In-gyu Choi ),이정수 ( Jung-soo Lee ) 한국지리정보학회 2019 한국지리정보학회지 Vol.22 No.2

The objectives of this study were to extract “Field Survey Based Infection Tree of Pine Wilt Disease(FSB_ITPWD)” and “Object Classification Based Infection Tree of Pine Wilt Disease(OCB_ITPWD)” from the Research Forest at Kangwon National University, and evaluate the spatial distribution characteristics and occurrence intensity of wood infested by pine wood nematode. It was found that the OCB optimum weights (OCB) were 11 for Scale, 0.1 for Shape, 0.9 for Color, 0.9 for Compactness, and 0.1 for Smoothness. The overall classification accuracy was approximately 94%, and the Kappa coefficient was 0.85, which was very high. OCB_ITPWD area is approximately 2.4ha, which is approximately 0.05% of the total area. When the stand structure, distribution characteristics, and topographic and geographic factors of OCB_ITPWD and those of FSB_ITPWD were compared, age class IV was the most abundant age class in FSB_ITPWD (approximately 55%) and OCB_ITPWD (approximately 44%) - the latter was 11% lower than the former. The diameter at breast heigh (DBH at 1.2m from the ground) results showed that (below 14㎝) and (below 28㎝) DBH trees were the majority (approximately 93%) in OCB_ITPWD, while medium and (more then 30cm) DBH trees were the majority (approximately 87%) in FSB_ITPWD, indicating different DBH distribution. On the other hand, the elevation distribution rate of OCB_ITPWD was mostly between 401 and 500m (approximately 30%), while that of FSB_ITPWD was mostly between 301 and 400m (approximately 45%). Additionally, the accessibility from the forest road was the highest at “100m or less” for both OCB_ITPWD (24%) and FSB_ITPWD (31%), indicating that more trees were infected when a stand was closer to a forest road with higher accessibility. OCB_ITPWD hotspots were 31 and 32 compartments, and it was highly distributed in areas with a higher age class and a higher DBH class.

딥러닝 기반 LUKUCF분야 국가수준 토지이용변화 매트릭스 구축 연구

박정묵(Jeong-Mook Park),심우담(Woo-Dam Shim),이정수(Jung-Soo Lee) 대한공간정보학회 2018 한국공간정보학회 학술대회 Vol.2018 No.11

공간통계기법을 이용한 생태계 관리지역의 산림축적 추정

서환석 ( Hwan Seok Seo ),박정묵 ( Jeong Mook Park ),김은숙 ( Eun Sook Kim ),이정수 ( Jung Soo Lee ) 한국지리정보학회 2015 한국지리정보학회지 Vol.18 No.2

This study aims to estimate the forest volumes of the upper region of Nam-Han River in ecosystem zoning by forest types and age classes, and to suggest the optimal estimation method through the comparison of the standard errors according to the spatial unit. In the estimation of forest volumes, we used both of direct estimation, which uses sample plots of the target area only, and synthetic estimation, which includes sample plots of the expanded areas as well as those of the target area. As for the spatial expansion, we applied four standards for synthetic estimator: Mountainous zone, Neighbor ecosystem region, Gangwon province, and Buffer zone. The results show that average forest volume per ha, calculated by direct estimation, was 143.5㎥/ha, while that by synthetic estimation with each standard, was estimated at 146.9㎥/ha by Gangwon province, 144.8㎥/ha by Buffer zone, 139.8㎥/ha by Neighbor ecosystem region, and 138.6㎥/ha by Mountainous zone, respectively. The standard errors of direct estimation was 1.79㎥/ha, while those of synthetic estimation showed not a great difference among the errors. Meanwhile, considering the standard errors by forest type, the lowest was ±2.3㎥/ha of broad-leaved forest, followed by ±3.3㎥/ha of mixed forest, and ±4.8㎥/h of coniferous forest.

원격탐사자료 기반 PDM기법을 활용한 산림특성분석

서환석 ( Hwan Seok Seo ),박정묵 ( Jeong Mook Park ),이정수 ( Jung Soo Lee ) 한국임학회 2014 산림과학 공동학술대회 논문집 Vol.2014 No.-

본 연구는 강원도 고성군의 DMZ지역을 대상으로 현장조사 자료를 분석하고, 현장조사자료와 영상지수간의 상관관계를 분석하였다. 지수영상은 Landsat TM의 6개 밴드를 이용하여 Pattern Decomposition Method(PDM)를 통해 3개의 지수영상(토양, 식생, 수계)을 추출하였다. 표준지의 현장조사정보로 상관분석을 실시한 결과, 직경과 수고와의 상관관계가 r=0.91로 가장 높았으며, 수고와 ha당 재적(r=0.64), 직경과 ha당 재적(r=0.59) 순이었다. 직경과 지수영상과의 상관관계는, 토양지수가 가장 높은 상관관계(r=0.94)였으며, 수고와 지수영상은 식생지수가 r=.0.94로 높은 음의 상관관계를 보였다. ha 당 재적과 지수영상과의 상관관계는 토양이 r=.0.92로 가장 높았고, 수계와 식생이 각각 r=0.78, r=-0.61 순이었다. Field investigation was conducted to measure tree height, diameter at breast height(dbh) and tree volume in forest areas of the demilitarized zone (DMZ) of Gosung-gun, Gangwon-do, then we examined the correlation between field data and index images. Three index images on soil, vegetation and stream network were extracted by Pattern Decomposition Method (PDM) using 6 bands of Landsat TM. Field data showed that significantly positive correlations were observed between dbh and tree height (r=0.91), between tree height and volume per ha (r=0.64), and between dbh and tree volume per ha (r=0.59). When examining correlation between dbh and index images, soil index showed a positive correlation with dbh (r=0.94) while vegetation index showed a negative correlation with tree height (r=-0.94). In case of considering the correlation between tree volume per ha and index images, both soil and vegetation index showed negative correlations with tree volume per ha (r=-0.92 and r=-0.61, respectively) while stream network showed a positive correlation with tree volume per ha (r=0.78).

원격탐사와 공간통계 기법을 이용한 토지피복 분류 및 패턴 분석 -강원도 DMZ일원을 대상으로-

나현섭 ( Hyun Sup Na ),박정묵 ( Jeong Mook Park ),이정수 ( Jung Soo Lee ) 한국지리정보학회 2015 한국지리정보학회지 Vol.18 No.4

This study established a land-cover classification method on objects using satellite images, and figured out distributional patterns of land cover according to categories through spatial statistics techniques. Object-based classification generated each land cover classification map by spectral information, texture information, and the combination of the two. Through assessment of accuracy, we selected optimum land cover classification map. Also, to figure out spatial distribution pattern of land cover according to categories, we analyzed hot spots and quantified them. Optimal weight for an object-based classification has been selected as the Scale 52, Shape 0.4, Color 0.6, Compactness 0.5, Smoothness 0.5. In case of using the combination of spectral information and texture information, the land cover classification map showed the best overall classification accuracy. Particularly in case of dry fields, protected cultivation, and bare lands, the accuracy has increased about 12 percent more than when we used only spectral information. Forest, paddy fields, transportation facilities, grasslands, dry fields, bare lands, buildings, water and protected cultivation in order of the higher area ratio of DMZ according to categories. Particularly, dry field sand transportation facilities in Yanggu occurred mainly in north areas of the civilian control line. dry fields in Cheorwon, forest and transportation facilities in Inje fulfilled actively in south areas of the civilian control line. In case of distributional patterns according to categories, hot spot of paddy fields, dry fields and protected cultivation, which is related to agriculture, was distributed intensively in plains of Yanggu and in basin areas of Cheorwon. Hot spot areas of bare lands, waters, buildings and roads have similar distribution patterns with hot spot areas related to agriculture, while hot spot areas of bare lands, water, buildings and roads have different distributional patterns with hot spot areas of forest and grasslands.

영상판독에 의한 산림훼손지의 공간적 특성분석 -화천군과 철원군 DMZ일원을 대상으로-

나현섭 ( Hyun-sup Na ),박정묵 ( Jeong-mook Park ),최재용 ( Jae-yong Choi ),이정수 ( Jung-soo Lee ) 한국사진지리학회 2015 한국사진지리학회지 Vol.25 No.3

This study was conducted to categorize the DMZ area into six types of damaged forest (bare ground, landslide ground, infertile land, fill-up ground, cutting ground, and other land) and analyze topographical characteristics according to the type of damaged forest. The land area of damaged forest in Hwacheon-gun and Cheorwon-gun is 126 ha and 102 ha, respectively, and average size of damaged forest is 2.4 times larger in Hwacheon-gun (0.12 ha) than in Cheorwon-gun. The area according to the type of damaged forest was listed in the sequence of other land, bare ground, and infertile land in Hwacheon-gun, but listed in the sequence of bare ground, other land, and infertile land in Cheorwon-gun. Also, more than 80% of the damaged forest occurred within 200 m from roads regardless of the region. 40 % of the damaged forest was occurred within 1 km from buildings. As a result of fragmentization by landscape index, landslide ground, fill-up, and cutting ground were a simple type with small area, other land and bare ground were a complex type with large area, and infertile land was a complex type with area. The type of fragmentization was similarly occurred regardless of the region.

토지이용변화 매트릭스 구축을 위한 국가공간주제도 활용방안에 관한 연구

심우담 ( Woo-dam Sim ),박정묵 ( Jeong-mook Park ),이정수 ( Jung-soo Lee ) 한국산림경제학회 2017 산림경제연구 Vol.24 No.2

본 연구는 주요 선진국의 국가 인벤토리 보고서 (National Inventory Report; NIR)를 통하여 우리나라의 토지이용 범주별 정의 및 토지이용 변화를 파악하기 위한 매 트릭스 구축 방법에 대하여 비교·분석하였다. IPCC 가이드라인에 의하면, LULUCF 분야의 온실가스 흡수 및 배출량 통계는 산림지, 농경지, 초지, 습지, 정주지, 기타토지의 6가지 범주로 구분하고 있으며, 각 국가 토지 상황에 맞게 토지이용 범주별 세부항목을 다르게 정의하고 있다. 일본의 경우, 산림지에 대해서 Approach(App.)3 수준의 토지이용 변화 매트릭스를 작성하고 있으며, 산림지를 제외한 5가지 범주는 App.1~2 수준으로 보고하고 있다. 또한, 독일, 핀란드, 뉴질랜드 등 주요선진국은 6가지 범주 모두 App.3 수준으로 보고하고 있으며, 범주에 따라서 App.1 - 3까지 적용방식이 다양하였다. 우리나라 NIR의 경우, LULUCF 분야 범주별 정의는 시계열 활동자료가 미비하여 6개의 토지이용 범주 중 정주지 및 기타토지는 산정하지 않고 있으며, 현재 정의하고 있는 산림지, 농경지, 초지, 습지는 세부항목에 대한 정의가 명확하지 않아 주요 선진국가의 사례를 바탕으로 IPCC 기준에 부합하는 정의에 대해 검토하였다. 토지이용 변화 매트릭스 구축의 경우, 주요 선진 국가에서는 Sampling 또는 Wall-to-wall 기법을 이용한 토지이용 변화 매트릭스를 구축하고 있지만, App.1 수준인 우리나라는 국제적인 LULUCF분야 통계로 인정받기 위해서는 국가 통계자료와 공간정보를 활용한 App.2- 3 수준의 토지이용변화 매트릭스를 구축이 필요할 것으로 사료된다. The objectives of this study were to define the land use categories of Korea and present the way to establish the land use change matrix by using the national inventory report(NIR) of major developed countries, according to the IPCC Guidelines, the GHG absorption and emission statistics of the LULUCF sector are classified land use into 6 categories: forest, agricultural, grassland, wetland, jungju, and other land. Major developed countries such as Japan, Germany, Finland, and New Zealand present the definitions of land use categories satisfying the standards of IPCC through the consultation among national agencies. Moreover, the details of land use category are defined differently according to each country's land situation. South Korea does not estimate the statistics of settlements and other land categories because there are not enough active data. Moreover, South Korea needs to add more sub-categories under forest land, cropland, grassland, and wetland, which are currently defined. In the aspect of establishing the land use change matrix, major developed countries have established the approach(App.)3 level matrix based on sampling and wall-to-wall techniques. However, South Korea is at the App. 1 level, based on the national statistics. Therefore, it is required to construct a matrix by using image data such as national thematic maps and forest aerial photographs.

Landsat TM 위성영상을 활용한 토지피복변화탐지 및 파편화 분석 -강원도 고성군의 DMZ지역 일원을 대상으로-

최병구 ( Byoung Koo Choi ),박정묵 ( Jung Mook Park ),이정수 ( Jung Soo Lee ) 한국사진지리학회 2013 한국사진지리학회지 Vol.23 No.1

The objectives of this study are to quantify the changes of land-cover and fragmentation pattern during 9 years from 2000 to 2009, using Landsat TM images in eastern DMZ of Gosung-gun, Gangwon province. Landcover classification map was derived from 3 types(Maximum likelihood(ML), minimum distance(MD), support vector machine(SVM)) of supervised classification algorithm. ML method showed significantly higher accuracy than the MD and SVM method, and overall accuracy(OA) and k-hat of ML method was 95% and 0.94. Occurrence of deforestation was higher in the northern part of the civilian control line(CCL) than that of southern part. Semi-forest area changed to forest and bare land. forest area were increased significantly during the 9 years period. the size of forest patches became smaller and complexity and irregularity of forest patches decreased during period.