• Korean Journal of Plant Resources
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• v.36 no.1
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• pp.32-61
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• 2023

To investigate the distribution of vascular plants growing at Wetland in Daegu·Gyeongbook, we surveyed from June 2020 to October in 2021. The flora of wetland was classified as a total of 459 taxa comprising of 104 families, 286 genus, 406 species, 12 subspecies, 34 varieties, 6 forma, 1 hybrid. Among them, the rare plants species 5 taxa, endemic plants 11 taxa, floristic regional indicator plants 57 taxa, naturalized plants 27 taxa and wetland plants 74 taxa were recorded. The percentage of urbanization index was 8.44%, the naturalized ratio was 5.88%, respectively.

• Journal of Wetlands Research
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• v.24 no.4
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• pp.224-255
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• 2022

This study was carried out to examine the changes in vascular flora in the first and second surveys targeting 32 outstanding forest wetlands in Jeonnam area including Gwangju metropolitan city, and based on this, establish a future monitoring system and effectively manage the excellent forest wetlands. The survey investigated the area seasonally every 4-5 years from 2015 to 2021. The change of flora of 32 excellent forest wetlands in Jeollanam-do increased from 103 families, 311 genera, 496 species, 16 subspecies, 38 varieties, 6 varieties, 556 taxa, to 111 families, 362 genera, 599 species, 16 subspecies, 51 varieties, 8 varieties, 674 taxa. Remarkable plants such as Red list and plants endemic to the Korean Peninsula increased also. However, Nepeta cataria and the like are exterminated locally, so an in situ and ex situ conservation strategy must be established. In the case of plants categorized according to wetland preference, the distribution ratio of such wetland plants slightly decreased and the distribution ratio of such terrestrial plants lightly increased for absolute wetland plants. It is necessary to prepare countermeasures for the terrestrialization of forest wetlands and to develop research techniques that can distinguish boundaries. In addition, the forest wetland should be systematically managed and supervised by designating it as a Forest Genetic Resources Reserve that can effectively conserve it.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.04a
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• pp.46-46
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• 2018

본 연구는 봉화군 청옥산 산림유전자원보호구역에 분포하는 관속식물을 파악하고자 수행하였다. 청옥산 보호구역은 산림청에서 '희귀식물자생지' 유형으로 지정하여 관리하고 있으며, 면적은 약 2,051ha에 달하며 주로 신갈나무군락과 소나무군락이 우점하고있다. 현지조사는 2017년 3월부터 10월까지 계절별로 수행하였다. 조사결과, 보호구역내 관속식물은 86과 258속 390종 4아종 54변종 6품종으로 총 454분류군의 분포가 확인되었다. 이 중 한국특산식물은 가야물봉선, 처녀치마, 할미밀망, 키버들 등 11분류군이며, 산림청 지정 희귀식물은 취약종(VU)에 주목, 백작약, 꼬리진달래 3분류군, 약관심종(LC)에 등칡, 도깨비부채, 정향나무, 말나리, 나도개감채 등 14분류군이다. 식물구계학적 특정식물로는 IV등급인 회리바람꽃, 가지괭이눈, 산겨릅나무, 귀박쥐나물 등 10분류군, III등급인 애기감둥사초, 중나리, 토현삼, 선갈퀴, 금강제비꽃, 노랑갈퀴, 분비나무 등 23분류군, II등급 32분류군, I등급 30분류군이 확인되었다. 외래식물은 오리새, 털별꽃아재비, 왕포아풀, 주걱개망초, 지느러미엉겅퀴, 족제비싸리 등 18분류군이 임도 주변에서 확인되었다. 조사된 관속식물을 용도별로 구분하면 식용식물 181분류군, 섬유용식물 6분류군, 약용식물 143분류군, 관상용식물 52분류군, 사료용식물 172분류군, 염료용식물 9분류군, 목재용식물 22분류군으로 분석되었다.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1407-1422
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• 2022

This study was conducted to classify tree species and assess the classification accuracy, using SE-Inception, a classification-based deep learning model. The input images of the dataset used Worldview-3 and GeoEye-1 images, and the size of the input images was divided into 10 × 10 m, 30 × 30 m, and 50 × 50 m to compare and evaluate the accuracy of classification of tree species. The label data was divided into five tree species (Pinus densiflora, Pinus koraiensis, Larix kaempferi, Abies holophylla Maxim. and Quercus) by visually interpreting the divided image, and then labeling was performed manually. The dataset constructed a total of 2,429 images, of which about 85% was used as learning data and about 15% as verification data. As a result of classification using the deep learning model, the overall accuracy of up to 78% was achieved when using the Worldview-3 image, the accuracy of up to 84% when using the GeoEye-1 image, and the classification accuracy was high performance. In particular, Quercus showed high accuracy of more than 85% in F₁ regardless of the input image size, but trees with similar spectral characteristics such as Pinus densiflora and Pinus koraiensis had many errors. Therefore, there may be limitations in extracting feature amount only with spectral information of satellite images, and classification accuracy may be improved by using images containing various pattern information such as vegetation index and Gray-Level Co-occurrence Matrix (GLCM).

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.04a
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• pp.49-49
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• 2018

본 연구는 함백산 산림유전자원보호구역의 생물다양성 증진과 체계적이고 객관적인 보전 및 관리를 위한 기초데이타 수립을 위하여 식물상과 정밀식생조사를 수행하였다. 함백산 산림유존자원보호구역에 분포하는 식물상은 83과 222속 321종 2아종 36변종 등 359분류군이 확인되었으며, 희귀 및 멸종위기식물은 산마늘, 등칡 등 총 10과 14분류군이 확인되었다. 식물구계학적 3등급 종은 15과 20분류군, 4등 급종은 8과 11분류군이 확인되었다. 산림청 특별산림보호 대상종은 3과 3분류군, 한국특산식물은 7과 10분류군이 확인되었으며 귀화식물은 9과 16분류군이 출현하였다. 함백산 산림유전자원보호구역 26개 조사구역에 대하여 정밀식생조사를 수행한 결과. 식생유형은 산지관목림, 일본잎갈나무식재림, 가래나무군락, 거제수나무군락, 거제수나무-신갈나무군락, 거제수나무-층층나무군락, 거제수나무-피나무군락, 소나무군락, 신갈나무군락, 피나무군락, 피나무-거제수나무군락 등 총 11개의 유형으로 확인되었다. 또한 식생조사와 드론을 활용하여 현존식생도를 작성하였으며, 그 결과 함백산 유전자원보호구역은 총 470.9ha로, 그 중 신갈나무군락이 총 390.8ha로 가장 넓게 분포하고 있으며, 거제수나무-신갈나무군락이 34.3ha, 산지관목림 18.5ha 순으로 대부분 10ha 이하로 나타났다.

• Journal of Korean Society of Forest Science
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• v.100 no.3
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• pp.494-503
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• 2011

This study was aimed at applying the IUCN category system to the Baekdudaegan Protected Area. A classification key was developed to apply the system to the overlapped designated protected areas inside of Baekdudaegan Protected Area. Korea national parks and forests managers' and experts' opinions were collected and they all agreed to the use of multiple classification in Baekdudaegan Protected Area. For example, the type of natural forests among the Forest Genetic Resources Reserves was classified to be IUCN Category Ia while other types of Forest Genetic Resources Reserve was classified to be Category IV. And the Protected Forest Landscape was classified to be Category V while the other types of protected forests were classified to be Category VI. The study suggests the need of classification of forest protected areas including Baekdudaegan Protected Area using IUCN system accompanying with protected areas management effectiveness evaluation.

• Korean Journal of Environment and Ecology
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• v.38 no.1
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• pp.22-47
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• 2024

This study aims to reveal the distribution of native plants, rare plants, and specialty plants and provides basic data for efficient ecosystem management through a survey of the flora in Mt. Chijae (Gamagol) and its adjacent areas in Damyang-gun, Jeonnam-do, while also identifying useful plants in the eco-city Damyang-gun for distinctive garden plants. A total of 21 field surveys were conducted from March 2022 to June 2023 to collect and identify 492 taxa consisting of 101 families, 304 genera, 444 species, 10 subspecies, 35 varieties, and 3 formas. The analysis of the prepared sample list showed 14 taxa designated as specialty plants, 9 taxa designated as rare plants by the Korea Forest Service, 7 taxa designated as the national red (i.e., endangered) plants by the Ministry of Environment, and 68 taxa with phylogenetic specific species, of which 45 taxa for Grade I, 5 taxa for Grade II, 16 taxa for Grade III, and 2 taxa for Grade IV were confirmed. The list included 155 taxa of biological resources subject to export approval by the Ministry of Environment and 38 taxa of alien plants of which 7.7 percent were naturalized, and the urbanization index was 6.1 percent. Four taxa were ecosystem-disturbing invasive alien plants designated by the Ministry of Environment introduced artificially or naturally from abroad. This study is expected to contribute to creating unique and attractive landscapes in Damyang if the specific plants found in Mt. Chijae are grown and planted in city gardens.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.359-364
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• 2006

최근 GIS를 비롯한 공간정보기술의 눈부신 발전으로 국토전반에 대한 정보화와 과학적인 관리기법이 확산되고 있다. 이에 효율적인 산림관리를 위하여 위성영상과 지리정보시스템을 이용한 산림정보가 구축되고 있으나, 산림지역이라는 지리특성상 현장 출입이 제한적이고 위험하여 정보수집에 어려움이 있다. 본 연구에서는 효율적인 산림정보구축을 위하여 남제주군을 대상으로 고해상도 위성영상과 공간정보추출언어인 SML(Spatial Modeler Language)을 이용하여 다양한 모델별 산림지역의 임상정보를 추출, 임상분류를 위한 모델링 기법을 개발하였다. 또한 l/5,000도엽을 기준으로 표본점을 배치하고 임상, 하층식생, 입지 및 토양에 대한 현지조사를 수행하였으며, 추출자료와의 상관성 분석 및 검증을 통하여 공간정보 기술을 이용한 산림정보 구축의 기반을 마련하고자 하였다.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.477-487
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• 2010

In North Korea, forests were intensively degraded by forest land reclamation for food production and firewood collection since the mid-1970s. These degraded forests have to be certainly recovered for economic support, environmental protection and disaster prevention. In order to provide detailed land cover information of forest recovery project (A/R CDM), this study was focused to develop an improved classification method for degraded forest using 2.5m SPOT-5 pan-sharpened image. The degraded forest of North Korea shows various different types of texture. This study used GLCM texture bands of segmented image with spectral bands during forest cover classification. When scale factor 40/shape factor 0.3 was used as a parameter set to generate segment image, segment image was generated on suitable segment scale that could classify types of degraded forest. Forest land cover types were classified with an optimum band combination of Band1, Band2, band3, GLCM dissimilarity (band2), GLCM homogeneity (band2) and GLCM standard deviation (band3). Segment-based classification method using spectral bands and texture bands reached an 80.4% overall accuracy, but the method using only spectral bands yielded an 70.3% overall accuracy. As using spectral and texture bands, a classification accuracy of stocked forest and unstocked forest showed an increase of 23~25%. In this research, SPOT-5 pan-sharpened high-resolution satellite image could provide a very useful information for classifying the forest cover of North Korea in which field data collection was not available for ground truth data and verification directly. And segment-based classification method using texture information improved classification accuracy of degraded forest.

• Korean Journal of Environment and Ecology
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• v.14 no.1
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• pp.57-66
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• 2000

본 연구는 울릉도의 성인봉과 태하령지역의 산림식생을 분류하기 위해 199년 7-8월에 36개소를 선정하여 식생조사를 실시하였으며 식물사회학적 방법과 TWINSPAN에 의하여 군락을 분류하였다 울릉도 산림의 종조성표에 의한 군락 분류결과 너도밤나무-섬노루귀 군락군으로 판명되었다 이 군락군은 다시 솔송나무-섬잣나무 군락, 참나도히초미-졸방제비꽃군락으로 크게 나뉘어졌으며 참나도히초미-졸방제비꽃군락은 다시 전형하위군락. 섬조릿대하위군락 일색고사리하위군락으로구분되었다 TWINSPAN에 의한 분류결과는 솔송나무-섬작나무군락 너도밤나무-섬조릭대군락 너도밤나무-일색고사리군락, 너도밤나무-큰두루미꽃군락으로 구분되었다 식물사회학적 군락 분류결과와 TWINSPAN에 의한 군락분류결과는 4개 군락으로 구분되는 일치성을 보이고 있어 두 방법에 의한 군락 분류방법은 상호 보완될수 있다고 판단된다.