• 제목/요약/키워드: Forest Cover

검색결과 670건 처리시간 0.026초

The Impact of Community-Based Forest Management on Local People around the Forest: Case Study in Forest Management Unit Bogor, Indonesia

  • Fajar, Nugraha Cahya;Kim, Joon Soon
    • Journal of Forest and Environmental Science
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    • 제35권2호
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    • pp.102-114
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    • 2019
  • The issue of sustainable forest management (SFM) continues to emerge as part of the REDD+ mechanism mitigation efforts. Especially for some developing countries, such as Indonesia, forest management is required to provide benefits to the welfare of local communities in addition to forest conservation efforts. This study aims to identify the economic, social, and environmental impacts of community-based forest management (CBFM) implementation activities, which is one of the implementations of SFM at field level. The primary objectives were to find out the impacts of CBFM activities based on local people's perceptions and to identify what factors need to be considered to increase local people's satisfaction on CBFM activities. The data from 6 sub-villages was derived through surveys with local people involved in CBFM activities, interviews with a key informant, and supported by secondary data. The results of the study state that CBFM activities have increased the local people's income as well as their welfare, strengthening the local institution, and help to resolve conflicts in the study area. CBFM has also been successful in protecting forests by rehabilitating unproductive lands and increase forest cover area. By using binary logistic regression analysis, it found that income, business development opportunities, access to forests, conflict resolution, institutional strengthening, and forest rehabilitation variable significantly affected the local people's satisfaction of CBFM activities.

Comparisons of microhabitat use of Schlegel's Japanese gecko (Gekko japonicus) among three populations and four land cover types

  • Kim, Dae-In;Choi, Woo-Jin;Park, Il-Kook;Kim, Jong-Sun;Kim, Il-Hun;Park, Daesik
    • Journal of Ecology and Environment
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    • 제42권4호
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    • pp.198-204
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    • 2018
  • Background: The effective use of habitats is essential for the successful adaptation of a species to the local environment. Although habitats exhibit a hierarchical structure, including macro-, meso-, and microhabitats, the relationships among habitats of differing hierarchy have not been well studied. In this study, we studied the quantitative measures of microhabitat use of Gekko japonicus from three field populations in Japan: one at Tsushima Island, one at Nishi Park, Fukuoka, and one at Ohori Park, Fukuoka. We investigated whether land cover type, a higher hierarchical habitat component, was associated with quantitative microhabitat use, a lower hierarchical component, in these populations. Results: The substrate temperature where we located geckos (SubT) and the distance from the ground to the gecko (Height) were significantly different among the three populations. In particular, SubT on Tsushima Island was lower than it was in the other two populations. Irradiance at gecko location and Height were significantly different among the land cover types. In particular, Height in evergreen needleleaf forest was significantly lower than that in deciduous broadleaf forest. Furthermore, significant interactions between population and land cover type were observed for the SubT and Height variables. Conclusions: The quantitative measures of microhabitat use of G. japonicus varied with population and land cover type, which exhibited significant interaction effects on microhabitat use variables. These results suggest that higher hierarchical habitat components can affect the quantitative measures of lower hierarchical microhabitat use in nocturnal geckos.

딥러닝 기반의 영상분할을 이용한 토지피복분류 (Land Cover Classification Using Sematic Image Segmentation with Deep Learning)

  • 이성혁;김진수
    • 대한원격탐사학회지
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    • 제35권2호
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    • pp.279-288
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    • 2019
  • 본 연구에서는 항공정사영상을 이용하여 SegNet 기반의 의미분할을 수행하고, 토지피복분류에서의 그 성능을 평가하였다. 의미분할을 위한 분류 항목을 4가지(시가화건조지역, 농지, 산림, 수역)로 선정하였고, 항공정사영상과 세분류 토지피복도를 이용하여 총 2,000개의 데이터셋을 8:2 비율로 훈련(1,600개) 및 검증(400개)로 구분하여 구축하였다. 구축된 데이터셋은 훈련과 검증으로 나누어 학습하였고, 모델 학습 시 정확도에 영향을 미치는 하이퍼파라미터의 변화에 따른 검증 정확도를 평가하였다. SegNet 모델 검증 결과 반복횟수 100,000회, batch size 5에서 가장 높은 성능을 보였다. 이상과 같이 훈련된 SegNet 모델을 이용하여 테스트 데이터셋 200개에 대한 의미분할을 수행한 결과, 항목별 정확도는 농지(87.89%), 산림(87.18%), 수역(83.66%), 시가화건조지역(82.67%), 전체 분류정확도는 85.48%로 나타났다. 이 결과는 기존의 항공영상을 활용한 토지피복분류연구보다 향상된 정확도를 나타냈으며, 딥러닝 기반 의미분할 기법의 적용 가능성이 충분하다고 판단된다. 향후 다양한 채널의 자료와 지수의 활용과 함께 분류 정확도 향상에 크게 기여할 수 있을 것으로 기대된다.

Study of Urban Land Cover Changes Relative to Demographic and Residential Form Changes: A Case Study of Wonju City, Korea

  • Han, Gab-Soo;Kim, Mintai
    • Journal of Forest and Environmental Science
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    • 제31권4호
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    • pp.288-296
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    • 2015
  • In many very high density cities in Asia in which there is limited area to expand, growth is forced upward as well as outward. Densely packed detached houses and low-rise buildings are replaced by lower density high-rises, leaving open spaces between high-rise buildings. Through this process, areas that formerly did not have much green space gain valuable green spaces, and new ecological corridors and patches are created. In this study, the demographic and housing-type changes of Wonju City were delineated using land use maps, aerial images, census data, and other administrative data. Green area changes were calculated using land cover data derived from multi-year Landsat TM satellite imagery. The values were then compared against demographic and housing-type changes for each administrative unit. The overall results showed a decrease of forested area in the city and an increase of developed area. Urban sprawl was clearly visible in many of the suburban areas. However, as expected, we also detected areas in which greenness did not decrease when the population greatly increased. These areas were characterized by residential building complexes of ten or more stories. If an equal number of housing units had been built as detached houses, these areas would not have kept as much green space. Our research result showed that high-density and high-rise residential structures can offer an alternative means to protect or create urban green spaces in high-density urban environments.

개발에 따른 탄천유역의 파편화 및 이질성분석 (Analysis of Fragmentation and Heterogeneity of Tancheon Watershed by Land Development Projects)

  • 이동근;이현이;김은영
    • 한국환경복원기술학회지
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    • 제10권6호
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    • pp.120-129
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    • 2007
  • Rapid urbanization has transformed the spatial pattern of urban land use or cover. This paper concentrates that changed characteristics of landscape structure in the Tancheon Watershed, from 1995 to 2003 were investigated using land cover map. We used FRAGSTATS software to calculate landscape indices to characterize the landscape structure. We found that built up area has been increased rapidly during the study period, while cultivated area and forest area have been decreased rapidly in the same period. From 1995 to 2003, built up area was increased from 19.73% to 39.62% and cultivated area and forest area was decreased 17.60% to 5.97% and 58.31% to 49.41%. Number of patches, mean euclidean nearest-neighbor distance, contagion index, Shannon's diversity index increased considerably from 1995 to 2003, also suggesting the landscape in the study area became more fragmented and heterogeneous. but because of continuously fragmentation, landscape became homogeneity. The study demonstrates that landscape metrics can be a useful indicator in landscape monitoring and landscape assessment.

장기적 토지피복 분석을 통한 경안천 유역의 토지이용 특성 (Land Use Characteristics in the Kyungan Watershed by Analyzing Long-Term Land Cover Data)

  • 한미덕;김지찬;정욱진
    • 한국물환경학회지
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    • 제27권2호
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    • pp.159-166
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    • 2011
  • The use of land cover was sharply changed during 1975~2007 in the Kyungan watershed $(561.12 km^2)$. The changes occurred over an area of more than $227.65 km^2$ during the overall period at changing rates of 1.04% per year for water area, 1.79% per year for residential area, 2.99% per year for bare area, 3.03% per year for wetland area, 3.04% per year for grass area, 0.87% per year for forest and 2.32% per year for agriculture area. Water, residential, bare and wetland areas increased, while grass, forest and agriculture areas decreased during the last 32 years. BOD concentrations of representative sites for each sub-watershed continuously increased until the early 2000s as residential area increased with the highest discharged load, but decreased after the mid 2000s except upper Kyungan watershed. Such decline appears to be associated with the planning of Total Maximum Daily Load management for Gwangju city and expansion of waste water treatment plant. It is necessary to control land use/cover changes of the upper watershed and to prepare appropriate watershed management system for improvement in river environment including water quality, stream flow and bio-diversity.

임도시공 후 경과년수에 따른 비탈면 식생침입 및 식물상 분석 (Analysis of Flora and Vegetation in Forest Road Slopes Along to Constructions Age)

  • 추갑철;박재현;마호섭
    • 한국산림과학회지
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    • 제103권3호
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    • pp.408-421
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    • 2014
  • 이 연구는 경상남도 사천시 용현면 용치리 지역에 5년(2007, 2009, 2010, 2011, 2012)동안 시공한 임도에 대하여 임도시공 후 경과년수에 따라 비탈면에 침입하는 식생과 식물상을 분석하였다. 조사대상 임도의 절토비탈면과 성토비탈면의 평균경사는 모두 $42^{\circ}$에서 $^54{\circ}$의 범위를 나타내어 급경사지였다. 토성은 2012년 개설된 임도의 절토와 성토비탈면만 양토이고 나머지는 모두 사양토로 나타났다. 조사대상 임도의 성토비탈면의 평균피복도(약 66%)는 절토비탈면의 평균피복도(약 49%) 보다 높게 나타났다. 절토비탈면에서의 평균출현종은 46종으로 성토비탈면에서의 평균출현종(50종) 보다 낮은 것으로 나타났다. 종다양성은 모든 임도에서 절토비탈면보다 성토비탈면이 더 높은 것으로 나타났는데, 절토비탈면에서는 2011년 개설 임도에서 1.4015로 가장 높게 나타났고, 성토비탈면에서는 2012년도 개설 임도에서 1.5603으로 가장 높게 나타났다. 균재도(Evenness)는 절토와 성토비탈면에서 임도개설년수가 짧을수록 높았으며, 출현한 식물종은 균일한 것으로 분석되었다.

시계열(時系列) AVHRR 위성자료(衛星資料)를 이용한 한반도 식생분포(植生分布) 구분(區分) (Vegetation Cover Type Mapping Over The Korean Peninsula Using Multitemporal AVHRR Data)

  • 이규성
    • 한국산림과학회지
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    • 제83권4호
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    • pp.441-449
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    • 1994
  • 본 연구의 목적(目的)은 현재 한국에서 자료획득이 비교적 용이한 AVHRR 위성자료(衛星資料)를 이용하여, 한반도 전지역(全地域)을 대상으로 식물(植物)의 시기별(時期別) 변화유형(變化類型)을 분석하고, 이를 응용하여 주요식생(主要植生)의 분포를 구분하고자 한다. 1991년 1년동안 NOAA-11 위성에서 수신(受信)된 AVHRR 자료중 비교적 운량(雲量)이 적은 날을 택하여 총 27일분의 일별영상자료(日別映像資料)를 추출하였다. 일별영상자료는 먼저 광학적(光學的) 보정(補正)을 마친 후, 적색(赤色)파장대 및 근적외선(近赤外線)파장대에서의 반사특성(反射特性)을 조합한 식생지수(植生指數)(NDVI-Normalized Difference Vegetation Index)로 변환되었다. 구름으로 덮혀있는 지역의 식생지수는 식물이 존재하는 지역보다 상대적으로 낮은 값을 나타내므로, 구름제거를 위하여 4-5개의 일별식생지수자료(日別植生指數資料)를 중첩한 뒤 각 화소(畵素)지점의 식생지수중 최대치를 선택함으로써 구름의 영향이 최소화된 월별식생지수자료(月別植生指數資料)가 산출되었다. 월별식생지수자료는 식물 생장의 연중변화(年中變化)를 비교 분석하기에 용이하도록 비생장기간(非生長期間)까지 포함하여 2월, 3월, 5월, 8월, 9월, 그리고 11월까지 6개가 산출되었다. 식생별로 상이(相異)한 계절별 잎의 발달상태에 따라, 6개의 월별식생지수자료(月別植生指數資料)에 나타나는 식생지수의 변화특성을 이용하여 식생분류(植生分類)를 실시하였다. 사용된 자료의 광학적 해상력(解像力)을 고려하여 분류집단은 침엽수림, 활엽수림, 침활혼효림, 농지, 초지관목림, 그리고 도시지역으로 구분하였다. 컴퓨터분류방식은 식생지수(植生指數)의 변화유형이 비슷한 집단끼리 스스로 규합(糾合)되게 하는 무감독류집분류법(無監督類集分類法)(unsupervised clustering)을 채택하였다. 컴퓨터분류 결과를 기존의 산림자원조사자료(山林資源調査資料)와 비교한 결과 상당히 근접한 통계치를 보여주었고, 산림지역내(內)에서도 침엽수림, 활엽수림, 혼효림의 구분 또한 만족할만한 결과를 나타내고 있다. 넓은 지역을 대상으로 필요한 영상자료(映像資料)를 비교적 신속하고 용이하게 수신(受信)할 수 있고, 타(他) 위성자료에 비교하여 자료의 양이나 가격 측면에서 유리한 AVHRR자료는 한반도 규모에 상응하는 넓은 지역의 식생현황을 주기적으로 모니터링하기에 적합한 위성자료로 판단된다.

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MODIS NDVI 시계열 패턴 변화를 이용한 산림식생변화 모니터링 방법론 (Method of Monitoring Forest Vegetation Change based on Change of MODIS NDVI Time Series Pattern)

  • 정명희;이상훈;장은미;홍성욱
    • Spatial Information Research
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    • 제20권4호
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    • pp.47-55
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    • 2012
  • 정규식생지수(NDVI)는 식생자원을 모니터링할 수 있도록 설계된 식생지수(VI-Vegetation Index) 중 하나로 여러 응용 분야에서 가장 많이 사용되고 있는 지수이다. 산림 분야에서도 NDVI가 많이 활용되고 있는데 본 논문에서는 산림 변화 모니터링을 위해 MODIS NDVI를 활용하는 방법론이 연구되었다. 특정 시점을 기준으로 NDVI 값을 비교 및 분류하여 변화를 탐지하는 방법은 기계나 기상상태의 영향으로 자료의 정확성이 떨어질 수 있고 장기적인 변화를 탐지하는데도 어려움이 있다. 이러한 점을 고려하여 본 논문에서는 하모닉 모형을 이용하여 NDVI 시계열 자료를 통해 NDVI 패턴을 고려하는 방법론을 제시하였다. 먼저 하모닉 모형을 적용하여 미관측 자료나 자료의 오류를 보정한 NDVI 시계열 자료를 재구축하고 추정된 하모닉 요소의 모수를 기준으로 장기적 패턴을 통해 식생의 변화를 모니터링할 수 있다. 제안된 방법은 한반도 지역의 2009년 8월 21일부터 2011년 9월 6일까지 총 49개의 MODIS NDVI 시계열 자료에 적용하여 모형의 유용성을 입증하였다.

Accuracy Assessment of Forest Degradation Detection in Semantic Segmentation based Deep Learning Models with Time-series Satellite Imagery

  • Woo-Dam Sim;Jung-Soo Lee
    • Journal of Forest and Environmental Science
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    • 제40권1호
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    • pp.15-23
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    • 2024
  • This research aimed to assess the possibility of detecting forest degradation using time-series satellite imagery and three different deep learning-based change detection techniques. The dataset used for the deep learning models was composed of two sets, one based on surface reflectance (SR) spectral information from satellite imagery, combined with Texture Information (GLCM; Gray-Level Co-occurrence Matrix) and terrain information. The deep learning models employed for land cover change detection included image differencing using the Unet semantic segmentation model, multi-encoder Unet model, and multi-encoder Unet++ model. The study found that there was no significant difference in accuracy between the deep learning models for forest degradation detection. Both training and validation accuracies were approx-imately 89% and 92%, respectively. Among the three deep learning models, the multi-encoder Unet model showed the most efficient analysis time and comparable accuracy. Moreover, models that incorporated both texture and gradient information in addition to spectral information were found to have a higher classification accuracy compared to models that used only spectral information. Overall, the accuracy of forest degradation extraction was outstanding, achieving 98%.