• Title/Summary/Keyword: 산림피해

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Damage Degree Valuation of Forest Using NDVI from Near Infrared CCD Camera and Spectral Radiometer in a Forest Fire Area (근적외 CCD카메라와 분광반사계의 식생지수를 이용한 산불 발생지역에서의 산림 피해도 평가)

  • Choi, Seung-Pil;Kim, Dong-Hee;Park, Jong-Sun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.23 no.4
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    • pp.367-374
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    • 2005
  • Recently, forest damage has occurred often and made big issues. Among them, the damage by forest fire is not only damage of itself but also being connected with secondary damage like a flood. This is the fact that a forest fire is caused rather artificially by people than nature. In this study, we try to investigate damage of a forest fire through spectral reflectance of a plant community surveyed using a near infrared CCD camera and a SPM (Spectral Radiometer) as advanced work to use satellite image data. That is, damage of a forest fire by the naked eye observation was divided into the No damage, the light damage, the serious damage and we estimated activity of forest and grasped revival possibility of forest. Through correlation analysis between the spectral reflectance by SPM and the near infrared CCD camera, we could get high correlation in the No damage and light damage. Therefore, when we surveyed damage of a forest fire, we could grasp damage, that is hardly observed by the naked eye by, using jointly the spectral radiometer and the near infrared CCD camera.

Deep Learning-based Forest Fire Classification Evaluation for Application of CAS500-4 (농림위성 활용을 위한 산불 피해지 분류 딥러닝 알고리즘 평가)

  • Cha, Sungeun;Won, Myoungsoo;Jang, Keunchang;Kim, Kyoungmin;Kim, Wonkook;Baek, Seungil;Lim, Joongbin
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1273-1283
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    • 2022
  • Recently, forest fires have frequently occurred due to climate change, leading to human and property damage every year. The forest fire monitoring technique using remote sensing can obtain quick and large-scale information of fire-damaged areas. In this study, the Gangneung and Donghae forest fires that occurred in March 2022 were analyzed using the spectral band of Sentinel-2, the normalized difference vegetation index (NDVI), and the normalized difference water index (NDWI) to classify the affected areas of forest fires. The U-net based convolutional neural networks (CNNs) model was simulated for the fire-damaged areas. The accuracy of forest fire classification in Donghae and Gangneung classification was high at 97.3% (f1=0.486, IoU=0.946). The same model used in Donghae and Gangneung was applied to Uljin and Samcheok areas to get rid of the possibility of overfitting often happen in machine learning. As a result, the portion of overlap with the forest fire damage area reported by the National Institute of Forest Science (NIFoS) was 74.4%, confirming a high level of accuracy even considering the uncertainty of the model. This study suggests that it is possible to quantitatively evaluate the classification of forest fire-damaged area using a spectral band and indices similar to that of the Compact Advanced Satellite 500 (CAS500-4) in the Sentinel-2.

An Evaluation of Damage Scale on the Local Governments in Gangwon-do using Landslide Risk Maps (산사태 위험지도를 이용한 강원도 지자체의 피해규모 산정)

  • Yang, In Tae;Park, Jae Kook;Park, Kheun
    • Journal of Korean Society for Geospatial Information Science
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    • v.22 no.4
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    • pp.71-80
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    • 2014
  • This study predicted damage areas due to landslides in Gangwon Province and estimated the scale of damage to roads, buildings, and forests on the local government level. By using old research findings to predict landslides, the study established techniques to make maps for landslide vulnerability, occurrence possibility, and risk. The scale of damage to roads, buildings, and forests was estimated at the local government level by making a landslide risk map for 100mm, 200mm, and 300mm of accumulated rainfall. The scale of damage to roads, buildings, and forests was estimated to be greatest in Hongcheon-gun, Jeongseon-gun, and Hongcheon-gun, respectively, in case of 100mm~200mm accumulated rainfall, in Chuncheon City, Pyeongchang-gun, and Hongcheon-gun, respectively, in case of 200mm~300mm accumulated rainfall, and in Hongcheon-gun in case of 300mm accumulated rainfall or more. Those estimation results of scale of damage by landslides at the local government level will help to set priorities in landslide prevention and provide basic data for budget decisions.

A Study on Detection and Monitoring in land creeping area by Using the UAV (무인기를 활용한 산지 땅밀림 피해지점 탐지 및 모니터링 방안 연구)

  • Seo, Jun-Pyo;Woo, Choong-Shik;Lee, Chang-Woo;Kim, Dong-Yeob
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.11
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    • pp.481-487
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    • 2018
  • This paper proposes a method to detect and monitor the land creeping area using a UAV to analyze the damaged area efficiently. Using a UAV, it was possible to secure the safety of the investigators before the field survey and effectively utilize it to establish an investigation plan because an orthophoto can be used to detect and scale the cracks in a land creeping area. In addition, it was possible to analyze the scale of the crack quantitatively by extracting the topographic information from the orthophoto. The study sites were found to have a total crack area of 1.01 ha, a length of 1.07 km, an average width of 10 m, and a step distance of 1 to 10 m. Periodic UAV measurements can be used to detect displacements on the land creeping area and monitor the direction and scale of crack spread. Therefore, it is expected to be used effectively during recovery planning. Applying the UAV to the land creeping area resulted in the qualitative and quantitative results quickly and easily in dangerous mountainous watersheds. Therefore, it is expected that it will contribute to the development of related industries because of the high availability of a UAV in forest soil sediment disasters, such as landslides, debris flow, and land creeping area.

A study on the development of an automatic detection algorithm for trees suspected of being damaged by forest pests (산림병해충 피해의심목 자동탐지 알고리즘 개발 연구)

  • Hoo-Dong, LEE;Seong-Hee, LEE;Young-Jin, LEE
    • Journal of the Korean Association of Geographic Information Studies
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    • v.25 no.4
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    • pp.151-162
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    • 2022
  • Recently, the forests in Korea have accumulated damage due to continuous forest disasters, and the need for technologies to monitor forest managements is being issued. The size of the affected area is large terrain, technologies using drones, artificial intelligence, and big data are being studied. In this study, a standard dataset were conducted to develop an algorithm that automatically detects suspicious trees damaged by forest pests using deep learning and drones. Experiments using the YOLO model among object detection algorithm models, the YOLOv4-P7 model showed the highest recall rate of 69.69% and precision of 69.15%. It was confirmed that YOLOv4-P7 should be used as an automatic detection algorithm model for trees suspected of being damaged by forest pests, considering the detection target is an ortho-image with a large image size.

Development of Measures to Reduce Forest Fire by Analyzing the Occurrence Frequency and the Ignition Point of Forest Fire (산림화재의 발생빈도와 발화장소 분석을 통한 산림화재 저감을 위한 방안 도출)

  • Lee, Jae-Young;Kim, Young-Min
    • Proceedings of the Korean Society of Disaster Information Conference
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    • 2022.10a
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    • pp.439-440
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    • 2022
  • 우리나라 건기에 해당하는 봄철에는 산불화재에 예방에 주의해야 한다. 그러나 안타깝게도 이 시기에는 다양한 언론매체를 통하여 산불화재 피해에 대한 소식을 전해 들어야만 하는 것이 사실이다. 2022년 울진군에서 발생한 산불화재는 국내에서 2000년 동해안 산불에 이어 역대 2번째로 피해 규모가 큰 산불화재이다. 산불화재은 건축화재와 달리 피해면적에 광범위하기에 더욱 주의를 기울여야만 하며, 언론매체를 통한 피해 규모를 살펴보면 산불의 위험성을 증대하는 것처럼 느껴진다. 본 연구에서는 국가화재통계를 이용하여 국내에서 발생하는 산불화재의 발생빈도와 발화장소에 대하여 살펴보았다. 이를 통하여 대규모 산불화재로 인한 피해를 예방하기 위한 방안으로서 화재안전대책 우선순위를 도출하고자 하였다.

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Forest Stand and Site Characteristics in Post Forest Fire Area and Management Treatments for Optimal Vegetation Restoration (산화지의 입지와 임분특성 및 경영시업에 따른 식생변화 추이분석)

  • Lee, Kwang-Soo;Kim, Suk-Kwon;Bae, Sang-Won;Lee, Kyung-Jae;Kang, Young-Jae;Jung, Su-Young;Moon, Hyun-Shik
    • Journal of agriculture & life science
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    • v.43 no.6
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    • pp.19-27
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    • 2009
  • This study was carried out to obtain the basic model to estimate damage degree from the correlation analysis between forest fire and site environment factors and to clarify the restoration trends thorough multi-temporal survey by observing species diversity followed by various treatments at damaged forest area over time. From the derived model, the damage degree of forest fire was higher in the area of dense coniferous stands composed of simple story at the elevation of about 100m and 200m, and on steeper slope area over 30 degree. As results of this study, fire damaged trees are needed to cut down and a mixed stand with deciduous and coniferous species from the same area is desirable for the future species composition on fire damaged forest. Thus, site characteristics, local species, and mixed stands are the main consideration to enhance the vegetation recovery.

Analysis of Forest Fuel Quality by Forest Fire Damage (산림연료 특성별 산불피해도 분석)

  • Kwon, Chun-Geun;Lee, Si-Young;Lee, Myung-Woog;Lee, Hae-Pyeong
    • 한국방재학회:학술대회논문집
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    • 2011.02a
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    • pp.196-196
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    • 2011
  • 산림연료 특성별 산불피해도 분석을 위하여 산불피해의 조사지역은 2009년, 2010년 산불이 발생했던 강원도 고성지역과 양양지역, 강릉지역과 삼척지역을 조사 대상지역으로 선정하였으며, 고성군의 경우 숲구조가 유령림인 활엽수림이 2개소, 칩엽수림 1개소, 장령림인 활엽수림 2개소로 총 5개소, 양양군은 숲구조가 유령림인 침엽수림이 1개소, 장령림 침엽수림 2개소 총 3개소, 삼척시의 경우는 숲구조가 유령림인 침엽수림이 1개소 외 대조구 장령림 침엽수림 1개소, 강릉시의 경우 숲구조가 장령림인 침엽수림이 3개소 총 13개소를 각각 대상지로 선정하였다. 산림연료 특성별 산불피해도를 조사하기 위한 조사지 규모는 $10m{\times}10m$로 하였으며, 현장 조사 항목은 조사지내의 산불피해 상태, 조사지 지형특성으로 나누어 조사를 실시하였다. 산불피해 상태는 산불진행방향, DBH, 총수고, 지하고, 고사여부, 편면연소, 밀도, 수간피해율, 수관피해율 등을 조사하였고, 조사지의 지형특성을 알아보기 위해 조사지의 위치(GPS), 해발고도, 사면방위, 산지경사, 지형을 조사하였다. 현장조사를 위한 조사장비로는 조사지의 지형도, 야장, 디지털 카메라, GPS, 수고측정기, 직경테이프, 캘리퍼, 50m 줄자 2개, 2m 폴대, 클리노메타, 바인더끈 등을 사용하였다. 산불사례 현장조사를 통해 임목고사여부, 편면연소, 수간피해율, 수관피해율 등의 산불피해 특성을 분석한 결과 연료의 특성별 유령림과 장령림의 편면연소율은 유령림은 97.3%, 장령림은 16.5%로 유령림의 편면연소율이 장령림보다 80.8% 더 피해를 받는 것으로 나타났으며, 수관피해율은 유령림은 95.4%, 장령림은 19.9%로 유령림의 수관피해율이 장령림보다 75.5%더 피해를 입은 것으로 조사 되었다. 또한 임목고사율은 유령림은 73.8%, 장령림은 24.5%로 유령림의 임목고사율이 장령림보다 49.3% 더 피해를 받는 것으로 분석 되었다.

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