• Title/Summary/Keyword: Vegetation model

Search Result 667, Processing Time 0.021 seconds

A Study on Extraction of Croplands Located nearby Coastal Areas Using High-Resolution Satellite Imagery and LiDAR Data (고해상도 위성영상과 LiDAR 자료를 활용한 해안지역에 인접한 농경지 추출에 관한 연구)

  • Choung, Yun-Jae
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.18 no.1
    • /
    • pp.170-181
    • /
    • 2015
  • A research on extracting croplands located nearby coastal areas using the spatial information data sets is the important task for managing the agricultural products in coastal areas. This research aims to extract the various croplands(croplands on mountains and croplands on plain areas) located nearby coastal areas using the KOMPSAT-2 imagery, the high-resolution satellite imagery, and the airborne topographic LiDAR(Light Detection And Ranging) data acquired in coastal areas of Uljin, Korea. Firstly, the NDVI(Normalized Difference Vegetation Index) imagery is generated from the KOMPSAT-2 imagery, and the vegetation areas are extracted from the NDVI imagery by using the appropriate threshold. Then, the DSM(Digital Surface Model) and DEM(Digital Elevation Model) are generated from the LiDAR data by using interpolation method, and the CHM(Canopy Height Model) is generated using the differences of the pixel values of the DSM and DEM. Then the plain areas are extracted from the CHM by using the appropriate threshold. The low slope areas are also extracted from the slope map generated using the pixel values of the DEM. Finally, the areas of intersection of the vegetation areas, the plain areas and the low slope areas are extracted with the areas higher than the threshold and they are defined as the croplands located nearby coastal areas. The statistical results show that 85% of the croplands on plain areas and 15% of the croplands on mountains located nearby coastal areas are extracted by using the proposed methodology.

Land Cover Classification of High-Spatial Resolution Imagery using Fixed-Wing UAV (고정익 UAV를 이용한 고해상도 영상의 토지피복분류)

  • Yang, Sung-Ryong;Lee, Hak-Sool
    • Journal of the Society of Disaster Information
    • /
    • v.14 no.4
    • /
    • pp.501-509
    • /
    • 2018
  • Purpose: UAV-based photo measurements are being researched using UAVs in the space information field as they are not only cost-effective compared to conventional aerial imaging but also easy to obtain high-resolution data on desired time and location. In this study, the UAV-based high-resolution images were used to perform the land cover classification. Method: RGB cameras were used to obtain high-resolution images, and in addition, multi-distribution cameras were used to photograph the same regions in order to accurately classify the feeding areas. Finally, Land cover classification was carried out for a total of seven classes using created ortho image by RGB and multispectral camera, DSM(Digital Surface Model), NDVI(Normalized Difference Vegetation Index), GLCM(Gray-Level Co-occurrence Matrix) using RF (Random Forest), a representative supervisory classification system. Results: To assess the accuracy of the classification, an accuracy assessment based on the error matrix was conducted, and the accuracy assessment results were verified that the proposed method could effectively classify classes in the region by comparing with the supervisory results using RGB images only. Conclusion: In case of adding orthoimage, multispectral image, NDVI and GLCM proposed in this study, accuracy was higher than that of conventional orthoimage. Future research will attempt to improve classification accuracy through the development of additional input data.

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
    • /
    • v.38 no.6_1
    • /
    • pp.1273-1283
    • /
    • 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.

Development of Tree Detection Methods for Estimating LULUCF Settlement Greenhouse Gas Inventories Using Vegetation Indices (식생지수를 활용한 LULUCF 정주지 온실가스 인벤토리 산정을 위한 수목탐지 방법 개발)

  • Joon-Woo Lee;Yu-Han Han;Jeong-Taek Lee;Jin-Hyuk Park;Geun-Han Kim
    • Korean Journal of Remote Sensing
    • /
    • v.39 no.6_3
    • /
    • pp.1721-1730
    • /
    • 2023
  • As awareness of the problem of global warming emerges around the world, the role of carbon sinks in settlement is increasingly emphasized to achieve carbon neutrality in urban areas. In order to manage carbon sinks in settlement, it is necessary to identify the current status of carbon sinks. Identifying the status of carbon sinks requires a lot of manpower and time and a corresponding budget. Therefore, in this study, a map predicting the location of trees was created using already established tree location information and Sentinel-2 satellite images targeting Seoul. To this end, after constructing a tree presence/absence dataset, structured data was generated using 16 types of vegetation indices information constructed from satellite images. After learning this by applying the Extreme Gradient Boosting (XGBoost) model, a tree prediction map was created. Afterward, the correlation between independent and dependent variables was investigated in model learning using the Shapely value of Shapley Additive exPlanations(SHAP). A comparative analysis was performed between maps produced for local parts of Seoul and sub-categorized land cover maps. In the case of the tree prediction model produced in this study, it was confirmed that even hard-to-detect street trees around the main street were predicted as trees.

An intercomparison of two satellite data-based evapotranspiration approaches (인공위성 데이터 기반의 두 공간 증발산 산정 모형 비교 분석)

  • Sur, Chan-Yang;Choi, Min-Ha
    • Journal of Wetlands Research
    • /
    • v.13 no.3
    • /
    • pp.471-479
    • /
    • 2011
  • Evapotranspiration (ET) including evaporation from a land surface and transpiration from photosynthesis of vegetation is a hydrological factor that has an important role in water cycle. However, there is a limitation to understand it due to heterogeneity of land cover and vegetation. In this study, Mapping EvapoTRanspiration with Internalized Calibration (METRIC) model, one of the energy balance models, and MODerate resolution Imaging Spectroradiometer (MODIS) satellite based well-known Penman-Monteith algorithm were compared. Two ET maps were categorized and compared by land cover classification. The results represented overall applicability of the two models with the highest correlation coefficients in needleleaf and broadleaf forests. This study will be useful to estimate remote sensing based ET maps with high resolution and to figure out spatio-temporal variability and seasonal changes.

Estimation of Carbon Stock in the Chir Pine (Pinus roxburghii Sarg.) Plantation Forest of Kathmandu Valley, Central Nepal

  • Sharma, Krishna Prasad;Bhatta, Suresh Prashad;Khatri, Ganga Bahadur;Pajiyar, Avinash;Joshi, Daya Krishna
    • Journal of Forest and Environmental Science
    • /
    • v.36 no.1
    • /
    • pp.37-46
    • /
    • 2020
  • Vegetation carbon sequestration and regeneration are the two major parameters of forest research. In this study, we analyzed the vegetation carbon stock and regeneration of community-managed pine plantation of Kathmandu, central Nepal. Vegetation data were collected from 40 circular plots of 10 m radius (for the tree) and 1m radius (for seedling) applying a stratified random sampling and nested quadrat method. The carbon stock was estimated by Chave allometric model and estimated carbon stock was converted into CO2 equivalents. Density-diameter (d-d) curve was also prepared to check the regeneration status and stability of the plantation. A d-d curve indicates the good regeneration status of the forest with a stable population in each size class. Diversity of trees was very low, only two tree species Pinus roxburghii and Eucalyptus citriodora occurred in the sample plots. Pine was the dominant tree in terms of density, basal area, biomass, carbon stock and CO2 stock than the eucalyptus. The basal area, carbon stock and CO2 stock of forest was 33±1.0 ㎡ ha-1, 108±5.0 Mg ha-1 and 394±18 Mg ha-1, respectively. Seedling and tree density of the plantation was 4,965 ha-1 and 339 ha-1 respectively. The forest carbon stock showed a positive relationship with biomass, tree diameter, height and basal area but no relationship with tree density. Canopy cover and tree diameter have a negative effect on seedling density and regeneration. In conclusion, the community forest has a stable population in each size class, sequestering a significant amount of carbon and CO2 emitted from densely populated Kathmandu metro city as the forest biomass hence have a potentiality to mitigate the global climate change.

An Ecological Corridor Plan in an Urban Neighborhood Park - A Case Study of Noryangjin Neighborhood Park in Dongjak-gu, Seoul - (도심지역 산지형 근린공원내 도로에 의한 단절지역 생물이동통로 조성계획 연구 - 동작구 노량진근린공원을 대상으로 -)

  • Han Bong-Ho;Kim Jeong-Ho;Kim Jong-Sik
    • Journal of the Korean Institute of Landscape Architecture
    • /
    • v.33 no.2 s.109
    • /
    • pp.16-31
    • /
    • 2005
  • This study was carried out to design a bridge-type ecological corridor plan in a forested neighborhood park affected by road construction in Dongjak-gu, Seoul. In order to study the site conditions, we analyzed topography, ecosystem structure, and user behavior and trail use. Existing vegetation was classified into 12 types. Based on a vegetation analysis, the Populus albaglandulosa and Robinia pseudoacacia communities, where planted species are dominant, were distributed extensively in the southern forest area. Planted areas with a single-layer structure of Korean landscape woody plants and Robinia pseudoacacia communities with a single-layer structure were distributed extensively in the northern forest and water-supply area. Based on a study of 28 quadrats, the similarity index between the multi-layer plant communities distributed in the southern forest and the single-layer planted areas was low. Twenty-four species of wild birds(355 individuals) were found in the survey area, including nine interior species and three urban species. The study of user behavior and numbers showed most users were walkers and few users were observed in the southern forest while most users were observed in the northern forest and water supply area. We selected some wild birds as model species to represent migrating species believed to use this park as an ecological corridor during migration. We suggested the new park plan include the following: improvement of vegetation structure for wildbird migration and habitat, connection of park trails for users and presentation of a landscape linked to nature.

The Analysis of Potential Reduction of CO2 Emission In Soil and Vegetation due to Land use Change (토지이용변화에 따른 식생 및 토양의 이산화탄소 저감잠재량 분석)

  • Lee, Dong-Kun;Park, Chan
    • Journal of the Korean Society of Environmental Restoration Technology
    • /
    • v.12 no.2
    • /
    • pp.95-105
    • /
    • 2009
  • Land Use Changes (LUCs) have effects on greenhouse gas emissions and carbon stocks in soil and vegetation. Therefore, predictions for LUC are very important for achieving quantitative targets of $CO_2$ reduction rates. Some research exists on carbon fluxes and carbon cycles to estimate carbon stocks in terrestrial ecosystems in Korea. However, these researches have limitations in terms of helping us understand future potential reductions of $CO_2$ that reflect the influence of LUC. The aim of this study is to analyze the reduction levels of $CO_2$ emissions while considering LUC scenarios that effect carbon fluxes for LCS basic study in the year 2030. In this study, a common approach to model the effects of LUC on carbon stocks is the use of CA-Markov technical process with LUC patterns in the past. Potential reduction of $CO_2$ is calculated by change of land use that contains different soil organic carbon, each land use type, and biomass in vegetation. An IPCC analytical method of natural carbon sink and coefficient results from previous study in Korea is used as a calculation method for potential reduction of $CO_2$. As a result, 12,419 KtC will be reduced annually, which is 8.3% percent of 2005 $CO_2$ emissions in Korea. This will result in 3,226 hundred million won of economic efficiency. In conclusion, conservation of natural carbon sinks is necessary even if the amount of potential reduction change is little.

A Suggestion of Formulae to Calculate Sectional Tractive Force on the Slope of Cohesive River Bank and its Application (점착성 제방사면의 구간별 소류력 산정식 제안 및 적용)

  • Han, Man-Shin;Choi, Gye-Woon
    • Journal of Korea Water Resources Association
    • /
    • v.45 no.6
    • /
    • pp.583-596
    • /
    • 2012
  • The revetment is a installed structure on the slope of river bank to protect against flowing. Through the design standards of domestic and overseas, the maximum tractive force is calculated and applied to the average concept on the slope of river bank. In the case of calculating the method of permissible tractive force on the slope of river bank, there is a need to consider soil sliding. In this study, suggested the tractive force formulae by section of adhesion that have 0 < ${\Phi}$ < $90^{\circ}$ slope of river bank and installed an open channel of length of 20 m and 2 m wide for calculating permissible tractive force and hydraulic model experimented with changing discharge. According to the results, the calculated permissible tractive force of section on the slope is the largest due to the significant effects of surface roughness of different revetment materials. In addition, the permissible tractive force increased in the presence of vegetation but has no the effect by vegetation density.

Rural Land Cover Classification using Multispectral Image and LIDAR Data (디중분광영상과 LIDAR자료를 이용한 농업지역 토지피복 분류)

  • Jang Jae-Dong
    • Korean Journal of Remote Sensing
    • /
    • v.22 no.2
    • /
    • pp.101-110
    • /
    • 2006
  • The accuracy of rural land cover using airborne multispectral images and LEAR (Light Detection And Ranging) data was analyzed. Multispectral image consists of three bands in green, red and near infrared. Intensity image was derived from the first returns of LIDAR, and vegetation height image was calculated by difference between elevation of the first returns and DEM (Digital Elevation Model) derived from the last returns of LIDAR. Using maximum likelihood classification method, three bands of multispectral images, LIDAR vegetation height image, and intensity image were employed for land cover classification. Overall accuracy of classification using all the five images was improved to 85.6% about 10% higher than that using only the three bands of multispectral images. The classification accuracy of rural land cover map using multispectral images and LIDAR images, was improved with clear difference between heights of different crops and between heights of crop and tree by LIDAR data and use of LIDAR intensity for land cover classification.