연구동향 분석

위성영상을 활용한 지상부 산림바이오매스 탄소량 추정 - k-Nearest Neighbor 및 Regression Tree Analysis 방법의 비교 분석 -

정재훈 ( Jae Hoon Jung ) 우엔콩효 ( Hieu Cong Nguyen ) 허준 ( Joon Heo ) 김경민 ( Kyoung Min Kim ) 임정호 ( Jung Ho Im ) 2014년

논문상세정보
인용/피인용
' 위성영상을 활용한 지상부 산림바이오매스 탄소량 추정 - k-Nearest Neighbor 및 Regression Tree Analysis 방법의 비교 분석 -' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • aster
  • carbonstockestimation
  • k-nearestneighbor
  • landsattm
  • national forest inventory
  • regressiontreeanalysis
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
49 1

0.0%

' 위성영상을 활용한 지상부 산림바이오매스 탄소량 추정 - k-Nearest Neighbor 및 Regression Tree Analysis 방법의 비교 분석 -' 의 참고문헌

  • 위성원격탐사와 분류 및 회귀트리를 이용한 중랑천 유역의 불투수층 추정
    김수영 대한토목학회 논문집D 28 (6) : 915 ~ 922 [2008]
  • 위성영상자료 및 국가 산림자원조사 자료를 이용한 산림 바이오매스 추정
    임종수 대한원격탐사학회지 25 (4) : 311 ~ 320 [2009]
  • 원격탐사자료를 이용한 국외 산림 바이오매스 추정 현황 및 비교분석: 다섯 가지 관점에서의 고찰
    조경훈 한국지형공간정보학회지 19 (1) : 87 ~ 96 [2011]
  • 산림 바이오매스 변환표와 위성영상을 이용한 무주군의 산림 바이오매스추정
    정상영 한국임학회지 98 (4) : 409 ~ 416 [2009]
  • kNN 알고리즘과 계절별 Landsat TM 위성영상을 이용한 단양군 지역의 지상부 바이오매스 탄소저장량 추정
    정재훈 한국지형공간정보학회지 18 (4) : 119 ~ 129 [2010]
  • comparison of vegetation indices over a global set of TM images for EOS-MODIS
    Huete, A.R. Remote Sensing of Environment 59 (3) : 440 ~ 451 [1997]
  • Using coarse scale forest variables as ancillary information and weighting of variables in k-NN estimation: a genetic algorithm approach
    Tomppo, E. Remote Sensing of Environment 92 (1) : 1 ~ 20 [2004]
  • Tropical deforestation and the Kyoto Protocol
    Santilli M Climatic Change 71 (3) : 267 ~ 276 [2005]
  • Topographic normalization in rugged terrain
    Colby, J.D. Photogrammetric Engineering and Remote Sensing 57 (5) : 531 ~ 537 [1991]
  • Timber age verification using historical satellite image analysis
    Heo, J. Forest ecology and management 236 (2) : 315 ~ 323 [2006]
  • The potential and challenge of remote sensing based biomass estimation
    Lu, D. International Journal of Remote Sensing 27 (7) : 1297 ~ 1328 [2006]
  • The fate of the tropical forest: Carbon or cattle?
    Coomes, O.T. Ecological Economics 65 (2) : 207 ~ 212 [2008]
  • The Tasseled Cap De-Mystified
    Crist, E.P. Photogrammetric Engineering and Remote Sensing 52 : 81 ~ 86 [1986]
  • The 5th national forest inventory surveying: field surveying guide book ver. 1.3 37
    Korea Forest Research Institute Korea Forest Research Institute [2009]
  • Spatially explicit estimation and the uncertainty analysis of carbon stocks in pine forest using growth model and GIS: The case of Danyang area, Chungcheongbuk-do
    Kim, K.M. Seoul National University [2012]
  • Selecting estimation parameters for the Finnish multisource National Forest Inventory
    Katila, M. Remote Sensing of Environment 76 (1) : 16 ~ 32 [2001]
  • Rulequest research data mining tools
    Rulequest [2012]
  • Revised Landsat-5 TM radiometric calibration procedures and postcalibration dynamic ranges
    Chander, G. IEEE Transactions on Geoscience and Remote Sensing 41 (11) : 2674 ~ 2677 [2003]
  • Relationships between forest stand parameters and Landsat TM spectral responses in the Brazilian Amazon Basin
    Lu, D. Forest Ecology and Management 198 (1-3) : 149 ~ 167 [2004]
  • Regional forest biomass and wood volume estimation using satellite data and ancillary data
    Fazakas, Z. Agricultural and Forest Meteorology 98 : 417 ~ 425 [1999]
  • Red and photographic infrared linear combinations for monitoring vegetation
    Tucker, C.J. Remote Sensing of Environment 8 (2) : 127 ~ 150 [1979]
  • Pattern recognition principles
    Tou, J.T. [1974]
  • Overview of the radiometric and biophysical performance of the MODIS vegetation indices
    Huete, A. Remote Sensing of Environment 83 : 195 ~ 213 [2002]
  • Optimization of soil-adjusted vegetation indices
    Rondeaux, G. Remote Sensing of Environment 55 (2) : 95 ~ 107 [1996]
  • Newer classification and regression tree techniques:bagging and random forests for ecological prediction
    Prasad, A.M. Ecosystems 9 (2) : 181 ~ 199 [2006]
  • NDWI?A normalized difference water index for remote sensing of vegetation liquid water from space
    Gao, B.-c. Remote Sensing of Environment 58 (3) : 257 ~ 266 [1996]
  • Monitoring vegetation systems in the Great Plains with ERTS
    Rouse, J.W. NASA special publication [1973]
  • Measuring the Color of Growing Turf with a Reflectance Spectrophotometer
    McVey, G.R. Agronomy Journal 60 : 640 ~ 643 [1968]
  • Landsat TM 위성영상과 비율영상을 적용한 지상부 탄소 저장량 추정 - kNN 알고리즘 및 회귀 모델을 중점적으로
    유수홍 한국지형공간정보학회지 19 (2) : 39 ~ 48 [2011]
  • Good practice guidance for land use, land-use change and forestry
    Penman, J. IPCC National Greenhouse Gas Inventories Programme and Institute for Global Environmental Strategies, IGES), Kanagawa, Japan [2003]
  • GEMI: A Non-Linear Index to Monitor Global Vegetation from Satellites
    Pinty, B. Vegetatio 101 : 15 ~ 20 [1992]
  • Forest inventory-based largescale forest biomass and carbon budget assessment: new enhanced methods and use of remote sensing for verification
    Muukkonen, P. University of Helsinki [2006]
  • Forest carbon densities and uncertainties from Lidar, QuickBird, and field measurements in California
    Gonzalez, P. Remote Sensing of Environment 114 (7) : 1561 ~ 1575 [2010]
  • Estimation and mapping of forest stand density, volume and cover type using the k-nearest neighbors method
    Franco-Lopez, H. Remote Sensing of Environment 77 (3) : 251 ~ 274 [2001]
  • Estimating aboveground carbon in a catchment of the Siberian forest tundra: Combining satellite imagery and field inventory
    Fuchs, H. Remote Sensing of Environment 113 (3) : 518 ~ 531 [2009]
  • Estimating PAR absorbed by vegetation from bidirectional reflectance measurements
    Roujean, J.L. Remote Sensing of Environment 51 (3) : 375 ~ 384 [1995]
  • Effects of national forest inventory plot location error on forest carbon stock estimation using k-nearest neighbor algorithm
    Jung, J.H. ISPRS Journal of Photogrammetry and Remote Sensing 81 : 82 ~ 92 [2013]
  • Effects of forest cover, terrain, and scale on timber volume estimation with Thematic Mapper data in a rocky mountain site
    Gemmell, F.M. Remote Sensing of Environment 51 (2) : 291 ~ 305 [1995]
  • Determination of above ground carbon in Canada’s forests-a multi-source approach
    Apps, M. Bhogal, A. S. Dyk, A. Goodenough, D.G. Hall, R. Proc. of 2000 Geoscience and Remote Sensing Symposium : 949 ~ 953 [2000]
  • Countrywide estimates of forest variables using satellite data and field data from the National Forest Inventory
    Reese, H. AMBIO: A Journal of the Human Environment 32 (8) : 542 ~ 548 [2003]
  • Completion of the 2001National Land Cover Database for the Counterminous United States
    Homer, C. Photogrammetric Engineering and Remote Sensing 73 (4) : 337 ~ [2007]
  • Comparing accuracy of airborne laser scanning and TerraSAR-X radar images in the estimation of plot-level forest variables
    Holopainen, M. Remote Sensing 2 (2) : 432 ~ 445 [2010]
  • Combining national forest inventory field plots and remote sensing data for forest databases
    Tomppo, E. Remote Sensing of Environment 112 (5) : 1982 ~ 1999 [2008]
  • Child development production functions
  • Biomass mapping using forest type and structure derived from Landsat TM imagery
    Luther, J. International journal of applied earth observation and geoinformation 8 (3) : 173 ~ 187 [2006]
  • Biomass estimation using satellite remote sensing data?an investigation on possible approaches for natural forest
    Roy, P. Journal of Biosciences 21 (4) : 535 ~ 561 [1996]
  • An integrated methodology for estimation of forest fire-loss using geospatial information
    Heo, J. Environmental monitoring and assessment 144 (1) : 285 ~ 299 [2008]
  • Adapting Finnish Multi-Source Forest Inventory Techniques to the New Zealand Preharvest Inventory
    Tomppo, E. Scandinavian Journal of Forest Research 14 : 182 ~ 192 [1999]
  • Accuracy of forest mapping based on Landsat TM data and a kNN-based method
    Gjertsen, A.K. Remote Sensing of Environment 110 (4) : 420 ~ 430 [2007]
  • Accuracy comparison of various remote sensing data sources in the retrieval of forest stand attributes
    Hyyppä, J. Forest Ecology and Management 128 (1) : 109 ~ 120 [2000]
  • A temporal analysis of urban forest carbon storage using remote sensing
    Myeong, S. Remote Sensing of Environment 101 (2) : 277 ~ 282 [2006]
  • A synergetic approach to estimating timber age using integrated remotely sensed optical image and InSAR height data
    Kim, C. International Journal of Remote Sensing 33 (1) : 243 ~ 260 [2012]
  • A soil-adjusted vegetation index (SAVI)
    Huete, A.R. Remote Sensing of Environment 25 (3) : 295 ~ 309 [1988]
  • A ratio vegetation index adjusted for soil brightness
    Major, D.J. International Journal of Remote Sensing 11 : 727 ~ 740 [1990]
  • A preliminary comparison of Landsat Thematic Mapper and SPOT-1 HTV multispectral data for estimating coniferous forest volume
    Ripple, W.J. International Journal of Remote Sensing 12 : 1971 ~ 1977 [1991]
  • A modified soil adjusted vegetation index
    Qi, J. Remote Sensing of Environment 48 (2) : 119 ~ 126 [1994]
  • A comparison of four methods to map biomass from Landsat-TM and inventory data in western Newfoundland
    Labrecque, S. Forest Ecology and Management 226 (1) : 129 ~ 144 [2006]
  • A comparison of SPOT and Landsat-TM data for use in conducting inventories of forest resources
    Brockhaus, J.A. International Journal of Remote Sensing 13 (16) : 3035 ~ 3043 [1992]