메뉴 건너뛰기




Volumn 163, Issue , 2015, Pages 13-22

Optimizing the k-Nearest neighbors technique for estimating forest aboveground biomass using airborne laser scanning data

Author keywords

Distance metric; Precision

Indexed keywords

FORESTRY; LASER APPLICATIONS; MOTION COMPENSATION; SURFACE ANALYSIS;

EID: 84937395299     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2015.02.026     Document Type: Article
Times cited : (56)

References (46)
  • 3
    • 58249132746 scopus 로고    scopus 로고
    • Design-based approach to k-nearest neighbours technique for coupling field and remotely sensed data in forest surveys
    • Baffetta F., Fattorini L., Franeschi S., Corona P. Design-based approach to k-nearest neighbours technique for coupling field and remotely sensed data in forest surveys. Remote Sensing of Environment 2009, 113(3):463-475.
    • (2009) Remote Sensing of Environment , vol.113 , Issue.3 , pp. 463-475
    • Baffetta, F.1    Fattorini, L.2    Franeschi, S.3    Corona, P.4
  • 7
    • 0031334221 scopus 로고    scopus 로고
    • Selection of relevant features and examples in machine learning
    • Blum A.L., Langley P. Selection of relevant features and examples in machine learning. Artificial Intelligence 1997, 97:245-271.
    • (1997) Artificial Intelligence , vol.97 , pp. 245-271
    • Blum, A.L.1    Langley, P.2
  • 8
    • 2342549076 scopus 로고
    • Volume tables for birch
    • (In Norwegian with English summary)
    • Braastad H. Volume tables for birch. Meddelelser Norske SkogforsVes 1966, 21:265-365. (In Norwegian with English summary).
    • (1966) Meddelelser Norske SkogforsVes , vol.21 , pp. 265-365
    • Braastad, H.1
  • 9
    • 0001761759 scopus 로고
    • Volume functions and tables for Scots pine. South Norway
    • (In Norwegian with English summary)
    • Brantseg A. Volume functions and tables for Scots pine. South Norway. Meddelelser Norske SkogforsVes 1967, 22:689-739. (In Norwegian with English summary).
    • (1967) Meddelelser Norske SkogforsVes , vol.22 , pp. 689-739
    • Brantseg, A.1
  • 10
    • 84855465036 scopus 로고    scopus 로고
    • Improving k-nearest neighbor predictions in forest inventories by combining high and low density airborne laser scanning data
    • Breidenbach J., Næsset E., Gobakken T. Improving k-nearest neighbor predictions in forest inventories by combining high and low density airborne laser scanning data. Remote Sensing of Environment 2012, 117:358-365.
    • (2012) Remote Sensing of Environment , vol.117 , pp. 358-365
    • Breidenbach, J.1    Næsset, E.2    Gobakken, T.3
  • 13
  • 15
    • 33745847104 scopus 로고    scopus 로고
    • Leave-one-out error and stability of learning algorithms with applications
    • NATO Advanced Study Institute on Learning Theory and Practice
    • Elisseef A., Pontil M. Leave-one-out error and stability of learning algorithms with applications. Advances in learning theory: Methods, models, and applications 2002, 111-1130. NATO Advanced Study Institute on Learning Theory and Practice.
    • (2002) Advances in learning theory: Methods, models, and applications , pp. 111-1130
    • Elisseef, A.1    Pontil, M.2
  • 17
    • 44449130875 scopus 로고    scopus 로고
    • Assessing effects of laser point density, ground sampling intensity, and field plot sample size on biophysical stand properties derived from airborne laser scanner data
    • Gobakken T., Næsset E. Assessing effects of laser point density, ground sampling intensity, and field plot sample size on biophysical stand properties derived from airborne laser scanner data. Canadian Journal of Forest Research 2008, 38:1095-1109.
    • (2008) Canadian Journal of Forest Research , vol.38 , pp. 1095-1109
    • Gobakken, T.1    Næsset, E.2
  • 20
    • 79954529248 scopus 로고    scopus 로고
    • Comparing accuracy of airborne laser scanning and TerraSAR-X radar images in the estimation of plot-level forest variables
    • Holopainen M., Haapanen R., Karjalainen M., Vastaranta M., Hyyppä J., Yu X., et al. Comparing accuracy of airborne laser scanning and TerraSAR-X radar images in the estimation of plot-level forest variables. Remote Sensing 2010, 2:432-445.
    • (2010) Remote Sensing , vol.2 , pp. 432-445
    • Holopainen, M.1    Haapanen, R.2    Karjalainen, M.3    Vastaranta, M.4    Hyyppä, J.5    Yu, X.6
  • 21
    • 84880361849 scopus 로고    scopus 로고
    • Retrieval of forest aboveground biomass and stem volume with airborne scanning LiDAR
    • Kankare V., Vastaranta M., Holopainen M., Räty M., Yu X., Hyyppä J., et al. Retrieval of forest aboveground biomass and stem volume with airborne scanning LiDAR. Remote Sensing 2013, 5:2257-2274.
    • (2013) Remote Sensing , vol.5 , pp. 2257-2274
    • Kankare, V.1    Vastaranta, M.2    Holopainen, M.3    Räty, M.4    Yu, X.5    Hyyppä, J.6
  • 23
    • 84879799188 scopus 로고
    • Estimation of error rates in discriminant analysis
    • Lachenbruch P.A., Mickey M.R. Estimation of error rates in discriminant analysis. Technometrics 1986, 10:1-11.
    • (1986) Technometrics , vol.10 , pp. 1-11
    • Lachenbruch, P.A.1    Mickey, M.R.2
  • 25
    • 18044374299 scopus 로고    scopus 로고
    • Comparison of nearest neighbor methods for estimating basal area and stems per hectare using aerial auxiliary variables
    • LeMay V., Temesgen H. Comparison of nearest neighbor methods for estimating basal area and stems per hectare using aerial auxiliary variables. Forest Science 2005, 51(2):109-119.
    • (2005) Forest Science , vol.51 , Issue.2 , pp. 109-119
    • LeMay, V.1    Temesgen, H.2
  • 26
    • 58249141434 scopus 로고    scopus 로고
    • Model-based mean square error estimators for k-nearest neighbour predictions and applications using remotely sensed data for forest inventories
    • Magnussen S., McRoberts R.E., Tomppo E.O. Model-based mean square error estimators for k-nearest neighbour predictions and applications using remotely sensed data for forest inventories. Remote Sensing of Environment 2009, 113:476-488.
    • (2009) Remote Sensing of Environment , vol.113 , pp. 476-488
    • Magnussen, S.1    McRoberts, R.E.2    Tomppo, E.O.3
  • 27
    • 33744998400 scopus 로고    scopus 로고
    • A model-based approach to estimating forest area
    • McRoberts R.E. A model-based approach to estimating forest area. Remote Sensing of Environment 2006, 103:56-66.
    • (2006) Remote Sensing of Environment , vol.103 , pp. 56-66
    • McRoberts, R.E.1
  • 28
    • 41249099247 scopus 로고    scopus 로고
    • Using satellite imagery and the k-nearest neighbors technique as a bridge between strategic and management forest inventories
    • McRoberts R.E. Using satellite imagery and the k-nearest neighbors technique as a bridge between strategic and management forest inventories. Remote Sensing of Environment 2008, 112:2212-2221.
    • (2008) Remote Sensing of Environment , vol.112 , pp. 2212-2221
    • McRoberts, R.E.1
  • 29
    • 58249142084 scopus 로고    scopus 로고
    • Diagnostic tools for nearest neighbors techniques when used with satellite imagery
    • McRoberts R.E. Diagnostic tools for nearest neighbors techniques when used with satellite imagery. Remote Sensing of Environment 2009, 113:489-499.
    • (2009) Remote Sensing of Environment , vol.113 , pp. 489-499
    • McRoberts, R.E.1
  • 30
    • 78650879398 scopus 로고    scopus 로고
    • Satellite image-based maps: Scientific inference or pretty pictures
    • McRoberts R.E. Satellite image-based maps: Scientific inference or pretty pictures. Remote Sensing of Environment 2011, 115:715-724.
    • (2011) Remote Sensing of Environment , vol.115 , pp. 715-724
    • McRoberts, R.E.1
  • 31
    • 84857982932 scopus 로고    scopus 로고
    • Estimating forest attribute parameters for small areas using nearest neighbors techniques
    • McRoberts R.E. Estimating forest attribute parameters for small areas using nearest neighbors techniques. Forest Ecology and Management 2012, 272:3-12.
    • (2012) Forest Ecology and Management , vol.272 , pp. 3-12
    • McRoberts, R.E.1
  • 32
    • 81355138597 scopus 로고    scopus 로고
    • Parametric, bootstrap, and jackknife variance estimators for the k-Nearest Neighbors technique with illustrations using forest inventory and satellite image data
    • McRoberts R.E., Magnussen S., Tomppo E.O., Chirici G. Parametric, bootstrap, and jackknife variance estimators for the k-Nearest Neighbors technique with illustrations using forest inventory and satellite image data. Remote Sensing of Environment 2011, 115:3165-3174.
    • (2011) Remote Sensing of Environment , vol.115 , pp. 3165-3174
    • McRoberts, R.E.1    Magnussen, S.2    Tomppo, E.O.3    Chirici, G.4
  • 33
    • 84868532449 scopus 로고    scopus 로고
    • Inference for lidar-assisted estimation of forest growing stock volume
    • McRoberts R.E., Næsset E., Gobakken T. Inference for lidar-assisted estimation of forest growing stock volume. Remote Sensing of Environment 2013, 128:268-275.
    • (2013) Remote Sensing of Environment , vol.128 , pp. 268-275
    • McRoberts, R.E.1    Næsset, E.2    Gobakken, T.3
  • 34
    • 0036789610 scopus 로고    scopus 로고
    • Stratified estimation of forest area using satellite imagery, inventory data, and the k-Nearest Neighbors technique
    • McRoberts R.E., Nelson M.D., Wendt D.G. Stratified estimation of forest area using satellite imagery, inventory data, and the k-Nearest Neighbors technique. Remote Sensing of Environment 2002, 82:457-468.
    • (2002) Remote Sensing of Environment , vol.82 , pp. 457-468
    • McRoberts, R.E.1    Nelson, M.D.2    Wendt, D.G.3
  • 35
    • 35548938953 scopus 로고    scopus 로고
    • Estimating areal means and variances using the k-Nearest Neighbors technique and satellite imagery
    • McRoberts R.E., Tomppo E.O., Finley A.O., Heikkinen J. Estimating areal means and variances using the k-Nearest Neighbors technique and satellite imagery. Remote Sensing of Environment 2007, 111:466-480.
    • (2007) Remote Sensing of Environment , vol.111 , pp. 466-480
    • McRoberts, R.E.1    Tomppo, E.O.2    Finley, A.O.3    Heikkinen, J.4
  • 36
    • 84892495228 scopus 로고    scopus 로고
    • Effects of uncertainty in model predictions of individual tree volume on large area volume estimates
    • McRoberts R.E., Westfall J.A. Effects of uncertainty in model predictions of individual tree volume on large area volume estimates. Forest Science 2014, 60(1):34-42.
    • (2014) Forest Science , vol.60 , Issue.1 , pp. 34-42
    • McRoberts, R.E.1    Westfall, J.A.2
  • 37
    • 0000256443 scopus 로고
    • Most similar neighbor - an improved sampling inference procedure for natural resource planning
    • Moeur M., Stage A.R. Most similar neighbor - an improved sampling inference procedure for natural resource planning. Forest Science 1995, 41(2):337-359.
    • (1995) Forest Science , vol.41 , Issue.2 , pp. 337-359
    • Moeur, M.1    Stage, A.R.2
  • 38
    • 0036229447 scopus 로고    scopus 로고
    • Predictive mapping of forest composition and structure with direct gradient analysis and nearest neighbor imputation in coastal Oregon, U.S.A.
    • Ohmann J.L., Gregory M.J. Predictive mapping of forest composition and structure with direct gradient analysis and nearest neighbor imputation in coastal Oregon, U.S.A. Canadian Journal of Forest Research 2002, 32:725-741.
    • (2002) Canadian Journal of Forest Research , vol.32 , pp. 725-741
    • Ohmann, J.L.1    Gregory, M.J.2
  • 39
    • 84906944515 scopus 로고    scopus 로고
    • Scale considerations for integrating forest inventory plot data and satellite image data for regional forest mapping
    • Ohmann J.L., Gregory M.J., Roberts H.M. Scale considerations for integrating forest inventory plot data and satellite image data for regional forest mapping. Remote Sensing of Environment 2014, 151:3-15.
    • (2014) Remote Sensing of Environment , vol.151 , pp. 3-15
    • Ohmann, J.L.1    Gregory, M.J.2    Roberts, H.M.3
  • 43
    • 58249137246 scopus 로고    scopus 로고
    • Predicting categorical forest variables using an improved k-Nearest Neighbour estimator and Landsat imagery
    • Tomppo E.O., Gagliano C., De Natale F., Katila M., McRoberts R.E. Predicting categorical forest variables using an improved k-Nearest Neighbour estimator and Landsat imagery. Remote Sensing of Environment 2009, 113:500-517.
    • (2009) Remote Sensing of Environment , vol.113 , pp. 500-517
    • Tomppo, E.O.1    Gagliano, C.2    De Natale, F.3    Katila, M.4    McRoberts, R.E.5
  • 44
    • 3242666106 scopus 로고    scopus 로고
    • Using coarse scale forest variables as ancillary information and weighting of k-NN estimation: A genetic algorithm approach
    • Tomppo E., Halme M. Using coarse scale forest variables as ancillary information and weighting of k-NN estimation: A genetic algorithm approach. Remote Sensing of Environment 2004, 92:1-20.
    • (2004) Remote Sensing of Environment , vol.92 , pp. 1-20
    • Tomppo, E.1    Halme, M.2
  • 45
    • 84865546515 scopus 로고    scopus 로고
    • Development of Norway's National Forest Inventory
    • Springer, E. Tomppo, T. Gschwantner, M. Lawrence, R.E. McRoberts (Eds.)
    • Tomter S.M., Hylen G., Nilsen J.-E. Development of Norway's National Forest Inventory. National Forest Inventories - Pathways for Common Reporting 2010, 411-424. Springer. E. Tomppo, T. Gschwantner, M. Lawrence, R.E. McRoberts (Eds.).
    • (2010) National Forest Inventories - Pathways for Common Reporting , pp. 411-424
    • Tomter, S.M.1    Hylen, G.2    Nilsen, J.-E.3
  • 46
    • 0001761761 scopus 로고
    • Functions and tables for volume of standing trees. Norway spruce
    • (In Norwegian with English summary)
    • Vestjordet E. Functions and tables for volume of standing trees. Norway spruce. Meddelelser Norske SkogforsVes 1967, 22:539-574. (In Norwegian with English summary).
    • (1967) Meddelelser Norske SkogforsVes , vol.22 , pp. 539-574
    • Vestjordet, E.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.