메뉴 건너뛰기




Volumn 84, Issue , 2020, Pages

Discrimination of species composition types of a grazed pasture landscape using Sentinel-1 and Sentinel-2 data

Author keywords

Botanical composition; Pasture species classification; Random forest; Satellite remote sensing; Support vector machine; Synthetic aperture radar

Indexed keywords

ACCURACY ASSESSMENT; COMMUNITY COMPOSITION; COMMUNITY DYNAMICS; ESTIMATION METHOD; GIS; SATELLITE DATA; SATELLITE IMAGERY; SENTINEL; SUPPORT VECTOR MACHINE;

EID: 85085559239     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2019.101978     Document Type: Article
Times cited : (29)

References (80)
  • 1
    • 84925259431 scopus 로고    scopus 로고
    • Employing ground and satellite-based QuickBird data and random forest to discriminate five tree species in a Southern African Woodland
    • Adelabu, S., Dube, T., Employing ground and satellite-based QuickBird data and random forest to discriminate five tree species in a Southern African Woodland. Geocarto Int. 30 (2015), 457–471, 10.1080/10106049.2014.885589.
    • (2015) Geocarto Int. , vol.30 , pp. 457-471
    • Adelabu, S.1    Dube, T.2
  • 2
    • 0000581356 scopus 로고
    • An introduction to kernel and nearest-neighbor nonparametric regression
    • Altman, N.S., An introduction to kernel and nearest-neighbor nonparametric regression. Am. Stat. 46 (1992), 175–185, 10.1080/00031305.1992.10475879.
    • (1992) Am. Stat. , vol.46 , pp. 175-185
    • Altman, N.S.1
  • 3
    • 85020222777 scopus 로고    scopus 로고
    • Spectral features and separability of alpine wetland grass species
    • Bao, S., Cao, C., Chen, W., Tian, H., Spectral features and separability of alpine wetland grass species. Spectrosc. Lett. 50 (2017), 245–256, 10.1080/00387010.2016.1240088.
    • (2017) Spectrosc. Lett. , vol.50 , pp. 245-256
    • Bao, S.1    Cao, C.2    Chen, W.3    Tian, H.4
  • 5
    • 84961834117 scopus 로고    scopus 로고
    • Random forest in remote sensing: a review of applications and future directions
    • Belgiu, M., Drăguţ, L., Random forest in remote sensing: a review of applications and future directions. ISPRS J. Photogramm. Remote Sens. 114 (2016), 24–31, 10.1016/j.isprsjprs.2016.01.011.
    • (2016) ISPRS J. Photogramm. Remote Sens. , vol.114 , pp. 24-31
    • Belgiu, M.1    Drăguţ, L.2
  • 6
    • 85045960898 scopus 로고    scopus 로고
    • Decision-tree, rule-based, and random forest classification of high-resolution multispectral imagery for wetland mapping and inventory
    • Berhane, T.M., Lane, C.R., Wu, Q., Autrey, B.C., Anenkhonov, O.A., Chepinoga, V.V., Liu, H., Decision-tree, rule-based, and random forest classification of high-resolution multispectral imagery for wetland mapping and inventory. Remote Sens., 10, 2018, 580, 10.3390/rs10040580.
    • (2018) Remote Sens. , vol.10 , pp. 580
    • Berhane, T.M.1    Lane, C.R.2    Wu, Q.3    Autrey, B.C.4    Anenkhonov, O.A.5    Chepinoga, V.V.6    Liu, H.7
  • 7
    • 85065082795 scopus 로고    scopus 로고
    • Livestock vocalisation classification in farm soundscapes
    • Bishop, J.C., Falzon, G., Trotter, M., Kwan, P., Meek, P.D., Livestock vocalisation classification in farm soundscapes. Comput. Electron. Agric. 162 (2019), 531–542, 10.1016/j.compag.2019.04.020.
    • (2019) Comput. Electron. Agric. , vol.162 , pp. 531-542
    • Bishop, J.C.1    Falzon, G.2    Trotter, M.3    Kwan, P.4    Meek, P.D.5
  • 8
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • Breiman, L., Random forests. Mach. Learn. 45 (2001), 5–32, 10.1023/A:1010933404324.
    • (2001) Mach. Learn. , vol.45 , pp. 5-32
    • Breiman, L.1
  • 9
    • 63749087288 scopus 로고    scopus 로고
    • Relationships between floristic diversity and vegetation indices, forest structure and landscape metrics of fragments in Brazilian Cerrado
    • Cabacinha, C.D., de Castro, S.S., Relationships between floristic diversity and vegetation indices, forest structure and landscape metrics of fragments in Brazilian Cerrado. For. Ecol. Manag. Tradit. For. Relat. Knowl. Asia 257 (2009), 2157–2165, 10.1016/j.foreco.2009.02.030.
    • (2009) For. Ecol. Manag. Tradit. For. Relat. Knowl. Asia , vol.257 , pp. 2157-2165
    • Cabacinha, C.D.1    de Castro, S.S.2
  • 10
    • 84907478732 scopus 로고    scopus 로고
    • Large differences in terrestrial vegetation production derived from satellite-based light use efficiency models
    • Cai, W., Yuan, W., Liang, S., Liu, S., Dong, W., Chen, Y., Liu, D., Zhang, H., Large differences in terrestrial vegetation production derived from satellite-based light use efficiency models. Remote Sens. 6 (2014), 8945–8965, 10.3390/rs6098945.
    • (2014) Remote Sens. , vol.6 , pp. 8945-8965
    • Cai, W.1    Yuan, W.2    Liang, S.3    Liu, S.4    Dong, W.5    Chen, Y.6    Liu, D.7    Zhang, H.8
  • 11
    • 85058891091 scopus 로고    scopus 로고
    • Identifying mangrove species using field close-range snapshot hyperspectral imaging and machine-learning techniques
    • Cao, J., Liu, K., Liu, L., Zhu, Y., Li, J., He, Z., Identifying mangrove species using field close-range snapshot hyperspectral imaging and machine-learning techniques. Remote Sens., 10, 2018, 2047, 10.3390/rs10122047.
    • (2018) Remote Sens. , vol.10 , pp. 2047
    • Cao, J.1    Liu, K.2    Liu, L.3    Zhu, Y.4    Li, J.5    He, Z.6
  • 12
    • 0036505670 scopus 로고    scopus 로고
    • A comparison of methods for multiclass support vector machines
    • Chih-Wei, Hsu, Chih-Jen, Lin, A comparison of methods for multiclass support vector machines. IEEE Trans. Neural Netw. 13 (2002), 415–425, 10.1109/72.991427.
    • (2002) IEEE Trans. Neural Netw. , vol.13 , pp. 415-425
    • Chih-Wei, H.1    Chih-Jen, L.2
  • 13
    • 85038228468 scopus 로고    scopus 로고
    • Fusion of Sentinel-1A and Sentinel-2A data for land cover mapping: a case study in the lower Magdalena region, Colombia
    • Clerici, N., Calderón, C.A.V., Posada, J.M., Fusion of Sentinel-1A and Sentinel-2A data for land cover mapping: a case study in the lower Magdalena region, Colombia. J. Maps 13 (2017), 718–726, 10.1080/17445647.2017.1372316.
    • (2017) J. Maps , vol.13 , pp. 718-726
    • Clerici, N.1    Calderón, C.A.V.2    Posada, J.M.3
  • 14
    • 34249753618 scopus 로고
    • Support-vector networks
    • Cortes, C., Vapnik, V., Support-vector networks. Mach. Learn. 20 (1995), 273–297, 10.1007/BF00994018.
    • (1995) Mach. Learn. , vol.20 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 15
    • 85061360424 scopus 로고    scopus 로고
    • Discriminating between C3, C4, and mixed C3/C4 pasture grasses of a grazed landscape using multi-temporal Sentinel-1a data
    • Crabbe, R.A., Lamb, D.W., Edwards, C., Discriminating between C3, C4, and mixed C3/C4 pasture grasses of a grazed landscape using multi-temporal Sentinel-1a data. Remote Sens., 11, 2019, 253, 10.3390/rs11030253.
    • (2019) Remote Sens. , vol.11 , pp. 253
    • Crabbe, R.A.1    Lamb, D.W.2    Edwards, C.3
  • 16
    • 85069875658 scopus 로고    scopus 로고
    • A preliminary investigation of the potential of Sentinel-1 radar to estimate pasture biomass in a grazed pasture landscape
    • Crabbe, R.A., Lamb, D.W., Edwards, C., Andersson, K., Schneider, D., A preliminary investigation of the potential of Sentinel-1 radar to estimate pasture biomass in a grazed pasture landscape. Remote Sens., 11, 2019, 872, 10.3390/rs11070872.
    • (2019) Remote Sens. , vol.11 , pp. 872
    • Crabbe, R.A.1    Lamb, D.W.2    Edwards, C.3    Andersson, K.4    Schneider, D.5
  • 18
    • 85063712587 scopus 로고    scopus 로고
    • Evaluation of variable selection methods for random forests and omics data sets
    • Degenhardt, F., Seifert, S., Szymczak, S., Evaluation of variable selection methods for random forests and omics data sets. Brief. Bioinform., 2017, 10.1093/bib/bbx124.
    • (2017) Brief. Bioinform.
    • Degenhardt, F.1    Seifert, S.2    Szymczak, S.3
  • 19
    • 30644464444 scopus 로고    scopus 로고
    • Gene selection and classification of microarray data using random forest
    • Díaz-Uriarte, R., Alvarez de Andrés, S., Gene selection and classification of microarray data using random forest. BMC Bioinform., 7, 2006, 3, 10.1186/1471-2105-7-3.
    • (2006) BMC Bioinform. , vol.7 , pp. 3
    • Díaz-Uriarte, R.1    Alvarez de Andrés, S.2
  • 20
    • 2142667047 scopus 로고    scopus 로고
    • Plant diversity effects on herbage production and compositional changes in New Zealand hill country pastures
    • Dodd, M.B., Barker, D.J., Wedderburn, M.E., Plant diversity effects on herbage production and compositional changes in New Zealand hill country pastures. Grass Forage Sci. 59 (2004), 29–40, 10.1111/j.1365-2494.2004.00402.x.
    • (2004) Grass Forage Sci. , vol.59 , pp. 29-40
    • Dodd, M.B.1    Barker, D.J.2    Wedderburn, M.E.3
  • 21
    • 34249909224 scopus 로고    scopus 로고
    • Canopy spectra and remote sensing of Ashe Juniper and associated vegetation
    • Everitt, J.H., Yang, C., Johnson, H.B., Canopy spectra and remote sensing of Ashe Juniper and associated vegetation. Environ. Monit. Assess. 130 (2007), 403–413, 10.1007/s10661-006-9407-2.
    • (2007) Environ. Monit. Assess. , vol.130 , pp. 403-413
    • Everitt, J.H.1    Yang, C.2    Johnson, H.B.3
  • 22
    • 77949472930 scopus 로고    scopus 로고
    • Mapping continuous fields of forest alpha and beta diversity
    • Feilhauer, H., Schmidtlein, S., Mapping continuous fields of forest alpha and beta diversity. Appl. Veg. Sci. 12 (2009), 429–439, 10.1111/j.1654-109X.2009.01037.x.
    • (2009) Appl. Veg. Sci. , vol.12 , pp. 429-439
    • Feilhauer, H.1    Schmidtlein, S.2
  • 23
    • 84919773193 scopus 로고    scopus 로고
    • Do we need hundreds of classifiers to solve real world classification problems?
    • Fernández-Delgado, M., Cernadas, E., Barro, S., Amorim, D., Do we need hundreds of classifiers to solve real world classification problems?. J. Mach. Learn. Res. 15 (2014), 3133–3181.
    • (2014) J. Mach. Learn. Res. , vol.15 , pp. 3133-3181
    • Fernández-Delgado, M.1    Cernadas, E.2    Barro, S.3    Amorim, D.4
  • 26
    • 80053172153 scopus 로고    scopus 로고
    • Classification of images of wheat, ryegrass and brome grass species at early growth stages using principal component analysis
    • Golzarian, M.R., Frick, R.A., Classification of images of wheat, ryegrass and brome grass species at early growth stages using principal component analysis. Plant Methods, 7, 2011, 28, 10.1186/1746-4811-7-28.
    • (2011) Plant Methods , vol.7 , pp. 28
    • Golzarian, M.R.1    Frick, R.A.2
  • 27
    • 0033673965 scopus 로고    scopus 로고
    • Remote sensing of vegetation, plant species richness, and regional biodiversity hotspots
    • Gould, W., Remote sensing of vegetation, plant species richness, and regional biodiversity hotspots. Ecol. Appl. 10 (2000), 1861–1870, 10.1890/1051-0761(2000)010[1861:RSOVPS]2.0.CO;2.
    • (2000) Ecol. Appl. , vol.10 , pp. 1861-1870
    • Gould, W.1
  • 30
    • 23844500689 scopus 로고    scopus 로고
    • Integration of optical and radar classifications for mapping pasture type in Western Australia
    • Hill, M.J., Ticehurst, C.J., Lee, Jong-Sen, Grunes, M.R., Donald, G.E., Henry, D., Integration of optical and radar classifications for mapping pasture type in Western Australia. IEEE Trans. Geosci. Remote Sens. 43 (2005), 1665–1681, 10.1109/TGRS.2005.846868.
    • (2005) IEEE Trans. Geosci. Remote Sens. , vol.43 , pp. 1665-1681
    • Hill, M.J.1    Ticehurst, C.J.2    Lee, J.-S.3    Grunes, M.R.4    Donald, G.E.5    Henry, D.6
  • 31
    • 0037138473 scopus 로고    scopus 로고
    • An assessment of support vector machines for land cover classification
    • Huang, C., Davis, L.S., Townshend, J.R.G., An assessment of support vector machines for land cover classification. Int. J. Remote Sens. 23 (2002), 725–749, 10.1080/01431160110040323.
    • (2002) Int. J. Remote Sens. , vol.23 , pp. 725-749
    • Huang, C.1    Davis, L.S.2    Townshend, J.R.G.3
  • 32
    • 85008195314 scopus 로고    scopus 로고
    • Species diversity effects on productivity, persistence and quality of multispecies swards in a four-year experiment
    • Jing, J., Søegaard, K., Cong, W.-F., Eriksen, J., Species diversity effects on productivity, persistence and quality of multispecies swards in a four-year experiment. PLoS One, 12, 2017, 10.1371/journal.pone.0169208.
    • (2017) PLoS One , vol.12
    • Jing, J.1    Søegaard, K.2    Cong, W.-F.3    Eriksen, J.4
  • 33
    • 36249023891 scopus 로고    scopus 로고
    • Pasture Plants of the Slopes and Tablelands of NSW
    • University of New England Botany
    • Kahn, L., Heard, B., Whalley, W., Pasture Plants of the Slopes and Tablelands of NSW. 2003, University of New England, Botany.
    • (2003)
    • Kahn, L.1    Heard, B.2    Whalley, W.3
  • 34
    • 85098728362 scopus 로고    scopus 로고
    • Sentinel-1 and Sentinel-2 Data Fusion for Wetlands Mapping: Balikdami
    • International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences Turkey
    • Kaplan, G., Avdan, U., Sentinel-1 and Sentinel-2 Data Fusion for Wetlands Mapping: Balikdami. 2018, International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, Turkey, 42.
    • (2018) , pp. 42
    • Kaplan, G.1    Avdan, U.2
  • 37
    • 84910139108 scopus 로고    scopus 로고
    • Earth observation satellite sensors for biodiversity monitoring: potentials and bottlenecks
    • Kuenzer, C., Ottinger, M., Wegmann, M., Guo, H., Wang, C., Zhang, J., Dech, S., Wikelski, M., Earth observation satellite sensors for biodiversity monitoring: potentials and bottlenecks. Int. J. Remote Sens. 35 (2014), 6599–6647, 10.1080/01431161.2014.964349.
    • (2014) Int. J. Remote Sens. , vol.35 , pp. 6599-6647
    • Kuenzer, C.1    Ottinger, M.2    Wegmann, M.3    Guo, H.4    Wang, C.5    Zhang, J.6    Dech, S.7    Wikelski, M.8
  • 38
    • 56249113343 scopus 로고    scopus 로고
    • Building predictive models in R using the caret package
    • Kuhn, M., Building predictive models in R using the caret package. J. Stat. Softw., 28, 2008, 10.18637/jss.v028.i05.
    • (2008) J. Stat. Softw. , vol.28
    • Kuhn, M.1
  • 39
    • 0036330812 scopus 로고    scopus 로고
    • Precision weed control system for cotton
    • Lamm, R.D., Slaughter, D.C., Giles, D.K., Precision weed control system for cotton. Trans. ASAE, 45, 2002, 231.
    • (2002) Trans. ASAE , vol.45 , pp. 231
    • Lamm, R.D.1    Slaughter, D.C.2    Giles, D.K.3
  • 40
    • 0019728197 scopus 로고
    • Refined filtering of image noise using local statistics
    • Lee, J.-S., Refined filtering of image noise using local statistics. Comput. Graph. Image Process. 15 (1981), 380–389.
    • (1981) Comput. Graph. Image Process. , vol.15 , pp. 380-389
    • Lee, J.-S.1
  • 41
    • 85048950271 scopus 로고    scopus 로고
    • Forest type identification with random forest using Sentinel-1A, Sentinel-2A, multi-temporal Landsat-8 and DEM data
    • Liu, Y., Gong, W., Hu, X., Gong, J., Forest type identification with random forest using Sentinel-1A, Sentinel-2A, multi-temporal Landsat-8 and DEM data. Remote Sens., 10, 2018, 946, 10.3390/rs10060946.
    • (2018) Remote Sens. , vol.10 , pp. 946
    • Liu, Y.1    Gong, W.2    Hu, X.3    Gong, J.4
  • 42
    • 85032861744 scopus 로고    scopus 로고
    • Spectro-temporal heterogeneity measures from dense high spatial resolution satellite image time series: application to grassland species diversity estimation
    • Lopes, M., Fauvel, M., Ouin, A., Girard, S., Spectro-temporal heterogeneity measures from dense high spatial resolution satellite image time series: application to grassland species diversity estimation. Remote Sens., 9, 2017, 993, 10.3390/rs9100993.
    • (2017) Remote Sens. , vol.9 , pp. 993
    • Lopes, M.1    Fauvel, M.2    Ouin, A.3    Girard, S.4
  • 44
    • 85059958624 scopus 로고    scopus 로고
    • The first wetland inventory map of newfoundland at a spatial resolution of 10 m using Sentinel-1 and Sentinel-2 data on the google earth engine cloud computing platform
    • Mahdianpari, M., Salehi, B., Mohammadimanesh, F., Homayouni, S., Gill, E., The first wetland inventory map of newfoundland at a spatial resolution of 10 m using Sentinel-1 and Sentinel-2 data on the google earth engine cloud computing platform. Remote Sens., 11, 2019, 43, 10.3390/rs11010043.
    • (2019) Remote Sens. , vol.11 , pp. 43
    • Mahdianpari, M.1    Salehi, B.2    Mohammadimanesh, F.3    Homayouni, S.4    Gill, E.5
  • 45
    • 26844554427 scopus 로고    scopus 로고
    • Estimation of Mediterranean forest attributes by the application of k-NN procedures to multitemporal Landsat ETM+ images
    • Maselli, F., Chirici, G., Bottai, L., Corona, P., Marchetti, M., Estimation of Mediterranean forest attributes by the application of k-NN procedures to multitemporal Landsat ETM+ images. Int. J. Remote Sens. 26 (2005), 3781–3796, 10.1080/01431160500166433.
    • (2005) Int. J. Remote Sens. , vol.26 , pp. 3781-3796
    • Maselli, F.1    Chirici, G.2    Bottai, L.3    Corona, P.4    Marchetti, M.5
  • 46
    • 85048716904 scopus 로고    scopus 로고
    • Implementation of machine-learning classification in remote sensing: an applied review
    • Maxwell, A.E., Warner, T.A., Fang, F., Implementation of machine-learning classification in remote sensing: an applied review. Int. J. Remote Sens. 39 (2018), 2784–2817, 10.1080/01431161.2018.1433343.
    • (2018) Int. J. Remote Sens. , vol.39 , pp. 2784-2817
    • Maxwell, A.E.1    Warner, T.A.2    Fang, F.3
  • 47
    • 84923357893 scopus 로고    scopus 로고
    • Assessing machine-learning algorithms and image- and lidar-derived variables for GEOBIA classification of mining and mine reclamation
    • Maxwell, A.E., Warner, T.A., Strager, M.P., Conley, J.F., Sharp, A.L., Assessing machine-learning algorithms and image- and lidar-derived variables for GEOBIA classification of mining and mine reclamation. Int. J. Remote Sens. 36 (2015), 954–978, 10.1080/01431161.2014.1001086.
    • (2015) Int. J. Remote Sens. , vol.36 , pp. 954-978
    • Maxwell, A.E.1    Warner, T.A.2    Strager, M.P.3    Conley, J.F.4    Sharp, A.L.5
  • 49
    • 79951950272 scopus 로고    scopus 로고
    • Support vector machines in remote sensing: a review
    • Mountrakis, G., Im, J., Ogole, C., Support vector machines in remote sensing: a review. ISPRS J. Photogramm. Remote Sens. 66 (2011), 247–259, 10.1016/j.isprsjprs.2010.11.001.
    • (2011) ISPRS J. Photogramm. Remote Sens. , vol.66 , pp. 247-259
    • Mountrakis, G.1    Im, J.2    Ogole, C.3
  • 50
    • 0034900424 scopus 로고    scopus 로고
    • Indices of grassland biodiversity in the chihuahuan desert ecoregion derived from remote sensing
    • Muldavin, E.H., Neville, P., Harper, G., Indices of grassland biodiversity in the chihuahuan desert ecoregion derived from remote sensing. Conserv. Biol. 15 (2001), 844–855, 10.1046/j.1523-1739.2001.015004844.x.
    • (2001) Conserv. Biol. , vol.15 , pp. 844-855
    • Muldavin, E.H.1    Neville, P.2    Harper, G.3
  • 51
    • 77956876008 scopus 로고    scopus 로고
    • Assessing plant diversity in a dry tropical forest: comparing the utility of landsat and ikonos satellite images
    • Nagendra, H., Rocchini, D., Ghate, R., Sharma, B., Pareeth, S., Assessing plant diversity in a dry tropical forest: comparing the utility of landsat and ikonos satellite images. Remote Sens. 2 (2010), 478–496, 10.3390/rs2020478.
    • (2010) Remote Sens. , vol.2 , pp. 478-496
    • Nagendra, H.1    Rocchini, D.2    Ghate, R.3    Sharma, B.4    Pareeth, S.5
  • 52
    • 84869488312 scopus 로고    scopus 로고
    • Evaluation of SVM, RVM and SMLR for accurate image classification with limited ground data
    • Pal, M., Foody, G.M., Evaluation of SVM, RVM and SMLR for accurate image classification with limited ground data. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 5 (2012), 1344–1355, 10.1109/JSTARS.2012.2215310.
    • (2012) IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. , vol.5 , pp. 1344-1355
    • Pal, M.1    Foody, G.M.2
  • 53
    • 77951295936 scopus 로고    scopus 로고
    • Feature selection for classification of hyperspectral data by SVM
    • Pal, M., Foody, G.M., Feature selection for classification of hyperspectral data by SVM. IEEE Trans. Geosci. Remote Sens. 48 (2010), 2297–2307.
    • (2010) IEEE Trans. Geosci. Remote Sens. , vol.48 , pp. 2297-2307
    • Pal, M.1    Foody, G.M.2
  • 54
    • 13644256120 scopus 로고    scopus 로고
    • Support vector machines for classification in remote sensing
    • Pal, M., Mather, P.M., Support vector machines for classification in remote sensing. Int. J. Remote Sens. 26 (2005), 1007–1011, 10.1080/01431160512331314083.
    • (2005) Int. J. Remote Sens. , vol.26 , pp. 1007-1011
    • Pal, M.1    Mather, P.M.2
  • 55
    • 84953776171 scopus 로고    scopus 로고
    • Changes in plant species richness and productivity in response to decreased nitrogen inputs in grassland in southern England
    • Pallett, D.W., Pescott, O.L., Schäfer, S.M., Changes in plant species richness and productivity in response to decreased nitrogen inputs in grassland in southern England. Ecol. Indic. 68 (2016), 73–81, 10.1016/j.ecolind.2015.12.024.
    • (2016) Ecol. Indic. , vol.68 , pp. 73-81
    • Pallett, D.W.1    Pescott, O.L.2    Schäfer, S.M.3
  • 56
    • 85039918306 scopus 로고    scopus 로고
    • High-dimensional data classification
    • F. Aleskerov B. Goldengorin P.M. Pardalos Springer New York, New York, NY
    • Pappu, V., Pardalos, P.M., High-dimensional data classification. Aleskerov, F., Goldengorin, B., Pardalos, P.M., (eds.) Clusters, Orders, and Trees: Methods and Applications, 2014, Springer, New York, New York, NY, 119–150, 10.1007/978-1-4939-0742-7_8.
    • (2014) Clusters, Orders, and Trees: Methods and Applications , pp. 119-150
    • Pappu, V.1    Pardalos, P.M.2
  • 57
    • 85044231757 scopus 로고    scopus 로고
    • Assessment of plant species diversity based on hyperspectral indices at a fine scale
    • Peng, Y., Fan, M., Song, J., Cui, T., Li, R., Assessment of plant species diversity based on hyperspectral indices at a fine scale. Sci. Rep., 8, 2018, 4776, 10.1038/s41598-018-23136-5.
    • (2018) Sci. Rep. , vol.8 , pp. 4776
    • Peng, Y.1    Fan, M.2    Song, J.3    Cui, T.4    Li, R.5
  • 58
    • 0036900660 scopus 로고    scopus 로고
    • Comparison of Landsat TM and ERS-2 SAR data for discriminating among grassland types and treatments in eastern Kansas
    • Price, K.P., Guo, X., Stiles, J.M., Comparison of Landsat TM and ERS-2 SAR data for discriminating among grassland types and treatments in eastern Kansas. Comput. Electron. Agric. 37 (2002), 157–171, 10.1016/S0168-1699(02)00110-2.
    • (2002) Comput. Electron. Agric. , vol.37 , pp. 157-171
    • Price, K.P.1    Guo, X.2    Stiles, J.M.3
  • 59
    • 35548986987 scopus 로고    scopus 로고
    • Effects of spatial and spectral resolution in estimating ecosystem α-diversity by satellite imagery
    • Rocchini, D., Effects of spatial and spectral resolution in estimating ecosystem α-diversity by satellite imagery. Remote Sens. Environ. 111 (2007), 423–434, 10.1016/j.rse.2007.03.018.
    • (2007) Remote Sens. Environ. , vol.111 , pp. 423-434
    • Rocchini, D.1
  • 61
  • 62
    • 26844580765 scopus 로고    scopus 로고
    • Forage mixture productivity and botanical composition in pastures grazed by dairy cattle
    • Sanderson, M.A., Soder, K.J., Muller, L.D., Klement, K.D., Skinner, R.H., Goslee, S.C., Forage mixture productivity and botanical composition in pastures grazed by dairy cattle. Agron. J. 97 (2005), 1465–1471, 10.2134/agronj2005.0032.
    • (2005) Agron. J. , vol.97 , pp. 1465-1471
    • Sanderson, M.A.1    Soder, K.J.2    Muller, L.D.3    Klement, K.D.4    Skinner, R.H.5    Goslee, S.C.6
  • 63
    • 85052154849 scopus 로고    scopus 로고
    • Synergetic use of Sentinel-1 and Sentinel-2 for assessments of heathland conservation status
    • Schmidt, J., Fassnacht, F.E., Förster, M., Schmidtlein, S., Synergetic use of Sentinel-1 and Sentinel-2 for assessments of heathland conservation status. Remote Sens. Ecol. Conserv. 4 (2018), 225–239, 10.1002/rse2.68.
    • (2018) Remote Sens. Ecol. Conserv. , vol.4 , pp. 225-239
    • Schmidt, J.1    Fassnacht, F.E.2    Förster, M.3    Schmidtlein, S.4
  • 64
    • 0004048620 scopus 로고    scopus 로고
    • Remote Sensing: Models and Methods for Image Processing
    • 3rd edition Academic Press Burlington, MA
    • Schowengerdt, R.A., Remote Sensing: Models and Methods for Image Processing. 3rd edition, 2006, Academic Press, Burlington, MA.
    • (2006)
    • Schowengerdt, R.A.1
  • 65
    • 84988416232 scopus 로고    scopus 로고
    • An assessment of algorithmic parameters affecting image classification accuracy by random forests
    • Shi, D., Yang, X., An assessment of algorithmic parameters affecting image classification accuracy by random forests. Photogramm. Eng. Remote Sens. 82 (2016), 407–417, 10.1016/S0099-1112(16)82032-7.
    • (2016) Photogramm. Eng. Remote Sens. , vol.82 , pp. 407-417
    • Shi, D.1    Yang, X.2
  • 66
    • 33645210431 scopus 로고    scopus 로고
    • Above- and belowground productivity and soil carbon dynamics of pasture mixtures
    • Skinner, R.H., Sanderson, M.A., Tracy, B.F., Dell, C.J., Above- and belowground productivity and soil carbon dynamics of pasture mixtures. Agron. J. 98 (2006), 320–326, 10.2134/agronj2005.0180a.
    • (2006) Agron. J. , vol.98 , pp. 320-326
    • Skinner, R.H.1    Sanderson, M.A.2    Tracy, B.F.3    Dell, C.J.4
  • 67
    • 80955153371 scopus 로고    scopus 로고
    • Investigating RADARSAT-2 as a tool for monitoring grassland in western Canada
    • Smith, A.M., Buckley, J.R., Investigating RADARSAT-2 as a tool for monitoring grassland in western Canada. Can. J. Remote Sens. 37 (2011), 93–102, 10.5589/m11-027.
    • (2011) Can. J. Remote Sens. , vol.37 , pp. 93-102
    • Smith, A.M.1    Buckley, J.R.2
  • 68
    • 85059936380 scopus 로고    scopus 로고
    • Combining Sentinel-1 and Sentinel-2 data for improved land use and land cover mapping of monsoon regions
    • Steinhausen, M.J., Wagner, P.D., Narasimhan, B., Waske, B., Combining Sentinel-1 and Sentinel-2 data for improved land use and land cover mapping of monsoon regions. Int. J. Appl. Earth Obs. Geoinf. 73 (2018), 595–604, 10.1016/j.jag.2018.08.011.
    • (2018) Int. J. Appl. Earth Obs. Geoinf. , vol.73 , pp. 595-604
    • Steinhausen, M.J.1    Wagner, P.D.2    Narasimhan, B.3    Waske, B.4
  • 70
    • 85019762868 scopus 로고    scopus 로고
    • Random forest classification of wetland landcovers from multi-sensor data in the arid region of Xinjiang, China
    • Tian, S., Zhang, X., Tian, J., Sun, Q., Random forest classification of wetland landcovers from multi-sensor data in the arid region of Xinjiang, China. Remote Sens., 8, 2016, 954, 10.3390/rs8110954.
    • (2016) Remote Sens. , vol.8 , pp. 954
    • Tian, S.1    Zhang, X.2    Tian, J.3    Sun, Q.4
  • 71
    • 0028181948 scopus 로고
    • Biodiversity and stability in grasslands
    • Tilman, D., Downing, J.A., Biodiversity and stability in grasslands. Nature, 367, 1994, 363, 10.1038/367363a0.
    • (1994) Nature , vol.367 , pp. 363
    • Tilman, D.1    Downing, J.A.2
  • 72
    • 0003404298 scopus 로고
    • BOTANAL: A Comprehensive Sampling and Computing Procedure for Estimating Pasture Yield and Composition. I, I
    • CSIRO, Division of Tropical Crops and Pastures Brisbane
    • Tothill, J.C., Jones, R.M., Hargreaves, J.N.G., Commonwealth Scientific and Industrial Research Organization (Australia), Division of Tropical Crops and Pastures, BOTANAL: A Comprehensive Sampling and Computing Procedure for Estimating Pasture Yield and Composition. I, I. 1978, CSIRO, Division of Tropical Crops and Pastures, Brisbane.
    • (1978)
    • Tothill, J.C.1    Jones, R.M.2    Hargreaves, J.N.G.3
  • 73
    • 11144229035 scopus 로고    scopus 로고
    • Effects of plant diversity on invasion of weed species in experimental pasture communities
    • Tracy, B.F., Renne, I.J., Gerrish, J., Sanderson, M.A., Effects of plant diversity on invasion of weed species in experimental pasture communities. Basic Appl. Ecol. 5 (2004), 543–550, 10.1016/j.baae.2004.08.007.
    • (2004) Basic Appl. Ecol. , vol.5 , pp. 543-550
    • Tracy, B.F.1    Renne, I.J.2    Gerrish, J.3    Sanderson, M.A.4
  • 74
    • 1542351520 scopus 로고    scopus 로고
    • Forage productivity, species evenness and weed invasion in pasture communities
    • Tracy, B.F., Sanderson, M.A., Forage productivity, species evenness and weed invasion in pasture communities. Agric. Ecosyst. Environ. 102 (2004), 175–183, 10.1016/j.agee.2003.08.002.
    • (2004) Agric. Ecosyst. Environ. , vol.102 , pp. 175-183
    • Tracy, B.F.1    Sanderson, M.A.2
  • 76
    • 0003450542 scopus 로고
    • The Nature of Statistical Learning Theory
    • Springer New York, New York, NY
    • Vapnik, V.N., The Nature of Statistical Learning Theory. 1995, Springer, New York, New York, NY, 10.1007/978-1-4757-2440-0.
    • (1995)
    • Vapnik, V.N.1
  • 77
    • 42449161875 scopus 로고    scopus 로고
    • Feature extraction for the identification of weed species in digital images for the purpose of site-specific weed control
    • Weis, M., Gerhards, R., Feature extraction for the identification of weed species in digital images for the purpose of site-specific weed control. Precis. Agric. 7 (2007), 537–545.
    • (2007) Precis. Agric. , vol.7 , pp. 537-545
    • Weis, M.1    Gerhards, R.2
  • 78
    • 84988697081 scopus 로고    scopus 로고
    • Mapping the distributions of C3 and C4 grasses in the mixed-grass prairies of southwest Oklahoma using the Random Forest classification algorithm
    • Yan, D., de Beurs, K.M., Mapping the distributions of C3 and C4 grasses in the mixed-grass prairies of southwest Oklahoma using the Random Forest classification algorithm. Int. J. Appl. Earth Obs. Geoinf. 47 (2016), 125–138, 10.1016/j.jag.2015.12.007.
    • (2016) Int. J. Appl. Earth Obs. Geoinf. , vol.47 , pp. 125-138
    • Yan, D.1    de Beurs, K.M.2
  • 80
    • 84902481208 scopus 로고    scopus 로고
    • Object-based vegetation mapping in the Kissimmee River watershed using HyMap data and machine learning techniques
    • Zhang, C., Xie, Z., Object-based vegetation mapping in the Kissimmee River watershed using HyMap data and machine learning techniques. Wetlands 33 (2013), 233–244, 10.1007/s13157-012-0373-x.
    • (2013) Wetlands , vol.33 , pp. 233-244
    • Zhang, C.1    Xie, Z.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.