Abstract

The fraction of absorbed photosynthetically active radiation (FPAR) is a key parameter for ecosystem modeling, crop growth monitoring and yield prediction. Ground-based FPAR measurements are time consuming and labor intensive. Remote sensing provides an alternative method to obtain repeated, rapid and inexpensive estimates of FPAR over large areas. LiDAR is an active remote sensing technology and can be used to extract accurate canopy structure parameters. A method to estimating FPAR of maize from airborne discrete-return LiDAR data was developed and tested in this study. The raw LiDAR point clouds were processed to separate ground returns from vegetation returns using a filter method over a maize field in the Heihe River Basin, northwest China. The fractional cover (fCover) of maize canopy was computed using the ratio of canopy return counts or intensity sums to the total of returns or intensities. FPAR estimation models were established based on linear regression analysis between the LiDAR-derived fCover and the field-measured FPAR (R2 = 0.90, RMSE = 0.032, p < 0.001). The reliability of the constructed regression model was assessed using the leave-one-out cross-validation procedure and results show that the regression model is not overfitting the data and has a good generalization capability. Finally, 15 independent field-measured FPARs were used to evaluate accuracy of the LiDAR-predicted FPARs and results show that the LiDAR-predicted FPAR has a high accuracy (R2 = 0.89, RMSE = 0.034). In summary, this study suggests that the airborne discrete-return LiDAR data could be adopted to accurately estimate FPAR of maize.

© 2014 Optical Society of America

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2013 (3)

S. P. Serbin, D. E. Ahl, and S. T. Gower, “Spatial and temporal validation of the MODIS LAI and FPAR products across a boreal forest wildfire chronosequence,” Remote Sens. Environ. 133(0), 71–84 (2013).
[Crossref]

S. Dupuy, G. Lainé, J. Tassin, and J.-M. Sarrailh, “Characterization of the horizontal structure of the tropical forest canopy using object-based LiDAR and multispectral image analysis,” Int. J. Appl. Earth Obs. Geoinf. 25, 76–86 (2013).
[Crossref]

S. Luo, C. Wang, G. Li, and X. Xi, “Retrieving leaf area index using ICESat/GLAS full-waveform data,” Remote Sens. Lett. 4(8), 745–753 (2013).
[Crossref]

2012 (6)

B. C. Bright, J. A. Hicke, and A. T. Hudak, “Estimating aboveground carbon stocks of a forest affected by mountain pine beetle in Idaho using lidar and multispectral imagery,” Remote Sens. Environ. 124, 270–281 (2012).
[Crossref]

F. J. Mesas-Carrascosa, I. L. Castillejo-González, M. S. de la Orden, and A. G.-F. Porras, “Combining LiDAR intensity with aerial camera data to discriminate agricultural land uses,” Comput. Electron. Agric. 84(0), 36–46 (2012).
[Crossref]

T. Hakala, J. Suomalainen, S. Kaasalainen, and Y. Chen, “Full waveform hyperspectral LiDAR for terrestrial laser scanning,” Opt. Express 20(7), 7119–7127 (2012).
[Crossref] [PubMed]

A. Peduzzi, R. H. Wynne, T. R. Fox, R. F. Nelson, and V. A. Thomas, “Estimating leaf area index in intensively managed pine plantations using airborne laser scanner data,” For. Ecol. Manage. 270(0), 54–65 (2012).
[Crossref]

Y. Qin, T. T. Vu, Y. Ban, and Z. Niu, “Range determination for generating point clouds from airborne small footprint LiDAR waveforms,” Opt. Express 20(23), 25935–25947 (2012).
[Crossref] [PubMed]

D. Peng, B. Zhang, L. Liu, D. Chen, H. Fang, and Y. Hu, “Seasonal dynamic pattern analysis on global FPAR derived from AVHRR GIMMS NDVI,” Int. J. Digit. Earth 5(5), 439–455 (2012).
[Crossref]

2011 (6)

D. Van der Zande, J. Stuckens, W. W. Verstraeten, S. Mereu, B. Muys, and P. Coppin, “3D modeling of light interception in heterogeneous forest canopies using ground-based LiDAR data,” Int. J. Appl. Earth Obs. Geoinf. 13(5), 792–800 (2011).
[Crossref]

F. Samadzadegan, F. T. Mahmoudi, and T. Schenk, “Information fusion of Lidar range and intensity data for automatic building recognition,” Int. J. Image Data Fusion 2(1), 37–60 (2011).
[Crossref]

L. Korhonen, I. Korpela, J. Heiskanen, and M. Maltamo, “Airborne discrete-return LIDAR data in the estimation of vertical canopy cover, angular canopy closure and leaf area index,” Remote Sens. Environ. 115(4), 1065–1080 (2011).
[Crossref]

G. Sun, K. J. Ranson, Z. Guo, Z. Zhang, P. Montesano, and D. Kimes, “Forest biomass mapping from lidar and radar synergies,” Remote Sens. Environ. 115(11), 2906–2916 (2011).
[Crossref]

S. Tonolli, M. Dalponte, M. Neteler, M. Rodeghiero, L. Vescovo, and D. Gianelle, “Fusion of airborne LiDAR and satellite multispectral data for the estimation of timber volume in the Southern Alps,” Remote Sens. Environ. 115(10), 2486–2498 (2011).
[Crossref]

M. García, D. Riaño, E. Chuvieco, J. Salas, and F. M. Danson, “Multispectral and LiDAR data fusion for fuel type mapping using Support Vector Machine and decision rules,” Remote Sens. Environ. 115(6), 1369–1379 (2011).
[Crossref]

2010 (5)

T. L. Erdody and L. M. Moskal, “Fusion of LiDAR and imagery for estimating forest canopy fuels,” Remote Sens. Environ. 114(4), 725–737 (2010).
[Crossref]

S. Solberg, “Mapping gap fraction, LAI and defoliation using various ALS penetration variables,” Int. J. Remote Sens. 31(5), 1227–1244 (2010).
[Crossref]

M. García, D. Riaño, E. Chuvieco, and F. M. Danson, “Estimating biomass carbon stocks for a Mediterranean forest in central Spain using LiDAR height and intensity data,” Remote Sens. Environ. 114(4), 816–830 (2010).
[Crossref]

F. Chen, K. T. Weber, J. Anderson, and B. Gokhale, “Comparison of MODIS fPAR products with Landsat-5 TM-derived fPAR over semiarid Rangelands of Idaho,” GISci. Remote Sens. 47(3), 360–378 (2010).

I. McCallum, W. Wagner, C. Schmullius, A. Shvidenko, M. Obersteiner, S. Fritz, and S. Nilsson, “Comparison of four global FAPAR datasets over Northern Eurasia for the year 2000,” Remote Sens. Environ. 114(5), 941–949 (2010).
[Crossref]

2009 (9)

H. Lee, K. C. Slatton, B. E. Roth, and W. P. Cropper, “Prediction of forest canopy light interception using three-dimensional airborne LiDAR data,” Int. J. Remote Sens. 30(1), 189–207 (2009).
[Crossref]

P. Propastin and M. Kappas, “Modeling net ecosystem exchange for grassland in Central Kazakhstan by combining remote sensing and field data,” Remote Sens. 1(3), 159–183 (2009).
[Crossref]

B. D. Cook, P. V. Bolstad, E. Næsset, R. S. Anderson, S. Garrigues, J. T. Morisette, J. Nickeson, and K. J. Davis, “Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations,” Remote Sens. Environ. 113(11), 2366–2379 (2009).
[Crossref]

J. J. Richardson, L. M. Moskal, and S.-H. Kim, “Modeling approaches to estimate effective leaf area index from aerial discrete-return LIDAR,” Agric. For. Meteorol. 149(6–7), 1152–1160 (2009).
[Crossref]

C. Wang, M. Menenti, M. Stoll, A. Feola, E. Belluco, and M. Marani, “Separation of ground and low vegetation signatures in LiDAR measurements of salt-marsh environments,” IEEE Trans. Geosci. Rem. Sens. 47(7), 2014–2023 (2009).
[Crossref]

K. Zhao and S. Popescu, “Lidar-based mapping of leaf area index and its use for validating GLOBCARBON satellite LAI product in a temperate forest of the southern USA,” Remote Sens. Environ. 113(8), 1628–1645 (2009).
[Crossref]

E. Næsset, “Effects of different sensors, flying altitudes, and pulse repetition frequencies on forest canopy metrics and biophysical stand properties derived from small-footprint airborne laser data,” Remote Sens. Environ. 113(1), 148–159 (2009).
[Crossref]

C. Hopkinson and L. Chasmer, “Testing LiDAR models of fractional cover across multiple forest ecozones,” Remote Sens. Environ. 113(1), 275–288 (2009).
[Crossref]

F. Morsdorf, C. Nichol, T. Malthus, and I. H. Woodhouse, “Assessing forest structural and physiological information content of multi-spectral LiDAR waveforms by radiative transfer modelling,” Remote Sens. Environ. 113(10), 2152–2163 (2009).
[Crossref]

2008 (7)

M. Dalponte, L. Bruzzone, and D. Gianelle, “Fusion of hyperspectral and LiDAR remote sensing data for classification of complex forest areas,” IEEE Trans. Geosci. Rem. Sens. 46(5), 1416–1427 (2008).
[Crossref]

L. Ronggao, L. Shunlin, H. Honglin, L. Jiyuan, and Z. Tao, “Mapping incident photosynthetically active radiation from MODIS data over China,” Remote Sens. Environ. 112(3), 998–1009 (2008).
[Crossref]

M. A. Brovelli, M. Crespi, F. Fratarcangeli, F. Giannone, and E. Realini, “Accuracy assessment of high resolution satellite imagery orientation by leave-one-out method,” ISPRS J. Photogramm. Remote Sens. 63(4), 427–440 (2008).
[Crossref]

A. Kukko, S. Kaasalainen, and P. Litkey, “Effect of incidence angle on laser scanner intensity and surface data,” Appl. Opt. 47(7), 986–992 (2008).
[Crossref] [PubMed]

J. L. R. Jensen, K. S. Humes, L. A. Vierling, and A. T. Hudak, “Discrete return LiDAR-based prediction of leaf area index in two conifer forests,” Remote Sens. Environ. 112(10), 3947–3957 (2008).
[Crossref]

D. Huang, Y. Knyazikhin, W. Wang, D. W. Deering, P. Stenberg, N. Shabanov, B. Tan, and R. B. Myneni, “Stochastic transport theory for investigating the three-dimensional canopy structure from space measurements,” Remote Sens. Environ. 112(1), 35–50 (2008).
[Crossref]

L. Chasmer, C. Hopkinson, P. Treitz, H. McCaughey, A. Barr, and A. Black, “A liDAR-based hierarchical approach for assessing MODIS fPAR,” Remote Sens. Environ. 112(12), 4344–4357 (2008).
[Crossref]

2007 (2)

B. Höfle and N. Pfeifer, “Correction of laser scanning intensity data: Data and model-driven approaches,” ISPRS J. Photogramm. Remote Sens. 62(6), 415–433 (2007).
[Crossref]

B. Koetz, G. Sun, F. Morsdorf, K. J. Ranson, M. Kneubühler, K. Itten, and B. Allgöwer, “Fusion of imaging spectrometer and LIDAR data over combined radiative transfer models for forest canopy characterization,” Remote Sens. Environ. 106(4), 449–459 (2007).
[Crossref]

2006 (2)

V. Thomas, D. A. Finch, J. H. McCaughey, T. Noland, L. Rich, and P. Treitz, “Spatial modelling of the fraction of photosynthetically active radiation absorbed by a boreal mixedwood forest using a LiDAR-hyperspectral approach,” Agric. For. Meteorol. 140(1–4), 287–307 (2006).
[Crossref]

F. Morsdorf, B. Kötz, E. Meier, K. I. Itten, and B. Allgöwer, “Estimation of LAI and fractional cover from small footprint airborne laser scanning data based on gap fraction,” Remote Sens. Environ. 104(1), 50–61 (2006).
[Crossref]

2005 (2)

M. A. Lefsky, A. T. Hudak, W. B. Cohen, and S. A. Acker, “Geographic variability in lidar predictions of forest stand structure in the Pacific Northwest,” Remote Sens. Environ. 95(4), 532–548 (2005).
[Crossref]

Q. Wang, S. Adiku, J. Tenhunen, and A. Granier, “On the relationship of NDVI with leaf area index in a deciduous forest site,” Remote Sens. Environ. 94(2), 244–255 (2005).
[Crossref]

2004 (3)

R. Fensholt, I. Sandholt, and M. S. Rasmussen, “Evaluation of MODIS LAI, fAPAR and the relation between fAPAR and NDVI in a semi-arid environment using in situ measurements,” Remote Sens. Environ. 91(3–4), 490–507 (2004).
[Crossref]

S. C. Popescu, R. H. Wynne, and J. A. Scrivani, “Fusion of small-footprint LiDAR and multispectral data to estimate plot-level volume and biomass in deciduous and pine forests in Virginia, USA,” For. Sci. 50(4), 551–565 (2004).

D. Riaño, F. Valladares, S. Condés, and E. Chuvieco, “Estimation of leaf area index and covered ground from airborne laser scanner (LiDAR) in two contrasting forests,” Agric. For. Meteorol. 124(3–4), 269–275 (2004).
[Crossref]

2003 (5)

K. W. Todd, F. Csillag, and P. M. Atkinson, “Three-dimensional mapping of light transmittance and foliage distribution using LiDAR,” Can. J. Rem. Sens. 29(5), 544–555 (2003).
[Crossref]

N. V. Shabanov, Y. Wang, W. Buermann, J. Dong, S. Hoffman, G. R. Smith, Y. Tian, Y. Knyazikhin, and R. B. Myneni, “Effect of foliage spatial heterogeneity in the MODIS LAI and FPAR algorithm over broadleaf forests,” Remote Sens. Environ. 85(4), 410–423 (2003).
[Crossref]

J. M. Chen, J. Liu, S. G. Leblanc, R. Lacaze, and J.-L. Roujean, “Multi-angular optical remote sensing for assessing vegetation structure and carbon absorption,” Remote Sens. Environ. 84(4), 516–525 (2003).
[Crossref]

S. C. Popescu, R. H. Wynne, and R. F. Nelson, “Measuring individual tree crown diameter with lidar and assessing its influence on estimating forest volume and biomass,” Can. J. Rem. Sens. 29(5), 564–577 (2003).
[Crossref]

K. Lim, P. Treitz, M. Wulder, B. St-Onge, and M. Flood, “LiDAR remote sensing of forest structure,” Prog. Phys. Geogr. 27(1), 88–106 (2003).
[Crossref]

2002 (1)

R. B. Myneni, S. Hoffman, Y. Knyazikhin, J. L. Privette, J. Glassy, Y. Tian, Y. Wang, X. Song, Y. Zhang, G. R. Smith, A. Lotsch, M. Friedl, J. T. Morisette, P. Votava, R. R. Nemani, and S. W. Running, “Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data,” Remote Sens. Environ. 83(1–2), 214–231 (2002).
[Crossref]

2001 (1)

K. C. Slatton, M. M. Crawford, and B. L. Evans, “Fusing interferometric radar and laser altimeter data to estimate surface topography and vegetation heights,” IEEE Trans. Geosci. Rem. Sens. 39(11), 2470–2482 (2001).
[Crossref]

2000 (1)

P. Axelsson, “DEM generation from laser scanner data using adaptive tin models,” Int. Arch. Photogramm. Remote Sens. 33, 111–118 (2000).

1999 (3)

S. T. Gower, C. J. Kucharik, and J. M. Norman, “Direct and Indirect Estimation of Leaf Area Index, fAPAR, and Net Primary Production of Terrestrial Ecosystems,” Remote Sens. Environ. 70(1), 29–51 (1999).
[Crossref]

M. A. Lefsky, W. B. Cohen, S. A. Acker, G. G. Parker, T. A. Spies, and D. Harding, “LiDAR remote sensing of the canopy structure and biophysical properties of douglas-fir western Hemlock forests,” Remote Sens. Environ. 70(3), 339–361 (1999).
[Crossref]

J. E. Means, S. A. Acker, D. J. Harding, J. B. Blair, M. A. Lefsky, W. B. Cohen, M. E. Harmon, and W. A. McKee, “Use of large-footprint scanning airborne LiDAR to estimate forest stand characteristics in the western Cascades of Oregon,” Remote Sens. Environ. 67(3), 298–308 (1999).
[Crossref]

1998 (1)

D. Casanova, G. F. Epema, and J. Goudriaan, “Monitoring rice reflectance at field level for estimating biomass and LAI,” Field Crops Res. 55(1–2), 83–92 (1998).
[Crossref]

1996 (1)

P. J. Sellers, C. J. Tucker, G. J. Collatz, S. O. Los, C. O. Justice, D. A. Dazlich, and D. A. Randall, “A revised land surface parameterization (SiB2) for atmospheric GCMS. part II: the generation of global fields of terrestrial biophysical parameters from satellite data,” J. Clim. 9(4), 706–737 (1996).
[Crossref]

1995 (1)

J.-L. Roujean and F.-M. Breon, “Estimating PAR absorbed by vegetation from bidirectional reflectance measurements,” Remote Sens. Environ. 51(3), 375–384 (1995).
[Crossref]

1992 (2)

C. L. Wiegand, S. J. Maas, J. K. Aase, J. L. Hatfield, P. J. Pinter, R. D. Jackson, E. T. Kanemasu, and R. L. Lapitan, “Multisite analyses of spectral-biophysical data for wheat,” Remote Sens. Environ. 42(1), 1–21 (1992).
[Crossref]

C. S. T. Daughtry, K. P. Gallo, S. N. Goward, S. D. Prince, and W. P. Kustas, “Spectral estimates of absorbed radiation and phytomass production in corn and soybean canopies,” Remote Sens. Environ. 39(2), 141–152 (1992).
[Crossref]

1991 (1)

F. Baret and G. Guyot, “Potentials and limits of vegetation indices for LAI and APAR assessment,” Remote Sens. Environ. 35(2–3), 161–173 (1991).
[Crossref]

1953 (1)

M. Monsi and T. Saeki, “U¨ ber den Lichtfaktor in den Pflanzengesellschaften undseine Bedeutung fu¨ r die Stoffproduktion,” Jap. J. Bot. 14, 22–52 (1953).

Aase, J. K.

C. L. Wiegand, S. J. Maas, J. K. Aase, J. L. Hatfield, P. J. Pinter, R. D. Jackson, E. T. Kanemasu, and R. L. Lapitan, “Multisite analyses of spectral-biophysical data for wheat,” Remote Sens. Environ. 42(1), 1–21 (1992).
[Crossref]

Acker, S. A.

M. A. Lefsky, A. T. Hudak, W. B. Cohen, and S. A. Acker, “Geographic variability in lidar predictions of forest stand structure in the Pacific Northwest,” Remote Sens. Environ. 95(4), 532–548 (2005).
[Crossref]

M. A. Lefsky, W. B. Cohen, S. A. Acker, G. G. Parker, T. A. Spies, and D. Harding, “LiDAR remote sensing of the canopy structure and biophysical properties of douglas-fir western Hemlock forests,” Remote Sens. Environ. 70(3), 339–361 (1999).
[Crossref]

J. E. Means, S. A. Acker, D. J. Harding, J. B. Blair, M. A. Lefsky, W. B. Cohen, M. E. Harmon, and W. A. McKee, “Use of large-footprint scanning airborne LiDAR to estimate forest stand characteristics in the western Cascades of Oregon,” Remote Sens. Environ. 67(3), 298–308 (1999).
[Crossref]

Adiku, S.

Q. Wang, S. Adiku, J. Tenhunen, and A. Granier, “On the relationship of NDVI with leaf area index in a deciduous forest site,” Remote Sens. Environ. 94(2), 244–255 (2005).
[Crossref]

Ahl, D. E.

S. P. Serbin, D. E. Ahl, and S. T. Gower, “Spatial and temporal validation of the MODIS LAI and FPAR products across a boreal forest wildfire chronosequence,” Remote Sens. Environ. 133(0), 71–84 (2013).
[Crossref]

Allgöwer, B.

B. Koetz, G. Sun, F. Morsdorf, K. J. Ranson, M. Kneubühler, K. Itten, and B. Allgöwer, “Fusion of imaging spectrometer and LIDAR data over combined radiative transfer models for forest canopy characterization,” Remote Sens. Environ. 106(4), 449–459 (2007).
[Crossref]

F. Morsdorf, B. Kötz, E. Meier, K. I. Itten, and B. Allgöwer, “Estimation of LAI and fractional cover from small footprint airborne laser scanning data based on gap fraction,” Remote Sens. Environ. 104(1), 50–61 (2006).
[Crossref]

Anderson, J.

F. Chen, K. T. Weber, J. Anderson, and B. Gokhale, “Comparison of MODIS fPAR products with Landsat-5 TM-derived fPAR over semiarid Rangelands of Idaho,” GISci. Remote Sens. 47(3), 360–378 (2010).

Anderson, R. S.

B. D. Cook, P. V. Bolstad, E. Næsset, R. S. Anderson, S. Garrigues, J. T. Morisette, J. Nickeson, and K. J. Davis, “Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations,” Remote Sens. Environ. 113(11), 2366–2379 (2009).
[Crossref]

Atkinson, P. M.

K. W. Todd, F. Csillag, and P. M. Atkinson, “Three-dimensional mapping of light transmittance and foliage distribution using LiDAR,” Can. J. Rem. Sens. 29(5), 544–555 (2003).
[Crossref]

Axelsson, P.

P. Axelsson, “DEM generation from laser scanner data using adaptive tin models,” Int. Arch. Photogramm. Remote Sens. 33, 111–118 (2000).

Ban, Y.

Baret, F.

F. Baret and G. Guyot, “Potentials and limits of vegetation indices for LAI and APAR assessment,” Remote Sens. Environ. 35(2–3), 161–173 (1991).
[Crossref]

Barr, A.

L. Chasmer, C. Hopkinson, P. Treitz, H. McCaughey, A. Barr, and A. Black, “A liDAR-based hierarchical approach for assessing MODIS fPAR,” Remote Sens. Environ. 112(12), 4344–4357 (2008).
[Crossref]

Belluco, E.

C. Wang, M. Menenti, M. Stoll, A. Feola, E. Belluco, and M. Marani, “Separation of ground and low vegetation signatures in LiDAR measurements of salt-marsh environments,” IEEE Trans. Geosci. Rem. Sens. 47(7), 2014–2023 (2009).
[Crossref]

Black, A.

L. Chasmer, C. Hopkinson, P. Treitz, H. McCaughey, A. Barr, and A. Black, “A liDAR-based hierarchical approach for assessing MODIS fPAR,” Remote Sens. Environ. 112(12), 4344–4357 (2008).
[Crossref]

Blair, J. B.

J. E. Means, S. A. Acker, D. J. Harding, J. B. Blair, M. A. Lefsky, W. B. Cohen, M. E. Harmon, and W. A. McKee, “Use of large-footprint scanning airborne LiDAR to estimate forest stand characteristics in the western Cascades of Oregon,” Remote Sens. Environ. 67(3), 298–308 (1999).
[Crossref]

Bolstad, P. V.

B. D. Cook, P. V. Bolstad, E. Næsset, R. S. Anderson, S. Garrigues, J. T. Morisette, J. Nickeson, and K. J. Davis, “Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations,” Remote Sens. Environ. 113(11), 2366–2379 (2009).
[Crossref]

Breon, F.-M.

J.-L. Roujean and F.-M. Breon, “Estimating PAR absorbed by vegetation from bidirectional reflectance measurements,” Remote Sens. Environ. 51(3), 375–384 (1995).
[Crossref]

Bright, B. C.

B. C. Bright, J. A. Hicke, and A. T. Hudak, “Estimating aboveground carbon stocks of a forest affected by mountain pine beetle in Idaho using lidar and multispectral imagery,” Remote Sens. Environ. 124, 270–281 (2012).
[Crossref]

Brovelli, M. A.

M. A. Brovelli, M. Crespi, F. Fratarcangeli, F. Giannone, and E. Realini, “Accuracy assessment of high resolution satellite imagery orientation by leave-one-out method,” ISPRS J. Photogramm. Remote Sens. 63(4), 427–440 (2008).
[Crossref]

Bruzzone, L.

M. Dalponte, L. Bruzzone, and D. Gianelle, “Fusion of hyperspectral and LiDAR remote sensing data for classification of complex forest areas,” IEEE Trans. Geosci. Rem. Sens. 46(5), 1416–1427 (2008).
[Crossref]

Buermann, W.

N. V. Shabanov, Y. Wang, W. Buermann, J. Dong, S. Hoffman, G. R. Smith, Y. Tian, Y. Knyazikhin, and R. B. Myneni, “Effect of foliage spatial heterogeneity in the MODIS LAI and FPAR algorithm over broadleaf forests,” Remote Sens. Environ. 85(4), 410–423 (2003).
[Crossref]

Casanova, D.

D. Casanova, G. F. Epema, and J. Goudriaan, “Monitoring rice reflectance at field level for estimating biomass and LAI,” Field Crops Res. 55(1–2), 83–92 (1998).
[Crossref]

Castillejo-González, I. L.

F. J. Mesas-Carrascosa, I. L. Castillejo-González, M. S. de la Orden, and A. G.-F. Porras, “Combining LiDAR intensity with aerial camera data to discriminate agricultural land uses,” Comput. Electron. Agric. 84(0), 36–46 (2012).
[Crossref]

Chasmer, L.

C. Hopkinson and L. Chasmer, “Testing LiDAR models of fractional cover across multiple forest ecozones,” Remote Sens. Environ. 113(1), 275–288 (2009).
[Crossref]

L. Chasmer, C. Hopkinson, P. Treitz, H. McCaughey, A. Barr, and A. Black, “A liDAR-based hierarchical approach for assessing MODIS fPAR,” Remote Sens. Environ. 112(12), 4344–4357 (2008).
[Crossref]

Chen, D.

D. Peng, B. Zhang, L. Liu, D. Chen, H. Fang, and Y. Hu, “Seasonal dynamic pattern analysis on global FPAR derived from AVHRR GIMMS NDVI,” Int. J. Digit. Earth 5(5), 439–455 (2012).
[Crossref]

Chen, F.

F. Chen, K. T. Weber, J. Anderson, and B. Gokhale, “Comparison of MODIS fPAR products with Landsat-5 TM-derived fPAR over semiarid Rangelands of Idaho,” GISci. Remote Sens. 47(3), 360–378 (2010).

Chen, J. M.

J. M. Chen, J. Liu, S. G. Leblanc, R. Lacaze, and J.-L. Roujean, “Multi-angular optical remote sensing for assessing vegetation structure and carbon absorption,” Remote Sens. Environ. 84(4), 516–525 (2003).
[Crossref]

Chen, Y.

Chuvieco, E.

M. García, D. Riaño, E. Chuvieco, J. Salas, and F. M. Danson, “Multispectral and LiDAR data fusion for fuel type mapping using Support Vector Machine and decision rules,” Remote Sens. Environ. 115(6), 1369–1379 (2011).
[Crossref]

M. García, D. Riaño, E. Chuvieco, and F. M. Danson, “Estimating biomass carbon stocks for a Mediterranean forest in central Spain using LiDAR height and intensity data,” Remote Sens. Environ. 114(4), 816–830 (2010).
[Crossref]

D. Riaño, F. Valladares, S. Condés, and E. Chuvieco, “Estimation of leaf area index and covered ground from airborne laser scanner (LiDAR) in two contrasting forests,” Agric. For. Meteorol. 124(3–4), 269–275 (2004).
[Crossref]

Cohen, W. B.

M. A. Lefsky, A. T. Hudak, W. B. Cohen, and S. A. Acker, “Geographic variability in lidar predictions of forest stand structure in the Pacific Northwest,” Remote Sens. Environ. 95(4), 532–548 (2005).
[Crossref]

J. E. Means, S. A. Acker, D. J. Harding, J. B. Blair, M. A. Lefsky, W. B. Cohen, M. E. Harmon, and W. A. McKee, “Use of large-footprint scanning airborne LiDAR to estimate forest stand characteristics in the western Cascades of Oregon,” Remote Sens. Environ. 67(3), 298–308 (1999).
[Crossref]

M. A. Lefsky, W. B. Cohen, S. A. Acker, G. G. Parker, T. A. Spies, and D. Harding, “LiDAR remote sensing of the canopy structure and biophysical properties of douglas-fir western Hemlock forests,” Remote Sens. Environ. 70(3), 339–361 (1999).
[Crossref]

Collatz, G. J.

P. J. Sellers, C. J. Tucker, G. J. Collatz, S. O. Los, C. O. Justice, D. A. Dazlich, and D. A. Randall, “A revised land surface parameterization (SiB2) for atmospheric GCMS. part II: the generation of global fields of terrestrial biophysical parameters from satellite data,” J. Clim. 9(4), 706–737 (1996).
[Crossref]

Condés, S.

D. Riaño, F. Valladares, S. Condés, and E. Chuvieco, “Estimation of leaf area index and covered ground from airborne laser scanner (LiDAR) in two contrasting forests,” Agric. For. Meteorol. 124(3–4), 269–275 (2004).
[Crossref]

Cook, B. D.

B. D. Cook, P. V. Bolstad, E. Næsset, R. S. Anderson, S. Garrigues, J. T. Morisette, J. Nickeson, and K. J. Davis, “Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations,” Remote Sens. Environ. 113(11), 2366–2379 (2009).
[Crossref]

Coppin, P.

D. Van der Zande, J. Stuckens, W. W. Verstraeten, S. Mereu, B. Muys, and P. Coppin, “3D modeling of light interception in heterogeneous forest canopies using ground-based LiDAR data,” Int. J. Appl. Earth Obs. Geoinf. 13(5), 792–800 (2011).
[Crossref]

Crawford, M. M.

K. C. Slatton, M. M. Crawford, and B. L. Evans, “Fusing interferometric radar and laser altimeter data to estimate surface topography and vegetation heights,” IEEE Trans. Geosci. Rem. Sens. 39(11), 2470–2482 (2001).
[Crossref]

Crespi, M.

M. A. Brovelli, M. Crespi, F. Fratarcangeli, F. Giannone, and E. Realini, “Accuracy assessment of high resolution satellite imagery orientation by leave-one-out method,” ISPRS J. Photogramm. Remote Sens. 63(4), 427–440 (2008).
[Crossref]

Cropper, W. P.

H. Lee, K. C. Slatton, B. E. Roth, and W. P. Cropper, “Prediction of forest canopy light interception using three-dimensional airborne LiDAR data,” Int. J. Remote Sens. 30(1), 189–207 (2009).
[Crossref]

Csillag, F.

K. W. Todd, F. Csillag, and P. M. Atkinson, “Three-dimensional mapping of light transmittance and foliage distribution using LiDAR,” Can. J. Rem. Sens. 29(5), 544–555 (2003).
[Crossref]

Dalponte, M.

S. Tonolli, M. Dalponte, M. Neteler, M. Rodeghiero, L. Vescovo, and D. Gianelle, “Fusion of airborne LiDAR and satellite multispectral data for the estimation of timber volume in the Southern Alps,” Remote Sens. Environ. 115(10), 2486–2498 (2011).
[Crossref]

M. Dalponte, L. Bruzzone, and D. Gianelle, “Fusion of hyperspectral and LiDAR remote sensing data for classification of complex forest areas,” IEEE Trans. Geosci. Rem. Sens. 46(5), 1416–1427 (2008).
[Crossref]

Danson, F. M.

M. García, D. Riaño, E. Chuvieco, J. Salas, and F. M. Danson, “Multispectral and LiDAR data fusion for fuel type mapping using Support Vector Machine and decision rules,” Remote Sens. Environ. 115(6), 1369–1379 (2011).
[Crossref]

M. García, D. Riaño, E. Chuvieco, and F. M. Danson, “Estimating biomass carbon stocks for a Mediterranean forest in central Spain using LiDAR height and intensity data,” Remote Sens. Environ. 114(4), 816–830 (2010).
[Crossref]

Daughtry, C. S. T.

C. S. T. Daughtry, K. P. Gallo, S. N. Goward, S. D. Prince, and W. P. Kustas, “Spectral estimates of absorbed radiation and phytomass production in corn and soybean canopies,” Remote Sens. Environ. 39(2), 141–152 (1992).
[Crossref]

Davis, K. J.

B. D. Cook, P. V. Bolstad, E. Næsset, R. S. Anderson, S. Garrigues, J. T. Morisette, J. Nickeson, and K. J. Davis, “Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations,” Remote Sens. Environ. 113(11), 2366–2379 (2009).
[Crossref]

Dazlich, D. A.

P. J. Sellers, C. J. Tucker, G. J. Collatz, S. O. Los, C. O. Justice, D. A. Dazlich, and D. A. Randall, “A revised land surface parameterization (SiB2) for atmospheric GCMS. part II: the generation of global fields of terrestrial biophysical parameters from satellite data,” J. Clim. 9(4), 706–737 (1996).
[Crossref]

de la Orden, M. S.

F. J. Mesas-Carrascosa, I. L. Castillejo-González, M. S. de la Orden, and A. G.-F. Porras, “Combining LiDAR intensity with aerial camera data to discriminate agricultural land uses,” Comput. Electron. Agric. 84(0), 36–46 (2012).
[Crossref]

Deering, D. W.

D. Huang, Y. Knyazikhin, W. Wang, D. W. Deering, P. Stenberg, N. Shabanov, B. Tan, and R. B. Myneni, “Stochastic transport theory for investigating the three-dimensional canopy structure from space measurements,” Remote Sens. Environ. 112(1), 35–50 (2008).
[Crossref]

Dong, J.

N. V. Shabanov, Y. Wang, W. Buermann, J. Dong, S. Hoffman, G. R. Smith, Y. Tian, Y. Knyazikhin, and R. B. Myneni, “Effect of foliage spatial heterogeneity in the MODIS LAI and FPAR algorithm over broadleaf forests,” Remote Sens. Environ. 85(4), 410–423 (2003).
[Crossref]

Dupuy, S.

S. Dupuy, G. Lainé, J. Tassin, and J.-M. Sarrailh, “Characterization of the horizontal structure of the tropical forest canopy using object-based LiDAR and multispectral image analysis,” Int. J. Appl. Earth Obs. Geoinf. 25, 76–86 (2013).
[Crossref]

Epema, G. F.

D. Casanova, G. F. Epema, and J. Goudriaan, “Monitoring rice reflectance at field level for estimating biomass and LAI,” Field Crops Res. 55(1–2), 83–92 (1998).
[Crossref]

Erdody, T. L.

T. L. Erdody and L. M. Moskal, “Fusion of LiDAR and imagery for estimating forest canopy fuels,” Remote Sens. Environ. 114(4), 725–737 (2010).
[Crossref]

Evans, B. L.

K. C. Slatton, M. M. Crawford, and B. L. Evans, “Fusing interferometric radar and laser altimeter data to estimate surface topography and vegetation heights,” IEEE Trans. Geosci. Rem. Sens. 39(11), 2470–2482 (2001).
[Crossref]

Fang, H.

D. Peng, B. Zhang, L. Liu, D. Chen, H. Fang, and Y. Hu, “Seasonal dynamic pattern analysis on global FPAR derived from AVHRR GIMMS NDVI,” Int. J. Digit. Earth 5(5), 439–455 (2012).
[Crossref]

Fensholt, R.

R. Fensholt, I. Sandholt, and M. S. Rasmussen, “Evaluation of MODIS LAI, fAPAR and the relation between fAPAR and NDVI in a semi-arid environment using in situ measurements,” Remote Sens. Environ. 91(3–4), 490–507 (2004).
[Crossref]

Feola, A.

C. Wang, M. Menenti, M. Stoll, A. Feola, E. Belluco, and M. Marani, “Separation of ground and low vegetation signatures in LiDAR measurements of salt-marsh environments,” IEEE Trans. Geosci. Rem. Sens. 47(7), 2014–2023 (2009).
[Crossref]

Finch, D. A.

V. Thomas, D. A. Finch, J. H. McCaughey, T. Noland, L. Rich, and P. Treitz, “Spatial modelling of the fraction of photosynthetically active radiation absorbed by a boreal mixedwood forest using a LiDAR-hyperspectral approach,” Agric. For. Meteorol. 140(1–4), 287–307 (2006).
[Crossref]

Flood, M.

K. Lim, P. Treitz, M. Wulder, B. St-Onge, and M. Flood, “LiDAR remote sensing of forest structure,” Prog. Phys. Geogr. 27(1), 88–106 (2003).
[Crossref]

Fox, T. R.

A. Peduzzi, R. H. Wynne, T. R. Fox, R. F. Nelson, and V. A. Thomas, “Estimating leaf area index in intensively managed pine plantations using airborne laser scanner data,” For. Ecol. Manage. 270(0), 54–65 (2012).
[Crossref]

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G. Sun, K. J. Ranson, Z. Guo, Z. Zhang, P. Montesano, and D. Kimes, “Forest biomass mapping from lidar and radar synergies,” Remote Sens. Environ. 115(11), 2906–2916 (2011).
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B. D. Cook, P. V. Bolstad, E. Næsset, R. S. Anderson, S. Garrigues, J. T. Morisette, J. Nickeson, and K. J. Davis, “Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations,” Remote Sens. Environ. 113(11), 2366–2379 (2009).
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R. B. Myneni, S. Hoffman, Y. Knyazikhin, J. L. Privette, J. Glassy, Y. Tian, Y. Wang, X. Song, Y. Zhang, G. R. Smith, A. Lotsch, M. Friedl, J. T. Morisette, P. Votava, R. R. Nemani, and S. W. Running, “Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data,” Remote Sens. Environ. 83(1–2), 214–231 (2002).
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F. Morsdorf, C. Nichol, T. Malthus, and I. H. Woodhouse, “Assessing forest structural and physiological information content of multi-spectral LiDAR waveforms by radiative transfer modelling,” Remote Sens. Environ. 113(10), 2152–2163 (2009).
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B. Koetz, G. Sun, F. Morsdorf, K. J. Ranson, M. Kneubühler, K. Itten, and B. Allgöwer, “Fusion of imaging spectrometer and LIDAR data over combined radiative transfer models for forest canopy characterization,” Remote Sens. Environ. 106(4), 449–459 (2007).
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F. Morsdorf, B. Kötz, E. Meier, K. I. Itten, and B. Allgöwer, “Estimation of LAI and fractional cover from small footprint airborne laser scanning data based on gap fraction,” Remote Sens. Environ. 104(1), 50–61 (2006).
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T. L. Erdody and L. M. Moskal, “Fusion of LiDAR and imagery for estimating forest canopy fuels,” Remote Sens. Environ. 114(4), 725–737 (2010).
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J. J. Richardson, L. M. Moskal, and S.-H. Kim, “Modeling approaches to estimate effective leaf area index from aerial discrete-return LIDAR,” Agric. For. Meteorol. 149(6–7), 1152–1160 (2009).
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D. Van der Zande, J. Stuckens, W. W. Verstraeten, S. Mereu, B. Muys, and P. Coppin, “3D modeling of light interception in heterogeneous forest canopies using ground-based LiDAR data,” Int. J. Appl. Earth Obs. Geoinf. 13(5), 792–800 (2011).
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D. Huang, Y. Knyazikhin, W. Wang, D. W. Deering, P. Stenberg, N. Shabanov, B. Tan, and R. B. Myneni, “Stochastic transport theory for investigating the three-dimensional canopy structure from space measurements,” Remote Sens. Environ. 112(1), 35–50 (2008).
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N. V. Shabanov, Y. Wang, W. Buermann, J. Dong, S. Hoffman, G. R. Smith, Y. Tian, Y. Knyazikhin, and R. B. Myneni, “Effect of foliage spatial heterogeneity in the MODIS LAI and FPAR algorithm over broadleaf forests,” Remote Sens. Environ. 85(4), 410–423 (2003).
[Crossref]

R. B. Myneni, S. Hoffman, Y. Knyazikhin, J. L. Privette, J. Glassy, Y. Tian, Y. Wang, X. Song, Y. Zhang, G. R. Smith, A. Lotsch, M. Friedl, J. T. Morisette, P. Votava, R. R. Nemani, and S. W. Running, “Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data,” Remote Sens. Environ. 83(1–2), 214–231 (2002).
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E. Næsset, “Effects of different sensors, flying altitudes, and pulse repetition frequencies on forest canopy metrics and biophysical stand properties derived from small-footprint airborne laser data,” Remote Sens. Environ. 113(1), 148–159 (2009).
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B. D. Cook, P. V. Bolstad, E. Næsset, R. S. Anderson, S. Garrigues, J. T. Morisette, J. Nickeson, and K. J. Davis, “Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations,” Remote Sens. Environ. 113(11), 2366–2379 (2009).
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A. Peduzzi, R. H. Wynne, T. R. Fox, R. F. Nelson, and V. A. Thomas, “Estimating leaf area index in intensively managed pine plantations using airborne laser scanner data,” For. Ecol. Manage. 270(0), 54–65 (2012).
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S. C. Popescu, R. H. Wynne, and R. F. Nelson, “Measuring individual tree crown diameter with lidar and assessing its influence on estimating forest volume and biomass,” Can. J. Rem. Sens. 29(5), 564–577 (2003).
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R. B. Myneni, S. Hoffman, Y. Knyazikhin, J. L. Privette, J. Glassy, Y. Tian, Y. Wang, X. Song, Y. Zhang, G. R. Smith, A. Lotsch, M. Friedl, J. T. Morisette, P. Votava, R. R. Nemani, and S. W. Running, “Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data,” Remote Sens. Environ. 83(1–2), 214–231 (2002).
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S. Tonolli, M. Dalponte, M. Neteler, M. Rodeghiero, L. Vescovo, and D. Gianelle, “Fusion of airborne LiDAR and satellite multispectral data for the estimation of timber volume in the Southern Alps,” Remote Sens. Environ. 115(10), 2486–2498 (2011).
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Nichol, C.

F. Morsdorf, C. Nichol, T. Malthus, and I. H. Woodhouse, “Assessing forest structural and physiological information content of multi-spectral LiDAR waveforms by radiative transfer modelling,” Remote Sens. Environ. 113(10), 2152–2163 (2009).
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B. D. Cook, P. V. Bolstad, E. Næsset, R. S. Anderson, S. Garrigues, J. T. Morisette, J. Nickeson, and K. J. Davis, “Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations,” Remote Sens. Environ. 113(11), 2366–2379 (2009).
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I. McCallum, W. Wagner, C. Schmullius, A. Shvidenko, M. Obersteiner, S. Fritz, and S. Nilsson, “Comparison of four global FAPAR datasets over Northern Eurasia for the year 2000,” Remote Sens. Environ. 114(5), 941–949 (2010).
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V. Thomas, D. A. Finch, J. H. McCaughey, T. Noland, L. Rich, and P. Treitz, “Spatial modelling of the fraction of photosynthetically active radiation absorbed by a boreal mixedwood forest using a LiDAR-hyperspectral approach,” Agric. For. Meteorol. 140(1–4), 287–307 (2006).
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A. Peduzzi, R. H. Wynne, T. R. Fox, R. F. Nelson, and V. A. Thomas, “Estimating leaf area index in intensively managed pine plantations using airborne laser scanner data,” For. Ecol. Manage. 270(0), 54–65 (2012).
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K. Zhao and S. Popescu, “Lidar-based mapping of leaf area index and its use for validating GLOBCARBON satellite LAI product in a temperate forest of the southern USA,” Remote Sens. Environ. 113(8), 1628–1645 (2009).
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S. C. Popescu, R. H. Wynne, and J. A. Scrivani, “Fusion of small-footprint LiDAR and multispectral data to estimate plot-level volume and biomass in deciduous and pine forests in Virginia, USA,” For. Sci. 50(4), 551–565 (2004).

S. C. Popescu, R. H. Wynne, and R. F. Nelson, “Measuring individual tree crown diameter with lidar and assessing its influence on estimating forest volume and biomass,” Can. J. Rem. Sens. 29(5), 564–577 (2003).
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F. J. Mesas-Carrascosa, I. L. Castillejo-González, M. S. de la Orden, and A. G.-F. Porras, “Combining LiDAR intensity with aerial camera data to discriminate agricultural land uses,” Comput. Electron. Agric. 84(0), 36–46 (2012).
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R. B. Myneni, S. Hoffman, Y. Knyazikhin, J. L. Privette, J. Glassy, Y. Tian, Y. Wang, X. Song, Y. Zhang, G. R. Smith, A. Lotsch, M. Friedl, J. T. Morisette, P. Votava, R. R. Nemani, and S. W. Running, “Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data,” Remote Sens. Environ. 83(1–2), 214–231 (2002).
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Ranson, K. J.

G. Sun, K. J. Ranson, Z. Guo, Z. Zhang, P. Montesano, and D. Kimes, “Forest biomass mapping from lidar and radar synergies,” Remote Sens. Environ. 115(11), 2906–2916 (2011).
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B. Koetz, G. Sun, F. Morsdorf, K. J. Ranson, M. Kneubühler, K. Itten, and B. Allgöwer, “Fusion of imaging spectrometer and LIDAR data over combined radiative transfer models for forest canopy characterization,” Remote Sens. Environ. 106(4), 449–459 (2007).
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R. Fensholt, I. Sandholt, and M. S. Rasmussen, “Evaluation of MODIS LAI, fAPAR and the relation between fAPAR and NDVI in a semi-arid environment using in situ measurements,” Remote Sens. Environ. 91(3–4), 490–507 (2004).
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M. García, D. Riaño, E. Chuvieco, and F. M. Danson, “Estimating biomass carbon stocks for a Mediterranean forest in central Spain using LiDAR height and intensity data,” Remote Sens. Environ. 114(4), 816–830 (2010).
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D. Riaño, F. Valladares, S. Condés, and E. Chuvieco, “Estimation of leaf area index and covered ground from airborne laser scanner (LiDAR) in two contrasting forests,” Agric. For. Meteorol. 124(3–4), 269–275 (2004).
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V. Thomas, D. A. Finch, J. H. McCaughey, T. Noland, L. Rich, and P. Treitz, “Spatial modelling of the fraction of photosynthetically active radiation absorbed by a boreal mixedwood forest using a LiDAR-hyperspectral approach,” Agric. For. Meteorol. 140(1–4), 287–307 (2006).
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Richardson, J. J.

J. J. Richardson, L. M. Moskal, and S.-H. Kim, “Modeling approaches to estimate effective leaf area index from aerial discrete-return LIDAR,” Agric. For. Meteorol. 149(6–7), 1152–1160 (2009).
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Rodeghiero, M.

S. Tonolli, M. Dalponte, M. Neteler, M. Rodeghiero, L. Vescovo, and D. Gianelle, “Fusion of airborne LiDAR and satellite multispectral data for the estimation of timber volume in the Southern Alps,” Remote Sens. Environ. 115(10), 2486–2498 (2011).
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L. Ronggao, L. Shunlin, H. Honglin, L. Jiyuan, and Z. Tao, “Mapping incident photosynthetically active radiation from MODIS data over China,” Remote Sens. Environ. 112(3), 998–1009 (2008).
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H. Lee, K. C. Slatton, B. E. Roth, and W. P. Cropper, “Prediction of forest canopy light interception using three-dimensional airborne LiDAR data,” Int. J. Remote Sens. 30(1), 189–207 (2009).
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R. B. Myneni, S. Hoffman, Y. Knyazikhin, J. L. Privette, J. Glassy, Y. Tian, Y. Wang, X. Song, Y. Zhang, G. R. Smith, A. Lotsch, M. Friedl, J. T. Morisette, P. Votava, R. R. Nemani, and S. W. Running, “Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data,” Remote Sens. Environ. 83(1–2), 214–231 (2002).
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M. Monsi and T. Saeki, “U¨ ber den Lichtfaktor in den Pflanzengesellschaften undseine Bedeutung fu¨ r die Stoffproduktion,” Jap. J. Bot. 14, 22–52 (1953).

Salas, J.

M. García, D. Riaño, E. Chuvieco, J. Salas, and F. M. Danson, “Multispectral and LiDAR data fusion for fuel type mapping using Support Vector Machine and decision rules,” Remote Sens. Environ. 115(6), 1369–1379 (2011).
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F. Samadzadegan, F. T. Mahmoudi, and T. Schenk, “Information fusion of Lidar range and intensity data for automatic building recognition,” Int. J. Image Data Fusion 2(1), 37–60 (2011).
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Sandholt, I.

R. Fensholt, I. Sandholt, and M. S. Rasmussen, “Evaluation of MODIS LAI, fAPAR and the relation between fAPAR and NDVI in a semi-arid environment using in situ measurements,” Remote Sens. Environ. 91(3–4), 490–507 (2004).
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Sarrailh, J.-M.

S. Dupuy, G. Lainé, J. Tassin, and J.-M. Sarrailh, “Characterization of the horizontal structure of the tropical forest canopy using object-based LiDAR and multispectral image analysis,” Int. J. Appl. Earth Obs. Geoinf. 25, 76–86 (2013).
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F. Samadzadegan, F. T. Mahmoudi, and T. Schenk, “Information fusion of Lidar range and intensity data for automatic building recognition,” Int. J. Image Data Fusion 2(1), 37–60 (2011).
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I. McCallum, W. Wagner, C. Schmullius, A. Shvidenko, M. Obersteiner, S. Fritz, and S. Nilsson, “Comparison of four global FAPAR datasets over Northern Eurasia for the year 2000,” Remote Sens. Environ. 114(5), 941–949 (2010).
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Scrivani, J. A.

S. C. Popescu, R. H. Wynne, and J. A. Scrivani, “Fusion of small-footprint LiDAR and multispectral data to estimate plot-level volume and biomass in deciduous and pine forests in Virginia, USA,” For. Sci. 50(4), 551–565 (2004).

Sellers, P. J.

P. J. Sellers, C. J. Tucker, G. J. Collatz, S. O. Los, C. O. Justice, D. A. Dazlich, and D. A. Randall, “A revised land surface parameterization (SiB2) for atmospheric GCMS. part II: the generation of global fields of terrestrial biophysical parameters from satellite data,” J. Clim. 9(4), 706–737 (1996).
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S. P. Serbin, D. E. Ahl, and S. T. Gower, “Spatial and temporal validation of the MODIS LAI and FPAR products across a boreal forest wildfire chronosequence,” Remote Sens. Environ. 133(0), 71–84 (2013).
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Shabanov, N.

D. Huang, Y. Knyazikhin, W. Wang, D. W. Deering, P. Stenberg, N. Shabanov, B. Tan, and R. B. Myneni, “Stochastic transport theory for investigating the three-dimensional canopy structure from space measurements,” Remote Sens. Environ. 112(1), 35–50 (2008).
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Shabanov, N. V.

N. V. Shabanov, Y. Wang, W. Buermann, J. Dong, S. Hoffman, G. R. Smith, Y. Tian, Y. Knyazikhin, and R. B. Myneni, “Effect of foliage spatial heterogeneity in the MODIS LAI and FPAR algorithm over broadleaf forests,” Remote Sens. Environ. 85(4), 410–423 (2003).
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Shunlin, L.

L. Ronggao, L. Shunlin, H. Honglin, L. Jiyuan, and Z. Tao, “Mapping incident photosynthetically active radiation from MODIS data over China,” Remote Sens. Environ. 112(3), 998–1009 (2008).
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Shvidenko, A.

I. McCallum, W. Wagner, C. Schmullius, A. Shvidenko, M. Obersteiner, S. Fritz, and S. Nilsson, “Comparison of four global FAPAR datasets over Northern Eurasia for the year 2000,” Remote Sens. Environ. 114(5), 941–949 (2010).
[Crossref]

Slatton, K. C.

H. Lee, K. C. Slatton, B. E. Roth, and W. P. Cropper, “Prediction of forest canopy light interception using three-dimensional airborne LiDAR data,” Int. J. Remote Sens. 30(1), 189–207 (2009).
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N. V. Shabanov, Y. Wang, W. Buermann, J. Dong, S. Hoffman, G. R. Smith, Y. Tian, Y. Knyazikhin, and R. B. Myneni, “Effect of foliage spatial heterogeneity in the MODIS LAI and FPAR algorithm over broadleaf forests,” Remote Sens. Environ. 85(4), 410–423 (2003).
[Crossref]

R. B. Myneni, S. Hoffman, Y. Knyazikhin, J. L. Privette, J. Glassy, Y. Tian, Y. Wang, X. Song, Y. Zhang, G. R. Smith, A. Lotsch, M. Friedl, J. T. Morisette, P. Votava, R. R. Nemani, and S. W. Running, “Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data,” Remote Sens. Environ. 83(1–2), 214–231 (2002).
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R. B. Myneni, S. Hoffman, Y. Knyazikhin, J. L. Privette, J. Glassy, Y. Tian, Y. Wang, X. Song, Y. Zhang, G. R. Smith, A. Lotsch, M. Friedl, J. T. Morisette, P. Votava, R. R. Nemani, and S. W. Running, “Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data,” Remote Sens. Environ. 83(1–2), 214–231 (2002).
[Crossref]

Spies, T. A.

M. A. Lefsky, W. B. Cohen, S. A. Acker, G. G. Parker, T. A. Spies, and D. Harding, “LiDAR remote sensing of the canopy structure and biophysical properties of douglas-fir western Hemlock forests,” Remote Sens. Environ. 70(3), 339–361 (1999).
[Crossref]

Stenberg, P.

D. Huang, Y. Knyazikhin, W. Wang, D. W. Deering, P. Stenberg, N. Shabanov, B. Tan, and R. B. Myneni, “Stochastic transport theory for investigating the three-dimensional canopy structure from space measurements,” Remote Sens. Environ. 112(1), 35–50 (2008).
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D. Van der Zande, J. Stuckens, W. W. Verstraeten, S. Mereu, B. Muys, and P. Coppin, “3D modeling of light interception in heterogeneous forest canopies using ground-based LiDAR data,” Int. J. Appl. Earth Obs. Geoinf. 13(5), 792–800 (2011).
[Crossref]

Sun, G.

G. Sun, K. J. Ranson, Z. Guo, Z. Zhang, P. Montesano, and D. Kimes, “Forest biomass mapping from lidar and radar synergies,” Remote Sens. Environ. 115(11), 2906–2916 (2011).
[Crossref]

B. Koetz, G. Sun, F. Morsdorf, K. J. Ranson, M. Kneubühler, K. Itten, and B. Allgöwer, “Fusion of imaging spectrometer and LIDAR data over combined radiative transfer models for forest canopy characterization,” Remote Sens. Environ. 106(4), 449–459 (2007).
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Suomalainen, J.

Tan, B.

D. Huang, Y. Knyazikhin, W. Wang, D. W. Deering, P. Stenberg, N. Shabanov, B. Tan, and R. B. Myneni, “Stochastic transport theory for investigating the three-dimensional canopy structure from space measurements,” Remote Sens. Environ. 112(1), 35–50 (2008).
[Crossref]

Tao, Z.

L. Ronggao, L. Shunlin, H. Honglin, L. Jiyuan, and Z. Tao, “Mapping incident photosynthetically active radiation from MODIS data over China,” Remote Sens. Environ. 112(3), 998–1009 (2008).
[Crossref]

Tassin, J.

S. Dupuy, G. Lainé, J. Tassin, and J.-M. Sarrailh, “Characterization of the horizontal structure of the tropical forest canopy using object-based LiDAR and multispectral image analysis,” Int. J. Appl. Earth Obs. Geoinf. 25, 76–86 (2013).
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V. Thomas, D. A. Finch, J. H. McCaughey, T. Noland, L. Rich, and P. Treitz, “Spatial modelling of the fraction of photosynthetically active radiation absorbed by a boreal mixedwood forest using a LiDAR-hyperspectral approach,” Agric. For. Meteorol. 140(1–4), 287–307 (2006).
[Crossref]

Thomas, V. A.

A. Peduzzi, R. H. Wynne, T. R. Fox, R. F. Nelson, and V. A. Thomas, “Estimating leaf area index in intensively managed pine plantations using airborne laser scanner data,” For. Ecol. Manage. 270(0), 54–65 (2012).
[Crossref]

Tian, Y.

N. V. Shabanov, Y. Wang, W. Buermann, J. Dong, S. Hoffman, G. R. Smith, Y. Tian, Y. Knyazikhin, and R. B. Myneni, “Effect of foliage spatial heterogeneity in the MODIS LAI and FPAR algorithm over broadleaf forests,” Remote Sens. Environ. 85(4), 410–423 (2003).
[Crossref]

R. B. Myneni, S. Hoffman, Y. Knyazikhin, J. L. Privette, J. Glassy, Y. Tian, Y. Wang, X. Song, Y. Zhang, G. R. Smith, A. Lotsch, M. Friedl, J. T. Morisette, P. Votava, R. R. Nemani, and S. W. Running, “Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data,” Remote Sens. Environ. 83(1–2), 214–231 (2002).
[Crossref]

Todd, K. W.

K. W. Todd, F. Csillag, and P. M. Atkinson, “Three-dimensional mapping of light transmittance and foliage distribution using LiDAR,” Can. J. Rem. Sens. 29(5), 544–555 (2003).
[Crossref]

Tonolli, S.

S. Tonolli, M. Dalponte, M. Neteler, M. Rodeghiero, L. Vescovo, and D. Gianelle, “Fusion of airborne LiDAR and satellite multispectral data for the estimation of timber volume in the Southern Alps,” Remote Sens. Environ. 115(10), 2486–2498 (2011).
[Crossref]

Treitz, P.

L. Chasmer, C. Hopkinson, P. Treitz, H. McCaughey, A. Barr, and A. Black, “A liDAR-based hierarchical approach for assessing MODIS fPAR,” Remote Sens. Environ. 112(12), 4344–4357 (2008).
[Crossref]

V. Thomas, D. A. Finch, J. H. McCaughey, T. Noland, L. Rich, and P. Treitz, “Spatial modelling of the fraction of photosynthetically active radiation absorbed by a boreal mixedwood forest using a LiDAR-hyperspectral approach,” Agric. For. Meteorol. 140(1–4), 287–307 (2006).
[Crossref]

K. Lim, P. Treitz, M. Wulder, B. St-Onge, and M. Flood, “LiDAR remote sensing of forest structure,” Prog. Phys. Geogr. 27(1), 88–106 (2003).
[Crossref]

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P. J. Sellers, C. J. Tucker, G. J. Collatz, S. O. Los, C. O. Justice, D. A. Dazlich, and D. A. Randall, “A revised land surface parameterization (SiB2) for atmospheric GCMS. part II: the generation of global fields of terrestrial biophysical parameters from satellite data,” J. Clim. 9(4), 706–737 (1996).
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D. Riaño, F. Valladares, S. Condés, and E. Chuvieco, “Estimation of leaf area index and covered ground from airborne laser scanner (LiDAR) in two contrasting forests,” Agric. For. Meteorol. 124(3–4), 269–275 (2004).
[Crossref]

Van der Zande, D.

D. Van der Zande, J. Stuckens, W. W. Verstraeten, S. Mereu, B. Muys, and P. Coppin, “3D modeling of light interception in heterogeneous forest canopies using ground-based LiDAR data,” Int. J. Appl. Earth Obs. Geoinf. 13(5), 792–800 (2011).
[Crossref]

Verstraeten, W. W.

D. Van der Zande, J. Stuckens, W. W. Verstraeten, S. Mereu, B. Muys, and P. Coppin, “3D modeling of light interception in heterogeneous forest canopies using ground-based LiDAR data,” Int. J. Appl. Earth Obs. Geoinf. 13(5), 792–800 (2011).
[Crossref]

Vescovo, L.

S. Tonolli, M. Dalponte, M. Neteler, M. Rodeghiero, L. Vescovo, and D. Gianelle, “Fusion of airborne LiDAR and satellite multispectral data for the estimation of timber volume in the Southern Alps,” Remote Sens. Environ. 115(10), 2486–2498 (2011).
[Crossref]

Vierling, L. A.

J. L. R. Jensen, K. S. Humes, L. A. Vierling, and A. T. Hudak, “Discrete return LiDAR-based prediction of leaf area index in two conifer forests,” Remote Sens. Environ. 112(10), 3947–3957 (2008).
[Crossref]

Votava, P.

R. B. Myneni, S. Hoffman, Y. Knyazikhin, J. L. Privette, J. Glassy, Y. Tian, Y. Wang, X. Song, Y. Zhang, G. R. Smith, A. Lotsch, M. Friedl, J. T. Morisette, P. Votava, R. R. Nemani, and S. W. Running, “Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data,” Remote Sens. Environ. 83(1–2), 214–231 (2002).
[Crossref]

Vu, T. T.

Wagner, W.

I. McCallum, W. Wagner, C. Schmullius, A. Shvidenko, M. Obersteiner, S. Fritz, and S. Nilsson, “Comparison of four global FAPAR datasets over Northern Eurasia for the year 2000,” Remote Sens. Environ. 114(5), 941–949 (2010).
[Crossref]

Wang, C.

S. Luo, C. Wang, G. Li, and X. Xi, “Retrieving leaf area index using ICESat/GLAS full-waveform data,” Remote Sens. Lett. 4(8), 745–753 (2013).
[Crossref]

C. Wang, M. Menenti, M. Stoll, A. Feola, E. Belluco, and M. Marani, “Separation of ground and low vegetation signatures in LiDAR measurements of salt-marsh environments,” IEEE Trans. Geosci. Rem. Sens. 47(7), 2014–2023 (2009).
[Crossref]

Wang, Q.

Q. Wang, S. Adiku, J. Tenhunen, and A. Granier, “On the relationship of NDVI with leaf area index in a deciduous forest site,” Remote Sens. Environ. 94(2), 244–255 (2005).
[Crossref]

Wang, W.

D. Huang, Y. Knyazikhin, W. Wang, D. W. Deering, P. Stenberg, N. Shabanov, B. Tan, and R. B. Myneni, “Stochastic transport theory for investigating the three-dimensional canopy structure from space measurements,” Remote Sens. Environ. 112(1), 35–50 (2008).
[Crossref]

Wang, Y.

N. V. Shabanov, Y. Wang, W. Buermann, J. Dong, S. Hoffman, G. R. Smith, Y. Tian, Y. Knyazikhin, and R. B. Myneni, “Effect of foliage spatial heterogeneity in the MODIS LAI and FPAR algorithm over broadleaf forests,” Remote Sens. Environ. 85(4), 410–423 (2003).
[Crossref]

R. B. Myneni, S. Hoffman, Y. Knyazikhin, J. L. Privette, J. Glassy, Y. Tian, Y. Wang, X. Song, Y. Zhang, G. R. Smith, A. Lotsch, M. Friedl, J. T. Morisette, P. Votava, R. R. Nemani, and S. W. Running, “Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data,” Remote Sens. Environ. 83(1–2), 214–231 (2002).
[Crossref]

Weber, K. T.

F. Chen, K. T. Weber, J. Anderson, and B. Gokhale, “Comparison of MODIS fPAR products with Landsat-5 TM-derived fPAR over semiarid Rangelands of Idaho,” GISci. Remote Sens. 47(3), 360–378 (2010).

Wiegand, C. L.

C. L. Wiegand, S. J. Maas, J. K. Aase, J. L. Hatfield, P. J. Pinter, R. D. Jackson, E. T. Kanemasu, and R. L. Lapitan, “Multisite analyses of spectral-biophysical data for wheat,” Remote Sens. Environ. 42(1), 1–21 (1992).
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F. Morsdorf, C. Nichol, T. Malthus, and I. H. Woodhouse, “Assessing forest structural and physiological information content of multi-spectral LiDAR waveforms by radiative transfer modelling,” Remote Sens. Environ. 113(10), 2152–2163 (2009).
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Wulder, M.

K. Lim, P. Treitz, M. Wulder, B. St-Onge, and M. Flood, “LiDAR remote sensing of forest structure,” Prog. Phys. Geogr. 27(1), 88–106 (2003).
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A. Peduzzi, R. H. Wynne, T. R. Fox, R. F. Nelson, and V. A. Thomas, “Estimating leaf area index in intensively managed pine plantations using airborne laser scanner data,” For. Ecol. Manage. 270(0), 54–65 (2012).
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S. C. Popescu, R. H. Wynne, and J. A. Scrivani, “Fusion of small-footprint LiDAR and multispectral data to estimate plot-level volume and biomass in deciduous and pine forests in Virginia, USA,” For. Sci. 50(4), 551–565 (2004).

S. C. Popescu, R. H. Wynne, and R. F. Nelson, “Measuring individual tree crown diameter with lidar and assessing its influence on estimating forest volume and biomass,” Can. J. Rem. Sens. 29(5), 564–577 (2003).
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Xi, X.

S. Luo, C. Wang, G. Li, and X. Xi, “Retrieving leaf area index using ICESat/GLAS full-waveform data,” Remote Sens. Lett. 4(8), 745–753 (2013).
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Zhang, B.

D. Peng, B. Zhang, L. Liu, D. Chen, H. Fang, and Y. Hu, “Seasonal dynamic pattern analysis on global FPAR derived from AVHRR GIMMS NDVI,” Int. J. Digit. Earth 5(5), 439–455 (2012).
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Zhang, Y.

R. B. Myneni, S. Hoffman, Y. Knyazikhin, J. L. Privette, J. Glassy, Y. Tian, Y. Wang, X. Song, Y. Zhang, G. R. Smith, A. Lotsch, M. Friedl, J. T. Morisette, P. Votava, R. R. Nemani, and S. W. Running, “Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data,” Remote Sens. Environ. 83(1–2), 214–231 (2002).
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G. Sun, K. J. Ranson, Z. Guo, Z. Zhang, P. Montesano, and D. Kimes, “Forest biomass mapping from lidar and radar synergies,” Remote Sens. Environ. 115(11), 2906–2916 (2011).
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Zhao, K.

K. Zhao and S. Popescu, “Lidar-based mapping of leaf area index and its use for validating GLOBCARBON satellite LAI product in a temperate forest of the southern USA,” Remote Sens. Environ. 113(8), 1628–1645 (2009).
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J. J. Richardson, L. M. Moskal, and S.-H. Kim, “Modeling approaches to estimate effective leaf area index from aerial discrete-return LIDAR,” Agric. For. Meteorol. 149(6–7), 1152–1160 (2009).
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V. Thomas, D. A. Finch, J. H. McCaughey, T. Noland, L. Rich, and P. Treitz, “Spatial modelling of the fraction of photosynthetically active radiation absorbed by a boreal mixedwood forest using a LiDAR-hyperspectral approach,” Agric. For. Meteorol. 140(1–4), 287–307 (2006).
[Crossref]

D. Riaño, F. Valladares, S. Condés, and E. Chuvieco, “Estimation of leaf area index and covered ground from airborne laser scanner (LiDAR) in two contrasting forests,” Agric. For. Meteorol. 124(3–4), 269–275 (2004).
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[Crossref]

S. C. Popescu, R. H. Wynne, and R. F. Nelson, “Measuring individual tree crown diameter with lidar and assessing its influence on estimating forest volume and biomass,” Can. J. Rem. Sens. 29(5), 564–577 (2003).
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S. C. Popescu, R. H. Wynne, and J. A. Scrivani, “Fusion of small-footprint LiDAR and multispectral data to estimate plot-level volume and biomass in deciduous and pine forests in Virginia, USA,” For. Sci. 50(4), 551–565 (2004).

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F. Chen, K. T. Weber, J. Anderson, and B. Gokhale, “Comparison of MODIS fPAR products with Landsat-5 TM-derived fPAR over semiarid Rangelands of Idaho,” GISci. Remote Sens. 47(3), 360–378 (2010).

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D. Van der Zande, J. Stuckens, W. W. Verstraeten, S. Mereu, B. Muys, and P. Coppin, “3D modeling of light interception in heterogeneous forest canopies using ground-based LiDAR data,” Int. J. Appl. Earth Obs. Geoinf. 13(5), 792–800 (2011).
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Int. J. Digit. Earth (1)

D. Peng, B. Zhang, L. Liu, D. Chen, H. Fang, and Y. Hu, “Seasonal dynamic pattern analysis on global FPAR derived from AVHRR GIMMS NDVI,” Int. J. Digit. Earth 5(5), 439–455 (2012).
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K. Lim, P. Treitz, M. Wulder, B. St-Onge, and M. Flood, “LiDAR remote sensing of forest structure,” Prog. Phys. Geogr. 27(1), 88–106 (2003).
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D. Huang, Y. Knyazikhin, W. Wang, D. W. Deering, P. Stenberg, N. Shabanov, B. Tan, and R. B. Myneni, “Stochastic transport theory for investigating the three-dimensional canopy structure from space measurements,” Remote Sens. Environ. 112(1), 35–50 (2008).
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R. B. Myneni, S. Hoffman, Y. Knyazikhin, J. L. Privette, J. Glassy, Y. Tian, Y. Wang, X. Song, Y. Zhang, G. R. Smith, A. Lotsch, M. Friedl, J. T. Morisette, P. Votava, R. R. Nemani, and S. W. Running, “Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data,” Remote Sens. Environ. 83(1–2), 214–231 (2002).
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I. McCallum, W. Wagner, C. Schmullius, A. Shvidenko, M. Obersteiner, S. Fritz, and S. Nilsson, “Comparison of four global FAPAR datasets over Northern Eurasia for the year 2000,” Remote Sens. Environ. 114(5), 941–949 (2010).
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Q. Wang, S. Adiku, J. Tenhunen, and A. Granier, “On the relationship of NDVI with leaf area index in a deciduous forest site,” Remote Sens. Environ. 94(2), 244–255 (2005).
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S. P. Serbin, D. E. Ahl, and S. T. Gower, “Spatial and temporal validation of the MODIS LAI and FPAR products across a boreal forest wildfire chronosequence,” Remote Sens. Environ. 133(0), 71–84 (2013).
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L. Chasmer, C. Hopkinson, P. Treitz, H. McCaughey, A. Barr, and A. Black, “A liDAR-based hierarchical approach for assessing MODIS fPAR,” Remote Sens. Environ. 112(12), 4344–4357 (2008).
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R. Fensholt, I. Sandholt, and M. S. Rasmussen, “Evaluation of MODIS LAI, fAPAR and the relation between fAPAR and NDVI in a semi-arid environment using in situ measurements,” Remote Sens. Environ. 91(3–4), 490–507 (2004).
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N. V. Shabanov, Y. Wang, W. Buermann, J. Dong, S. Hoffman, G. R. Smith, Y. Tian, Y. Knyazikhin, and R. B. Myneni, “Effect of foliage spatial heterogeneity in the MODIS LAI and FPAR algorithm over broadleaf forests,” Remote Sens. Environ. 85(4), 410–423 (2003).
[Crossref]

G. Sun, K. J. Ranson, Z. Guo, Z. Zhang, P. Montesano, and D. Kimes, “Forest biomass mapping from lidar and radar synergies,” Remote Sens. Environ. 115(11), 2906–2916 (2011).
[Crossref]

K. Zhao and S. Popescu, “Lidar-based mapping of leaf area index and its use for validating GLOBCARBON satellite LAI product in a temperate forest of the southern USA,” Remote Sens. Environ. 113(8), 1628–1645 (2009).
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C. S. T. Daughtry, K. P. Gallo, S. N. Goward, S. D. Prince, and W. P. Kustas, “Spectral estimates of absorbed radiation and phytomass production in corn and soybean canopies,” Remote Sens. Environ. 39(2), 141–152 (1992).
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F. Morsdorf, B. Kötz, E. Meier, K. I. Itten, and B. Allgöwer, “Estimation of LAI and fractional cover from small footprint airborne laser scanning data based on gap fraction,” Remote Sens. Environ. 104(1), 50–61 (2006).
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J. L. R. Jensen, K. S. Humes, L. A. Vierling, and A. T. Hudak, “Discrete return LiDAR-based prediction of leaf area index in two conifer forests,” Remote Sens. Environ. 112(10), 3947–3957 (2008).
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F. Morsdorf, C. Nichol, T. Malthus, and I. H. Woodhouse, “Assessing forest structural and physiological information content of multi-spectral LiDAR waveforms by radiative transfer modelling,” Remote Sens. Environ. 113(10), 2152–2163 (2009).
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M. A. Lefsky, W. B. Cohen, S. A. Acker, G. G. Parker, T. A. Spies, and D. Harding, “LiDAR remote sensing of the canopy structure and biophysical properties of douglas-fir western Hemlock forests,” Remote Sens. Environ. 70(3), 339–361 (1999).
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S. Luo, C. Wang, G. Li, and X. Xi, “Retrieving leaf area index using ICESat/GLAS full-waveform data,” Remote Sens. Lett. 4(8), 745–753 (2013).
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Figures (4)

Fig. 1
Fig. 1 The location of study area. A, B, C, D, E and F are six sampling areas where FPAR was measured using the ground-based method.
Fig. 2
Fig. 2 Flow chart of LiDAR data processing and PFAR estimation.
Fig. 3
Fig. 3 (a) Scatterplot of the return-based LiDAR-derived fCover versus the field-measured FPAR and the corresponding regression model (R2 = 0.85, RMSE = 0.038, n = 25, p<0.001). (b) Scatterplot of the intensity-based LiDAR-derived fCover versus the field-measured FPAR and the corresponding regression model (R2 = 0.90, RMSE = 0.032, n = 25, p<0.001).
Fig. 4
Fig. 4 Scatterplot of the intensity-based LiDAR-predicted FPAR and the field-measured FPAR and the corresponding linear regression (R2 = 0.89, RMSE = 0.034, p<0.001, n = 15).

Tables (1)

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Table 1 Statistical Characteristics of Estimated FPARs with Different Sample Radii

Equations (8)

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F P A R = ( S R - S R i , min ) ( F P A R max - F P A R min ) S R i , max - S R i , min + F P A R min .
F P A R = 1 e c × L A I .
F P A R = ( P A R a d P A R a u ) ( P A R b d P A R b u ) P A R a d
f C o v e r = N canopy N total .
I normalized = I R 2 R s 2 cos α .
I canopy = k I g r o u n d .
y = a x + b
f C o v e r = N canopy N total = N canopy N canopy + k N ground

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