Abstract

Leaf area index (LAI) is a key parameter for the study of biogeochemical cycles in ecosystems. Remote sensing techniques have been widely used to estimate LAIs in a wide range of vegetation types. However, limited by the sensor detection capability, considerable fewer studies investigated the layered estimation of LAIs in the vertical direction, which can significantly affect the precision evaluation of vegetation biophysical and biochemical processes. This study tried to generate a kind of pseudo large footprint waveform from the small footprint full-waveform airborne LiDAR data by an aggregation approach. The layered distribution of canopy heights and LAIs were successfully retrieved based on the large footprint waveform data in an agricultural landscape of orchards with typical multi-layer vegetation covers. The Gaussian fitting was conducted on the normalized large footprint waveforms to identify the vertical positions for different vegetation layers. Then, the gap theory was applied to retrieve the layered LAIs. Statistically significant simple linear regression models were fitted between the LiDAR-retrieved and field-observed values for the canopy heights and LAIs in different layers. Satisfactory results were obtained with a root mean square error of 0.36 m for the overstorey canopy height (R2 = 0.82), 0.29 m for the understory canopy height (R2 = 0.76), 0.28 for overstorey LAI (R2 = 0.75), 0.40 for understory LAI (R2 = 0.64), and 0.38 for total LAI (R2 = 0.69), respectively. To conclude, estimating the layered LAIs in the multi-layer agriculture orchards from the pseudo large footprint waveforms is feasible and the estimation errors are acceptable, which will provide some new ideas and methods for the quantitative remote sensing with vegetation.

© 2016 Optical Society of America

Full Article  |  PDF Article
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References

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    [Crossref]
  2. N. J. J. Bréda, “Ground-based measurements of leaf area index: a review of methods, instruments and current controversies,” J. Exp. Bot. 54(392), 2403–2417 (2003).
    [Crossref] [PubMed]
  3. I. Jonckheere, S. Fleck, K. Nackaerts, B. Muys, P. Coppin, M. Weiss, and F. Baret, “Review of methods for in situ leaf area index determination,” Agric. For. Meteorol. 121(1-2), 19–35 (2004).
    [Crossref]
  4. S. Gao, Z. Niu, N. Huang, and X. Hou, “Estimating the Leaf Area Index, height and biomass of maize using HJ-1 and RADARSAT-2,” Int. J. Appl. Earth. Obs. 24, 1–8 (2013).
    [Crossref]
  5. A. Kross, H. McNairn, D. Lapen, M. Sunohara, and C. Champagne, “Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops,” Int. J. Appl. Earth. Obs. 34, 235–248 (2015).
    [Crossref]
  6. C. Y. Wu, Z. Niu, J. D. Wang, S. A. Gao, and W. J. Huang, “Predicting leaf area index in wheat using angular vegetation indices derived from in situ canopy measurements,” Can. J. Rem. Sens. 36(4), 301–312 (2010).
    [Crossref]
  7. Y. Qi, F. Li, Z. Liu, and G. Jin, “Impact of understory on overstorey leaf area index estimation from optical remote sensing in five forest types in northeastern China,” Agric. For. Meteorol. 198–199, 72–80 (2014).
    [Crossref]
  8. K. K. Singh, A. J. Davis, and R. K. Meentemeyer, “Detecting understory plant invasion in urban forests using LiDAR,” Int. J. Appl. Earth. Obs. 38, 267–279 (2015).
    [Crossref]
  9. 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]
  10. 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]
  11. W. Li, Z. Niu, C. Wang, W. Huang, H. Chen, S. Gao, D. Li, and S. Muhammad, “Combined Use of Airborne LiDAR and Satellite GF-1 Data to Estimate Leaf Area Index, Height, and Aboveground Biomass of Maize During Peak Growing Season,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(9), 4489–4501 (2015).
    [Crossref]
  12. S. Luo, C. Wang, X. Xi, and F. Pan, “Estimating FPAR of maize canopy using airborne discrete-return LiDAR data,” Opt. Express 22(5), 5106–5117 (2014).
    [Crossref] [PubMed]
  13. W. Li, Z. Niu, N. Huang, C. Wang, S. Gao, and C. Wu, “Airborne LiDAR technique for estimating biomass components of maize: A case study in Zhangye City, Northwest China,” Ecol. Indic. 57, 486–496 (2015).
    [Crossref]
  14. 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]
  15. S. Luo, C. Wang, F. Pan, X. Xi, G. Li, S. Nie, and S. Xia, “Estimation of wetland vegetation height and leaf area index using airborne laser scanning data,” Ecol. Indic. 48, 550–559 (2015).
    [Crossref]
  16. T. Hermosilla, N. C. Coops, L. A. Ruiz, and L. M. Moskal, “Deriving pseudo-vertical waveforms from small-footprint full-waveform LiDAR data,” Remote Sens. Lett. 5(4), 332–341 (2014).
    [Crossref]
  17. S. Gao, Z. Niu, G. Sun, D. Zhao, K. Jia, and Y. Qin, “Height Extraction of Maize Using Airborne Full-Waveform LIDAR Data and a Deconvolution Algorithm,” IEEE Geosci. Remote. 12(9), 1978–1982 (2015).
    [Crossref]
  18. 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]
  19. H. Tang, R. Dubayah, A. Swatantran, M. Hofton, S. Sheldon, D. B. Clark, and B. Blair, “Retrieval of vertical LAI profiles over tropical rain forests using waveform lidar at La Selva, Costa Rica,” Remote Sens. Environ. 124, 242–250 (2012).
    [Crossref]
  20. 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]
  21. S. Nie, C. Wang, P. Dong, and X. Xi, “Estimating leaf area index of maize using airborne full-waveform lidar data,” Remote Sens. Lett. 7(2), 111–120 (2016).
    [Crossref]
  22. L. A. Magruder, A. L. Neuenschwander, and S. P. Marmillion, “Lidar waveform stacking techniques for faint ground return extraction,” J. Appl. Remote Sens. 4(1), 043501 (2010).
    [Crossref]
  23. K. D. Fieber, I. J. Davenport, M. A. Tanase, J. M. Ferryman, R. J. Gurney, V. M. Becerra, J. P. Walker, and J. M. Hacker, “Validation of Canopy Height Profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment,” ISPRS J. Photogramm. Remote Sens. 104, 144–157 (2015).
    [Crossref]
  24. V. H. Duong, R. Lindenbergh, N. Pfeifer, and G. Vosselman, “Single and two epoch analysis of ICESat full waveform data over forested areas,” Int. J. Remote Sens. 29(5), 1453–1473 (2008).
    [Crossref]
  25. Y. Qin, S. Li, T. T. Vu, Z. Niu, and Y. Ban, “Synergistic application of geometric and radiometric features of LiDAR data for urban land cover mapping,” Opt. Express 23(11), 13761–13775 (2015).
    [Crossref] [PubMed]
  26. Y. Qin, W. Yao, T. Vu, S. Li, Z. Niu, and Y. Ban, “Characterizing Radiometric Attributes of Point Cloud Using a Normalized Reflective Factor Derived From Small Footprint LiDAR Waveform,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(2), 740–749 (2015).
    [Crossref]
  27. Y. Qin, T. T. Vu, and Y. F. Ban, “Toward an Optimal Algorithm for LiDAR Waveform Decomposition,” IEEE Geosci Remote Sens. 9(3), 482–486 (2012).
    [Crossref]
  28. W. Ni-Meister, D. L. B. Jupp, and R. Dubayah, “Modeling lidar waveforms in heterogeneous and discrete canopies,” IEEE Geosci Remote. 39(9), 1943–1958 (2001).
    [Crossref]
  29. D. J. Harding, M. A. Lefsky, G. G. Parker, and J. B. Blair, “Laser altimeter canopy height profiles - Methods and validation for closed-canopy, broadleaf forests,” Remote Sens. Environ. 76(3), 283–297 (2001).
    [Crossref]
  30. J. Armston, M. Disney, P. Lewis, P. Scarth, S. Phinn, R. Lucas, P. Bunting, and N. Goodwin, “Direct retrieval of canopy gap probability using airborne waveform lidar,” Remote Sens. Environ. 134, 24–38 (2013).
    [Crossref]
  31. C. Hopkinson, L. E. Chasmer, G. Sass, I. F. Creed, M. Sitar, W. Kalbfleisch, and P. Treitz, “Vegetation class dependent errors in lidar ground elevation and canopy height estimates in a boreal wetland environment,” Can. J. Rem. Sens. 31(2), 191–206 (2005).
    [Crossref]
  32. W. Li, Z. Niu, S. Gao, N. Huang, and H. Y. Chen, “Correlating the Horizontal and Vertical Distribution of LiDAR Point Clouds with Components of Biomass in a Picea crassifolia Forest,” Forests 5(8), 1910–1930 (2014).
    [Crossref]
  33. S. Solberg, “Mapping gap fraction, LAI and defoliation using various ALS penetration variables,” Int. J. Remote Sens. 31(5), 1227–1244 (2010).
    [Crossref]
  34. 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, 54–65 (2012).
    [Crossref]
  35. S. Martinuzzi, L. A. Vierling, W. A. Gould, M. J. Falkowski, J. S. Evans, A. T. Hudak, and K. T. Vierling, “Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability,” Remote Sens. Environ. 113(12), 2533–2546 (2009).
    [Crossref]
  36. W. Li, Z. Niu, G. Sun, S. Gao, and M. Wu, “Deriving backscatter reflective factors from 32-channel full-waveform LiDAR data for the estimation of leaf biochemical contents,” Opt. Express 24(5), 4771–4785 (2016).
    [Crossref]
  37. W. Li, G. Sun, Z. Niu, S. Gao, and H. Qiao, “Estimation of leaf biochemical content using a novel hyperspectral full-waveform LiDAR system,” Remote Sens. Lett. 5(8), 693–702 (2014).
    [Crossref]

2016 (2)

S. Nie, C. Wang, P. Dong, and X. Xi, “Estimating leaf area index of maize using airborne full-waveform lidar data,” Remote Sens. Lett. 7(2), 111–120 (2016).
[Crossref]

W. Li, Z. Niu, G. Sun, S. Gao, and M. Wu, “Deriving backscatter reflective factors from 32-channel full-waveform LiDAR data for the estimation of leaf biochemical contents,” Opt. Express 24(5), 4771–4785 (2016).
[Crossref]

2015 (9)

Y. Qin, S. Li, T. T. Vu, Z. Niu, and Y. Ban, “Synergistic application of geometric and radiometric features of LiDAR data for urban land cover mapping,” Opt. Express 23(11), 13761–13775 (2015).
[Crossref] [PubMed]

Y. Qin, W. Yao, T. Vu, S. Li, Z. Niu, and Y. Ban, “Characterizing Radiometric Attributes of Point Cloud Using a Normalized Reflective Factor Derived From Small Footprint LiDAR Waveform,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(2), 740–749 (2015).
[Crossref]

K. D. Fieber, I. J. Davenport, M. A. Tanase, J. M. Ferryman, R. J. Gurney, V. M. Becerra, J. P. Walker, and J. M. Hacker, “Validation of Canopy Height Profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment,” ISPRS J. Photogramm. Remote Sens. 104, 144–157 (2015).
[Crossref]

A. Kross, H. McNairn, D. Lapen, M. Sunohara, and C. Champagne, “Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops,” Int. J. Appl. Earth. Obs. 34, 235–248 (2015).
[Crossref]

K. K. Singh, A. J. Davis, and R. K. Meentemeyer, “Detecting understory plant invasion in urban forests using LiDAR,” Int. J. Appl. Earth. Obs. 38, 267–279 (2015).
[Crossref]

W. Li, Z. Niu, C. Wang, W. Huang, H. Chen, S. Gao, D. Li, and S. Muhammad, “Combined Use of Airborne LiDAR and Satellite GF-1 Data to Estimate Leaf Area Index, Height, and Aboveground Biomass of Maize During Peak Growing Season,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(9), 4489–4501 (2015).
[Crossref]

W. Li, Z. Niu, N. Huang, C. Wang, S. Gao, and C. Wu, “Airborne LiDAR technique for estimating biomass components of maize: A case study in Zhangye City, Northwest China,” Ecol. Indic. 57, 486–496 (2015).
[Crossref]

S. Luo, C. Wang, F. Pan, X. Xi, G. Li, S. Nie, and S. Xia, “Estimation of wetland vegetation height and leaf area index using airborne laser scanning data,” Ecol. Indic. 48, 550–559 (2015).
[Crossref]

S. Gao, Z. Niu, G. Sun, D. Zhao, K. Jia, and Y. Qin, “Height Extraction of Maize Using Airborne Full-Waveform LIDAR Data and a Deconvolution Algorithm,” IEEE Geosci. Remote. 12(9), 1978–1982 (2015).
[Crossref]

2014 (5)

T. Hermosilla, N. C. Coops, L. A. Ruiz, and L. M. Moskal, “Deriving pseudo-vertical waveforms from small-footprint full-waveform LiDAR data,” Remote Sens. Lett. 5(4), 332–341 (2014).
[Crossref]

S. Luo, C. Wang, X. Xi, and F. Pan, “Estimating FPAR of maize canopy using airborne discrete-return LiDAR data,” Opt. Express 22(5), 5106–5117 (2014).
[Crossref] [PubMed]

W. Li, Z. Niu, S. Gao, N. Huang, and H. Y. Chen, “Correlating the Horizontal and Vertical Distribution of LiDAR Point Clouds with Components of Biomass in a Picea crassifolia Forest,” Forests 5(8), 1910–1930 (2014).
[Crossref]

Y. Qi, F. Li, Z. Liu, and G. Jin, “Impact of understory on overstorey leaf area index estimation from optical remote sensing in five forest types in northeastern China,” Agric. For. Meteorol. 198–199, 72–80 (2014).
[Crossref]

W. Li, G. Sun, Z. Niu, S. Gao, and H. Qiao, “Estimation of leaf biochemical content using a novel hyperspectral full-waveform LiDAR system,” Remote Sens. Lett. 5(8), 693–702 (2014).
[Crossref]

2013 (3)

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]

J. Armston, M. Disney, P. Lewis, P. Scarth, S. Phinn, R. Lucas, P. Bunting, and N. Goodwin, “Direct retrieval of canopy gap probability using airborne waveform lidar,” Remote Sens. Environ. 134, 24–38 (2013).
[Crossref]

S. Gao, Z. Niu, N. Huang, and X. Hou, “Estimating the Leaf Area Index, height and biomass of maize using HJ-1 and RADARSAT-2,” Int. J. Appl. Earth. Obs. 24, 1–8 (2013).
[Crossref]

2012 (3)

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, 54–65 (2012).
[Crossref]

H. Tang, R. Dubayah, A. Swatantran, M. Hofton, S. Sheldon, D. B. Clark, and B. Blair, “Retrieval of vertical LAI profiles over tropical rain forests using waveform lidar at La Selva, Costa Rica,” Remote Sens. Environ. 124, 242–250 (2012).
[Crossref]

Y. Qin, T. T. Vu, and Y. F. Ban, “Toward an Optimal Algorithm for LiDAR Waveform Decomposition,” IEEE Geosci Remote Sens. 9(3), 482–486 (2012).
[Crossref]

2011 (1)

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]

2010 (3)

C. Y. Wu, Z. Niu, J. D. Wang, S. A. Gao, and W. J. Huang, “Predicting leaf area index in wheat using angular vegetation indices derived from in situ canopy measurements,” Can. J. Rem. Sens. 36(4), 301–312 (2010).
[Crossref]

L. A. Magruder, A. L. Neuenschwander, and S. P. Marmillion, “Lidar waveform stacking techniques for faint ground return extraction,” J. Appl. Remote Sens. 4(1), 043501 (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]

2009 (3)

S. Martinuzzi, L. A. Vierling, W. A. Gould, M. J. Falkowski, J. S. Evans, A. T. Hudak, and K. T. Vierling, “Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability,” Remote Sens. Environ. 113(12), 2533–2546 (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]

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]

2008 (1)

V. H. Duong, R. Lindenbergh, N. Pfeifer, and G. Vosselman, “Single and two epoch analysis of ICESat full waveform data over forested areas,” Int. J. Remote Sens. 29(5), 1453–1473 (2008).
[Crossref]

2005 (1)

C. Hopkinson, L. E. Chasmer, G. Sass, I. F. Creed, M. Sitar, W. Kalbfleisch, and P. Treitz, “Vegetation class dependent errors in lidar ground elevation and canopy height estimates in a boreal wetland environment,” Can. J. Rem. Sens. 31(2), 191–206 (2005).
[Crossref]

2004 (1)

I. Jonckheere, S. Fleck, K. Nackaerts, B. Muys, P. Coppin, M. Weiss, and F. Baret, “Review of methods for in situ leaf area index determination,” Agric. For. Meteorol. 121(1-2), 19–35 (2004).
[Crossref]

2003 (1)

N. J. J. Bréda, “Ground-based measurements of leaf area index: a review of methods, instruments and current controversies,” J. Exp. Bot. 54(392), 2403–2417 (2003).
[Crossref] [PubMed]

2001 (2)

W. Ni-Meister, D. L. B. Jupp, and R. Dubayah, “Modeling lidar waveforms in heterogeneous and discrete canopies,” IEEE Geosci Remote. 39(9), 1943–1958 (2001).
[Crossref]

D. J. Harding, M. A. Lefsky, G. G. Parker, and J. B. Blair, “Laser altimeter canopy height profiles - Methods and validation for closed-canopy, broadleaf forests,” Remote Sens. Environ. 76(3), 283–297 (2001).
[Crossref]

1999 (1)

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]

1992 (1)

J. M. Chen and T. A. Black, “Defining leaf area index for non-flat leaves,” Plant Cell Environ. 15(4), 421–429 (1992).
[Crossref]

Acker, S. 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]

Armston, J.

J. Armston, M. Disney, P. Lewis, P. Scarth, S. Phinn, R. Lucas, P. Bunting, and N. Goodwin, “Direct retrieval of canopy gap probability using airborne waveform lidar,” Remote Sens. Environ. 134, 24–38 (2013).
[Crossref]

Ban, Y.

Y. Qin, W. Yao, T. Vu, S. Li, Z. Niu, and Y. Ban, “Characterizing Radiometric Attributes of Point Cloud Using a Normalized Reflective Factor Derived From Small Footprint LiDAR Waveform,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(2), 740–749 (2015).
[Crossref]

Y. Qin, S. Li, T. T. Vu, Z. Niu, and Y. Ban, “Synergistic application of geometric and radiometric features of LiDAR data for urban land cover mapping,” Opt. Express 23(11), 13761–13775 (2015).
[Crossref] [PubMed]

Ban, Y. F.

Y. Qin, T. T. Vu, and Y. F. Ban, “Toward an Optimal Algorithm for LiDAR Waveform Decomposition,” IEEE Geosci Remote Sens. 9(3), 482–486 (2012).
[Crossref]

Baret, F.

I. Jonckheere, S. Fleck, K. Nackaerts, B. Muys, P. Coppin, M. Weiss, and F. Baret, “Review of methods for in situ leaf area index determination,” Agric. For. Meteorol. 121(1-2), 19–35 (2004).
[Crossref]

Becerra, V. M.

K. D. Fieber, I. J. Davenport, M. A. Tanase, J. M. Ferryman, R. J. Gurney, V. M. Becerra, J. P. Walker, and J. M. Hacker, “Validation of Canopy Height Profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment,” ISPRS J. Photogramm. Remote Sens. 104, 144–157 (2015).
[Crossref]

Black, T. A.

J. M. Chen and T. A. Black, “Defining leaf area index for non-flat leaves,” Plant Cell Environ. 15(4), 421–429 (1992).
[Crossref]

Blair, B.

H. Tang, R. Dubayah, A. Swatantran, M. Hofton, S. Sheldon, D. B. Clark, and B. Blair, “Retrieval of vertical LAI profiles over tropical rain forests using waveform lidar at La Selva, Costa Rica,” Remote Sens. Environ. 124, 242–250 (2012).
[Crossref]

Blair, J. B.

D. J. Harding, M. A. Lefsky, G. G. Parker, and J. B. Blair, “Laser altimeter canopy height profiles - Methods and validation for closed-canopy, broadleaf forests,” Remote Sens. Environ. 76(3), 283–297 (2001).
[Crossref]

Bréda, N. J. J.

N. J. J. Bréda, “Ground-based measurements of leaf area index: a review of methods, instruments and current controversies,” J. Exp. Bot. 54(392), 2403–2417 (2003).
[Crossref] [PubMed]

Bunting, P.

J. Armston, M. Disney, P. Lewis, P. Scarth, S. Phinn, R. Lucas, P. Bunting, and N. Goodwin, “Direct retrieval of canopy gap probability using airborne waveform lidar,” Remote Sens. Environ. 134, 24–38 (2013).
[Crossref]

Champagne, C.

A. Kross, H. McNairn, D. Lapen, M. Sunohara, and C. Champagne, “Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops,” Int. J. Appl. Earth. Obs. 34, 235–248 (2015).
[Crossref]

Chasmer, L. E.

C. Hopkinson, L. E. Chasmer, G. Sass, I. F. Creed, M. Sitar, W. Kalbfleisch, and P. Treitz, “Vegetation class dependent errors in lidar ground elevation and canopy height estimates in a boreal wetland environment,” Can. J. Rem. Sens. 31(2), 191–206 (2005).
[Crossref]

Chen, H.

W. Li, Z. Niu, C. Wang, W. Huang, H. Chen, S. Gao, D. Li, and S. Muhammad, “Combined Use of Airborne LiDAR and Satellite GF-1 Data to Estimate Leaf Area Index, Height, and Aboveground Biomass of Maize During Peak Growing Season,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(9), 4489–4501 (2015).
[Crossref]

Chen, H. Y.

W. Li, Z. Niu, S. Gao, N. Huang, and H. Y. Chen, “Correlating the Horizontal and Vertical Distribution of LiDAR Point Clouds with Components of Biomass in a Picea crassifolia Forest,” Forests 5(8), 1910–1930 (2014).
[Crossref]

Chen, J. M.

J. M. Chen and T. A. Black, “Defining leaf area index for non-flat leaves,” Plant Cell Environ. 15(4), 421–429 (1992).
[Crossref]

Clark, D. B.

H. Tang, R. Dubayah, A. Swatantran, M. Hofton, S. Sheldon, D. B. Clark, and B. Blair, “Retrieval of vertical LAI profiles over tropical rain forests using waveform lidar at La Selva, Costa Rica,” Remote Sens. Environ. 124, 242–250 (2012).
[Crossref]

Cohen, W. B.

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]

Coops, N. C.

T. Hermosilla, N. C. Coops, L. A. Ruiz, and L. M. Moskal, “Deriving pseudo-vertical waveforms from small-footprint full-waveform LiDAR data,” Remote Sens. Lett. 5(4), 332–341 (2014).
[Crossref]

Coppin, P.

I. Jonckheere, S. Fleck, K. Nackaerts, B. Muys, P. Coppin, M. Weiss, and F. Baret, “Review of methods for in situ leaf area index determination,” Agric. For. Meteorol. 121(1-2), 19–35 (2004).
[Crossref]

Creed, I. F.

C. Hopkinson, L. E. Chasmer, G. Sass, I. F. Creed, M. Sitar, W. Kalbfleisch, and P. Treitz, “Vegetation class dependent errors in lidar ground elevation and canopy height estimates in a boreal wetland environment,” Can. J. Rem. Sens. 31(2), 191–206 (2005).
[Crossref]

Davenport, I. J.

K. D. Fieber, I. J. Davenport, M. A. Tanase, J. M. Ferryman, R. J. Gurney, V. M. Becerra, J. P. Walker, and J. M. Hacker, “Validation of Canopy Height Profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment,” ISPRS J. Photogramm. Remote Sens. 104, 144–157 (2015).
[Crossref]

Davis, A. J.

K. K. Singh, A. J. Davis, and R. K. Meentemeyer, “Detecting understory plant invasion in urban forests using LiDAR,” Int. J. Appl. Earth. Obs. 38, 267–279 (2015).
[Crossref]

Disney, M.

J. Armston, M. Disney, P. Lewis, P. Scarth, S. Phinn, R. Lucas, P. Bunting, and N. Goodwin, “Direct retrieval of canopy gap probability using airborne waveform lidar,” Remote Sens. Environ. 134, 24–38 (2013).
[Crossref]

Dong, P.

S. Nie, C. Wang, P. Dong, and X. Xi, “Estimating leaf area index of maize using airborne full-waveform lidar data,” Remote Sens. Lett. 7(2), 111–120 (2016).
[Crossref]

Dubayah, R.

H. Tang, R. Dubayah, A. Swatantran, M. Hofton, S. Sheldon, D. B. Clark, and B. Blair, “Retrieval of vertical LAI profiles over tropical rain forests using waveform lidar at La Selva, Costa Rica,” Remote Sens. Environ. 124, 242–250 (2012).
[Crossref]

W. Ni-Meister, D. L. B. Jupp, and R. Dubayah, “Modeling lidar waveforms in heterogeneous and discrete canopies,” IEEE Geosci Remote. 39(9), 1943–1958 (2001).
[Crossref]

Duong, V. H.

V. H. Duong, R. Lindenbergh, N. Pfeifer, and G. Vosselman, “Single and two epoch analysis of ICESat full waveform data over forested areas,” Int. J. Remote Sens. 29(5), 1453–1473 (2008).
[Crossref]

Evans, J. S.

S. Martinuzzi, L. A. Vierling, W. A. Gould, M. J. Falkowski, J. S. Evans, A. T. Hudak, and K. T. Vierling, “Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability,” Remote Sens. Environ. 113(12), 2533–2546 (2009).
[Crossref]

Falkowski, M. J.

S. Martinuzzi, L. A. Vierling, W. A. Gould, M. J. Falkowski, J. S. Evans, A. T. Hudak, and K. T. Vierling, “Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability,” Remote Sens. Environ. 113(12), 2533–2546 (2009).
[Crossref]

Ferryman, J. M.

K. D. Fieber, I. J. Davenport, M. A. Tanase, J. M. Ferryman, R. J. Gurney, V. M. Becerra, J. P. Walker, and J. M. Hacker, “Validation of Canopy Height Profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment,” ISPRS J. Photogramm. Remote Sens. 104, 144–157 (2015).
[Crossref]

Fieber, K. D.

K. D. Fieber, I. J. Davenport, M. A. Tanase, J. M. Ferryman, R. J. Gurney, V. M. Becerra, J. P. Walker, and J. M. Hacker, “Validation of Canopy Height Profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment,” ISPRS J. Photogramm. Remote Sens. 104, 144–157 (2015).
[Crossref]

Fleck, S.

I. Jonckheere, S. Fleck, K. Nackaerts, B. Muys, P. Coppin, M. Weiss, and F. Baret, “Review of methods for in situ leaf area index determination,” Agric. For. Meteorol. 121(1-2), 19–35 (2004).
[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, 54–65 (2012).
[Crossref]

Gao, S.

W. Li, Z. Niu, G. Sun, S. Gao, and M. Wu, “Deriving backscatter reflective factors from 32-channel full-waveform LiDAR data for the estimation of leaf biochemical contents,” Opt. Express 24(5), 4771–4785 (2016).
[Crossref]

S. Gao, Z. Niu, G. Sun, D. Zhao, K. Jia, and Y. Qin, “Height Extraction of Maize Using Airborne Full-Waveform LIDAR Data and a Deconvolution Algorithm,” IEEE Geosci. Remote. 12(9), 1978–1982 (2015).
[Crossref]

W. Li, Z. Niu, N. Huang, C. Wang, S. Gao, and C. Wu, “Airborne LiDAR technique for estimating biomass components of maize: A case study in Zhangye City, Northwest China,” Ecol. Indic. 57, 486–496 (2015).
[Crossref]

W. Li, Z. Niu, C. Wang, W. Huang, H. Chen, S. Gao, D. Li, and S. Muhammad, “Combined Use of Airborne LiDAR and Satellite GF-1 Data to Estimate Leaf Area Index, Height, and Aboveground Biomass of Maize During Peak Growing Season,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(9), 4489–4501 (2015).
[Crossref]

W. Li, G. Sun, Z. Niu, S. Gao, and H. Qiao, “Estimation of leaf biochemical content using a novel hyperspectral full-waveform LiDAR system,” Remote Sens. Lett. 5(8), 693–702 (2014).
[Crossref]

W. Li, Z. Niu, S. Gao, N. Huang, and H. Y. Chen, “Correlating the Horizontal and Vertical Distribution of LiDAR Point Clouds with Components of Biomass in a Picea crassifolia Forest,” Forests 5(8), 1910–1930 (2014).
[Crossref]

S. Gao, Z. Niu, N. Huang, and X. Hou, “Estimating the Leaf Area Index, height and biomass of maize using HJ-1 and RADARSAT-2,” Int. J. Appl. Earth. Obs. 24, 1–8 (2013).
[Crossref]

Gao, S. A.

C. Y. Wu, Z. Niu, J. D. Wang, S. A. Gao, and W. J. Huang, “Predicting leaf area index in wheat using angular vegetation indices derived from in situ canopy measurements,” Can. J. Rem. Sens. 36(4), 301–312 (2010).
[Crossref]

Goodwin, N.

J. Armston, M. Disney, P. Lewis, P. Scarth, S. Phinn, R. Lucas, P. Bunting, and N. Goodwin, “Direct retrieval of canopy gap probability using airborne waveform lidar,” Remote Sens. Environ. 134, 24–38 (2013).
[Crossref]

Gould, W. A.

S. Martinuzzi, L. A. Vierling, W. A. Gould, M. J. Falkowski, J. S. Evans, A. T. Hudak, and K. T. Vierling, “Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability,” Remote Sens. Environ. 113(12), 2533–2546 (2009).
[Crossref]

Gurney, R. J.

K. D. Fieber, I. J. Davenport, M. A. Tanase, J. M. Ferryman, R. J. Gurney, V. M. Becerra, J. P. Walker, and J. M. Hacker, “Validation of Canopy Height Profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment,” ISPRS J. Photogramm. Remote Sens. 104, 144–157 (2015).
[Crossref]

Hacker, J. M.

K. D. Fieber, I. J. Davenport, M. A. Tanase, J. M. Ferryman, R. J. Gurney, V. M. Becerra, J. P. Walker, and J. M. Hacker, “Validation of Canopy Height Profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment,” ISPRS J. Photogramm. Remote Sens. 104, 144–157 (2015).
[Crossref]

Harding, D.

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]

Harding, D. J.

D. J. Harding, M. A. Lefsky, G. G. Parker, and J. B. Blair, “Laser altimeter canopy height profiles - Methods and validation for closed-canopy, broadleaf forests,” Remote Sens. Environ. 76(3), 283–297 (2001).
[Crossref]

Heiskanen, J.

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]

Hermosilla, T.

T. Hermosilla, N. C. Coops, L. A. Ruiz, and L. M. Moskal, “Deriving pseudo-vertical waveforms from small-footprint full-waveform LiDAR data,” Remote Sens. Lett. 5(4), 332–341 (2014).
[Crossref]

Hofton, M.

H. Tang, R. Dubayah, A. Swatantran, M. Hofton, S. Sheldon, D. B. Clark, and B. Blair, “Retrieval of vertical LAI profiles over tropical rain forests using waveform lidar at La Selva, Costa Rica,” Remote Sens. Environ. 124, 242–250 (2012).
[Crossref]

Hopkinson, C.

C. Hopkinson, L. E. Chasmer, G. Sass, I. F. Creed, M. Sitar, W. Kalbfleisch, and P. Treitz, “Vegetation class dependent errors in lidar ground elevation and canopy height estimates in a boreal wetland environment,” Can. J. Rem. Sens. 31(2), 191–206 (2005).
[Crossref]

Hou, X.

S. Gao, Z. Niu, N. Huang, and X. Hou, “Estimating the Leaf Area Index, height and biomass of maize using HJ-1 and RADARSAT-2,” Int. J. Appl. Earth. Obs. 24, 1–8 (2013).
[Crossref]

Huang, N.

W. Li, Z. Niu, N. Huang, C. Wang, S. Gao, and C. Wu, “Airborne LiDAR technique for estimating biomass components of maize: A case study in Zhangye City, Northwest China,” Ecol. Indic. 57, 486–496 (2015).
[Crossref]

W. Li, Z. Niu, S. Gao, N. Huang, and H. Y. Chen, “Correlating the Horizontal and Vertical Distribution of LiDAR Point Clouds with Components of Biomass in a Picea crassifolia Forest,” Forests 5(8), 1910–1930 (2014).
[Crossref]

S. Gao, Z. Niu, N. Huang, and X. Hou, “Estimating the Leaf Area Index, height and biomass of maize using HJ-1 and RADARSAT-2,” Int. J. Appl. Earth. Obs. 24, 1–8 (2013).
[Crossref]

Huang, W.

W. Li, Z. Niu, C. Wang, W. Huang, H. Chen, S. Gao, D. Li, and S. Muhammad, “Combined Use of Airborne LiDAR and Satellite GF-1 Data to Estimate Leaf Area Index, Height, and Aboveground Biomass of Maize During Peak Growing Season,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(9), 4489–4501 (2015).
[Crossref]

Huang, W. J.

C. Y. Wu, Z. Niu, J. D. Wang, S. A. Gao, and W. J. Huang, “Predicting leaf area index in wheat using angular vegetation indices derived from in situ canopy measurements,” Can. J. Rem. Sens. 36(4), 301–312 (2010).
[Crossref]

Hudak, A. T.

S. Martinuzzi, L. A. Vierling, W. A. Gould, M. J. Falkowski, J. S. Evans, A. T. Hudak, and K. T. Vierling, “Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability,” Remote Sens. Environ. 113(12), 2533–2546 (2009).
[Crossref]

Jia, K.

S. Gao, Z. Niu, G. Sun, D. Zhao, K. Jia, and Y. Qin, “Height Extraction of Maize Using Airborne Full-Waveform LIDAR Data and a Deconvolution Algorithm,” IEEE Geosci. Remote. 12(9), 1978–1982 (2015).
[Crossref]

Jin, G.

Y. Qi, F. Li, Z. Liu, and G. Jin, “Impact of understory on overstorey leaf area index estimation from optical remote sensing in five forest types in northeastern China,” Agric. For. Meteorol. 198–199, 72–80 (2014).
[Crossref]

Jonckheere, I.

I. Jonckheere, S. Fleck, K. Nackaerts, B. Muys, P. Coppin, M. Weiss, and F. Baret, “Review of methods for in situ leaf area index determination,” Agric. For. Meteorol. 121(1-2), 19–35 (2004).
[Crossref]

Jupp, D. L. B.

W. Ni-Meister, D. L. B. Jupp, and R. Dubayah, “Modeling lidar waveforms in heterogeneous and discrete canopies,” IEEE Geosci Remote. 39(9), 1943–1958 (2001).
[Crossref]

Kalbfleisch, W.

C. Hopkinson, L. E. Chasmer, G. Sass, I. F. Creed, M. Sitar, W. Kalbfleisch, and P. Treitz, “Vegetation class dependent errors in lidar ground elevation and canopy height estimates in a boreal wetland environment,” Can. J. Rem. Sens. 31(2), 191–206 (2005).
[Crossref]

Kim, S.-H.

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]

Korhonen, L.

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]

Korpela, I.

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]

Kross, A.

A. Kross, H. McNairn, D. Lapen, M. Sunohara, and C. Champagne, “Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops,” Int. J. Appl. Earth. Obs. 34, 235–248 (2015).
[Crossref]

Lapen, D.

A. Kross, H. McNairn, D. Lapen, M. Sunohara, and C. Champagne, “Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops,” Int. J. Appl. Earth. Obs. 34, 235–248 (2015).
[Crossref]

Lefsky, M. A.

D. J. Harding, M. A. Lefsky, G. G. Parker, and J. B. Blair, “Laser altimeter canopy height profiles - Methods and validation for closed-canopy, broadleaf forests,” Remote Sens. Environ. 76(3), 283–297 (2001).
[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]

Lewis, P.

J. Armston, M. Disney, P. Lewis, P. Scarth, S. Phinn, R. Lucas, P. Bunting, and N. Goodwin, “Direct retrieval of canopy gap probability using airborne waveform lidar,” Remote Sens. Environ. 134, 24–38 (2013).
[Crossref]

Li, D.

W. Li, Z. Niu, C. Wang, W. Huang, H. Chen, S. Gao, D. Li, and S. Muhammad, “Combined Use of Airborne LiDAR and Satellite GF-1 Data to Estimate Leaf Area Index, Height, and Aboveground Biomass of Maize During Peak Growing Season,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(9), 4489–4501 (2015).
[Crossref]

Li, F.

Y. Qi, F. Li, Z. Liu, and G. Jin, “Impact of understory on overstorey leaf area index estimation from optical remote sensing in five forest types in northeastern China,” Agric. For. Meteorol. 198–199, 72–80 (2014).
[Crossref]

Li, G.

S. Luo, C. Wang, F. Pan, X. Xi, G. Li, S. Nie, and S. Xia, “Estimation of wetland vegetation height and leaf area index using airborne laser scanning data,” Ecol. Indic. 48, 550–559 (2015).
[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]

Li, S.

Y. Qin, W. Yao, T. Vu, S. Li, Z. Niu, and Y. Ban, “Characterizing Radiometric Attributes of Point Cloud Using a Normalized Reflective Factor Derived From Small Footprint LiDAR Waveform,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(2), 740–749 (2015).
[Crossref]

Y. Qin, S. Li, T. T. Vu, Z. Niu, and Y. Ban, “Synergistic application of geometric and radiometric features of LiDAR data for urban land cover mapping,” Opt. Express 23(11), 13761–13775 (2015).
[Crossref] [PubMed]

Li, W.

W. Li, Z. Niu, G. Sun, S. Gao, and M. Wu, “Deriving backscatter reflective factors from 32-channel full-waveform LiDAR data for the estimation of leaf biochemical contents,” Opt. Express 24(5), 4771–4785 (2016).
[Crossref]

W. Li, Z. Niu, N. Huang, C. Wang, S. Gao, and C. Wu, “Airborne LiDAR technique for estimating biomass components of maize: A case study in Zhangye City, Northwest China,” Ecol. Indic. 57, 486–496 (2015).
[Crossref]

W. Li, Z. Niu, C. Wang, W. Huang, H. Chen, S. Gao, D. Li, and S. Muhammad, “Combined Use of Airborne LiDAR and Satellite GF-1 Data to Estimate Leaf Area Index, Height, and Aboveground Biomass of Maize During Peak Growing Season,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(9), 4489–4501 (2015).
[Crossref]

W. Li, Z. Niu, S. Gao, N. Huang, and H. Y. Chen, “Correlating the Horizontal and Vertical Distribution of LiDAR Point Clouds with Components of Biomass in a Picea crassifolia Forest,” Forests 5(8), 1910–1930 (2014).
[Crossref]

W. Li, G. Sun, Z. Niu, S. Gao, and H. Qiao, “Estimation of leaf biochemical content using a novel hyperspectral full-waveform LiDAR system,” Remote Sens. Lett. 5(8), 693–702 (2014).
[Crossref]

Lindenbergh, R.

V. H. Duong, R. Lindenbergh, N. Pfeifer, and G. Vosselman, “Single and two epoch analysis of ICESat full waveform data over forested areas,” Int. J. Remote Sens. 29(5), 1453–1473 (2008).
[Crossref]

Liu, Z.

Y. Qi, F. Li, Z. Liu, and G. Jin, “Impact of understory on overstorey leaf area index estimation from optical remote sensing in five forest types in northeastern China,” Agric. For. Meteorol. 198–199, 72–80 (2014).
[Crossref]

Lucas, R.

J. Armston, M. Disney, P. Lewis, P. Scarth, S. Phinn, R. Lucas, P. Bunting, and N. Goodwin, “Direct retrieval of canopy gap probability using airborne waveform lidar,” Remote Sens. Environ. 134, 24–38 (2013).
[Crossref]

Luo, S.

S. Luo, C. Wang, F. Pan, X. Xi, G. Li, S. Nie, and S. Xia, “Estimation of wetland vegetation height and leaf area index using airborne laser scanning data,” Ecol. Indic. 48, 550–559 (2015).
[Crossref]

S. Luo, C. Wang, X. Xi, and F. Pan, “Estimating FPAR of maize canopy using airborne discrete-return LiDAR data,” Opt. Express 22(5), 5106–5117 (2014).
[Crossref] [PubMed]

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]

Magruder, L. A.

L. A. Magruder, A. L. Neuenschwander, and S. P. Marmillion, “Lidar waveform stacking techniques for faint ground return extraction,” J. Appl. Remote Sens. 4(1), 043501 (2010).
[Crossref]

Maltamo, M.

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]

Marmillion, S. P.

L. A. Magruder, A. L. Neuenschwander, and S. P. Marmillion, “Lidar waveform stacking techniques for faint ground return extraction,” J. Appl. Remote Sens. 4(1), 043501 (2010).
[Crossref]

Martinuzzi, S.

S. Martinuzzi, L. A. Vierling, W. A. Gould, M. J. Falkowski, J. S. Evans, A. T. Hudak, and K. T. Vierling, “Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability,” Remote Sens. Environ. 113(12), 2533–2546 (2009).
[Crossref]

McNairn, H.

A. Kross, H. McNairn, D. Lapen, M. Sunohara, and C. Champagne, “Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops,” Int. J. Appl. Earth. Obs. 34, 235–248 (2015).
[Crossref]

Meentemeyer, R. K.

K. K. Singh, A. J. Davis, and R. K. Meentemeyer, “Detecting understory plant invasion in urban forests using LiDAR,” Int. J. Appl. Earth. Obs. 38, 267–279 (2015).
[Crossref]

Moskal, L. M.

T. Hermosilla, N. C. Coops, L. A. Ruiz, and L. M. Moskal, “Deriving pseudo-vertical waveforms from small-footprint full-waveform LiDAR data,” Remote Sens. Lett. 5(4), 332–341 (2014).
[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]

Muhammad, S.

W. Li, Z. Niu, C. Wang, W. Huang, H. Chen, S. Gao, D. Li, and S. Muhammad, “Combined Use of Airborne LiDAR and Satellite GF-1 Data to Estimate Leaf Area Index, Height, and Aboveground Biomass of Maize During Peak Growing Season,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(9), 4489–4501 (2015).
[Crossref]

Muys, B.

I. Jonckheere, S. Fleck, K. Nackaerts, B. Muys, P. Coppin, M. Weiss, and F. Baret, “Review of methods for in situ leaf area index determination,” Agric. For. Meteorol. 121(1-2), 19–35 (2004).
[Crossref]

Nackaerts, K.

I. Jonckheere, S. Fleck, K. Nackaerts, B. Muys, P. Coppin, M. Weiss, and F. Baret, “Review of methods for in situ leaf area index determination,” Agric. For. Meteorol. 121(1-2), 19–35 (2004).
[Crossref]

Nelson, R. F.

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, 54–65 (2012).
[Crossref]

Neuenschwander, A. L.

L. A. Magruder, A. L. Neuenschwander, and S. P. Marmillion, “Lidar waveform stacking techniques for faint ground return extraction,” J. Appl. Remote Sens. 4(1), 043501 (2010).
[Crossref]

Nie, S.

S. Nie, C. Wang, P. Dong, and X. Xi, “Estimating leaf area index of maize using airborne full-waveform lidar data,” Remote Sens. Lett. 7(2), 111–120 (2016).
[Crossref]

S. Luo, C. Wang, F. Pan, X. Xi, G. Li, S. Nie, and S. Xia, “Estimation of wetland vegetation height and leaf area index using airborne laser scanning data,” Ecol. Indic. 48, 550–559 (2015).
[Crossref]

Ni-Meister, W.

W. Ni-Meister, D. L. B. Jupp, and R. Dubayah, “Modeling lidar waveforms in heterogeneous and discrete canopies,” IEEE Geosci Remote. 39(9), 1943–1958 (2001).
[Crossref]

Niu, Z.

W. Li, Z. Niu, G. Sun, S. Gao, and M. Wu, “Deriving backscatter reflective factors from 32-channel full-waveform LiDAR data for the estimation of leaf biochemical contents,” Opt. Express 24(5), 4771–4785 (2016).
[Crossref]

Y. Qin, S. Li, T. T. Vu, Z. Niu, and Y. Ban, “Synergistic application of geometric and radiometric features of LiDAR data for urban land cover mapping,” Opt. Express 23(11), 13761–13775 (2015).
[Crossref] [PubMed]

W. Li, Z. Niu, N. Huang, C. Wang, S. Gao, and C. Wu, “Airborne LiDAR technique for estimating biomass components of maize: A case study in Zhangye City, Northwest China,” Ecol. Indic. 57, 486–496 (2015).
[Crossref]

S. Gao, Z. Niu, G. Sun, D. Zhao, K. Jia, and Y. Qin, “Height Extraction of Maize Using Airborne Full-Waveform LIDAR Data and a Deconvolution Algorithm,” IEEE Geosci. Remote. 12(9), 1978–1982 (2015).
[Crossref]

Y. Qin, W. Yao, T. Vu, S. Li, Z. Niu, and Y. Ban, “Characterizing Radiometric Attributes of Point Cloud Using a Normalized Reflective Factor Derived From Small Footprint LiDAR Waveform,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(2), 740–749 (2015).
[Crossref]

W. Li, Z. Niu, C. Wang, W. Huang, H. Chen, S. Gao, D. Li, and S. Muhammad, “Combined Use of Airborne LiDAR and Satellite GF-1 Data to Estimate Leaf Area Index, Height, and Aboveground Biomass of Maize During Peak Growing Season,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(9), 4489–4501 (2015).
[Crossref]

W. Li, Z. Niu, S. Gao, N. Huang, and H. Y. Chen, “Correlating the Horizontal and Vertical Distribution of LiDAR Point Clouds with Components of Biomass in a Picea crassifolia Forest,” Forests 5(8), 1910–1930 (2014).
[Crossref]

W. Li, G. Sun, Z. Niu, S. Gao, and H. Qiao, “Estimation of leaf biochemical content using a novel hyperspectral full-waveform LiDAR system,” Remote Sens. Lett. 5(8), 693–702 (2014).
[Crossref]

S. Gao, Z. Niu, N. Huang, and X. Hou, “Estimating the Leaf Area Index, height and biomass of maize using HJ-1 and RADARSAT-2,” Int. J. Appl. Earth. Obs. 24, 1–8 (2013).
[Crossref]

C. Y. Wu, Z. Niu, J. D. Wang, S. A. Gao, and W. J. Huang, “Predicting leaf area index in wheat using angular vegetation indices derived from in situ canopy measurements,” Can. J. Rem. Sens. 36(4), 301–312 (2010).
[Crossref]

Pan, F.

S. Luo, C. Wang, F. Pan, X. Xi, G. Li, S. Nie, and S. Xia, “Estimation of wetland vegetation height and leaf area index using airborne laser scanning data,” Ecol. Indic. 48, 550–559 (2015).
[Crossref]

S. Luo, C. Wang, X. Xi, and F. Pan, “Estimating FPAR of maize canopy using airborne discrete-return LiDAR data,” Opt. Express 22(5), 5106–5117 (2014).
[Crossref] [PubMed]

Parker, G. G.

D. J. Harding, M. A. Lefsky, G. G. Parker, and J. B. Blair, “Laser altimeter canopy height profiles - Methods and validation for closed-canopy, broadleaf forests,” Remote Sens. Environ. 76(3), 283–297 (2001).
[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]

Peduzzi, 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, 54–65 (2012).
[Crossref]

Pfeifer, N.

V. H. Duong, R. Lindenbergh, N. Pfeifer, and G. Vosselman, “Single and two epoch analysis of ICESat full waveform data over forested areas,” Int. J. Remote Sens. 29(5), 1453–1473 (2008).
[Crossref]

Phinn, S.

J. Armston, M. Disney, P. Lewis, P. Scarth, S. Phinn, R. Lucas, P. Bunting, and N. Goodwin, “Direct retrieval of canopy gap probability using airborne waveform lidar,” Remote Sens. Environ. 134, 24–38 (2013).
[Crossref]

Popescu, S.

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]

Qi, Y.

Y. Qi, F. Li, Z. Liu, and G. Jin, “Impact of understory on overstorey leaf area index estimation from optical remote sensing in five forest types in northeastern China,” Agric. For. Meteorol. 198–199, 72–80 (2014).
[Crossref]

Qiao, H.

W. Li, G. Sun, Z. Niu, S. Gao, and H. Qiao, “Estimation of leaf biochemical content using a novel hyperspectral full-waveform LiDAR system,” Remote Sens. Lett. 5(8), 693–702 (2014).
[Crossref]

Qin, Y.

Y. Qin, W. Yao, T. Vu, S. Li, Z. Niu, and Y. Ban, “Characterizing Radiometric Attributes of Point Cloud Using a Normalized Reflective Factor Derived From Small Footprint LiDAR Waveform,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(2), 740–749 (2015).
[Crossref]

S. Gao, Z. Niu, G. Sun, D. Zhao, K. Jia, and Y. Qin, “Height Extraction of Maize Using Airborne Full-Waveform LIDAR Data and a Deconvolution Algorithm,” IEEE Geosci. Remote. 12(9), 1978–1982 (2015).
[Crossref]

Y. Qin, S. Li, T. T. Vu, Z. Niu, and Y. Ban, “Synergistic application of geometric and radiometric features of LiDAR data for urban land cover mapping,” Opt. Express 23(11), 13761–13775 (2015).
[Crossref] [PubMed]

Y. Qin, T. T. Vu, and Y. F. Ban, “Toward an Optimal Algorithm for LiDAR Waveform Decomposition,” IEEE Geosci Remote Sens. 9(3), 482–486 (2012).
[Crossref]

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).
[Crossref]

Ruiz, L. A.

T. Hermosilla, N. C. Coops, L. A. Ruiz, and L. M. Moskal, “Deriving pseudo-vertical waveforms from small-footprint full-waveform LiDAR data,” Remote Sens. Lett. 5(4), 332–341 (2014).
[Crossref]

Sass, G.

C. Hopkinson, L. E. Chasmer, G. Sass, I. F. Creed, M. Sitar, W. Kalbfleisch, and P. Treitz, “Vegetation class dependent errors in lidar ground elevation and canopy height estimates in a boreal wetland environment,” Can. J. Rem. Sens. 31(2), 191–206 (2005).
[Crossref]

Scarth, P.

J. Armston, M. Disney, P. Lewis, P. Scarth, S. Phinn, R. Lucas, P. Bunting, and N. Goodwin, “Direct retrieval of canopy gap probability using airborne waveform lidar,” Remote Sens. Environ. 134, 24–38 (2013).
[Crossref]

Sheldon, S.

H. Tang, R. Dubayah, A. Swatantran, M. Hofton, S. Sheldon, D. B. Clark, and B. Blair, “Retrieval of vertical LAI profiles over tropical rain forests using waveform lidar at La Selva, Costa Rica,” Remote Sens. Environ. 124, 242–250 (2012).
[Crossref]

Singh, K. K.

K. K. Singh, A. J. Davis, and R. K. Meentemeyer, “Detecting understory plant invasion in urban forests using LiDAR,” Int. J. Appl. Earth. Obs. 38, 267–279 (2015).
[Crossref]

Sitar, M.

C. Hopkinson, L. E. Chasmer, G. Sass, I. F. Creed, M. Sitar, W. Kalbfleisch, and P. Treitz, “Vegetation class dependent errors in lidar ground elevation and canopy height estimates in a boreal wetland environment,” Can. J. Rem. Sens. 31(2), 191–206 (2005).
[Crossref]

Solberg, S.

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

Sun, G.

W. Li, Z. Niu, G. Sun, S. Gao, and M. Wu, “Deriving backscatter reflective factors from 32-channel full-waveform LiDAR data for the estimation of leaf biochemical contents,” Opt. Express 24(5), 4771–4785 (2016).
[Crossref]

S. Gao, Z. Niu, G. Sun, D. Zhao, K. Jia, and Y. Qin, “Height Extraction of Maize Using Airborne Full-Waveform LIDAR Data and a Deconvolution Algorithm,” IEEE Geosci. Remote. 12(9), 1978–1982 (2015).
[Crossref]

W. Li, G. Sun, Z. Niu, S. Gao, and H. Qiao, “Estimation of leaf biochemical content using a novel hyperspectral full-waveform LiDAR system,” Remote Sens. Lett. 5(8), 693–702 (2014).
[Crossref]

Sunohara, M.

A. Kross, H. McNairn, D. Lapen, M. Sunohara, and C. Champagne, “Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops,” Int. J. Appl. Earth. Obs. 34, 235–248 (2015).
[Crossref]

Swatantran, A.

H. Tang, R. Dubayah, A. Swatantran, M. Hofton, S. Sheldon, D. B. Clark, and B. Blair, “Retrieval of vertical LAI profiles over tropical rain forests using waveform lidar at La Selva, Costa Rica,” Remote Sens. Environ. 124, 242–250 (2012).
[Crossref]

Tanase, M. A.

K. D. Fieber, I. J. Davenport, M. A. Tanase, J. M. Ferryman, R. J. Gurney, V. M. Becerra, J. P. Walker, and J. M. Hacker, “Validation of Canopy Height Profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment,” ISPRS J. Photogramm. Remote Sens. 104, 144–157 (2015).
[Crossref]

Tang, H.

H. Tang, R. Dubayah, A. Swatantran, M. Hofton, S. Sheldon, D. B. Clark, and B. Blair, “Retrieval of vertical LAI profiles over tropical rain forests using waveform lidar at La Selva, Costa Rica,” Remote Sens. Environ. 124, 242–250 (2012).
[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, 54–65 (2012).
[Crossref]

Treitz, P.

C. Hopkinson, L. E. Chasmer, G. Sass, I. F. Creed, M. Sitar, W. Kalbfleisch, and P. Treitz, “Vegetation class dependent errors in lidar ground elevation and canopy height estimates in a boreal wetland environment,” Can. J. Rem. Sens. 31(2), 191–206 (2005).
[Crossref]

Vierling, K. T.

S. Martinuzzi, L. A. Vierling, W. A. Gould, M. J. Falkowski, J. S. Evans, A. T. Hudak, and K. T. Vierling, “Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability,” Remote Sens. Environ. 113(12), 2533–2546 (2009).
[Crossref]

Vierling, L. A.

S. Martinuzzi, L. A. Vierling, W. A. Gould, M. J. Falkowski, J. S. Evans, A. T. Hudak, and K. T. Vierling, “Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability,” Remote Sens. Environ. 113(12), 2533–2546 (2009).
[Crossref]

Vosselman, G.

V. H. Duong, R. Lindenbergh, N. Pfeifer, and G. Vosselman, “Single and two epoch analysis of ICESat full waveform data over forested areas,” Int. J. Remote Sens. 29(5), 1453–1473 (2008).
[Crossref]

Vu, T.

Y. Qin, W. Yao, T. Vu, S. Li, Z. Niu, and Y. Ban, “Characterizing Radiometric Attributes of Point Cloud Using a Normalized Reflective Factor Derived From Small Footprint LiDAR Waveform,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(2), 740–749 (2015).
[Crossref]

Vu, T. T.

Walker, J. P.

K. D. Fieber, I. J. Davenport, M. A. Tanase, J. M. Ferryman, R. J. Gurney, V. M. Becerra, J. P. Walker, and J. M. Hacker, “Validation of Canopy Height Profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment,” ISPRS J. Photogramm. Remote Sens. 104, 144–157 (2015).
[Crossref]

Wang, C.

S. Nie, C. Wang, P. Dong, and X. Xi, “Estimating leaf area index of maize using airborne full-waveform lidar data,” Remote Sens. Lett. 7(2), 111–120 (2016).
[Crossref]

S. Luo, C. Wang, F. Pan, X. Xi, G. Li, S. Nie, and S. Xia, “Estimation of wetland vegetation height and leaf area index using airborne laser scanning data,” Ecol. Indic. 48, 550–559 (2015).
[Crossref]

W. Li, Z. Niu, N. Huang, C. Wang, S. Gao, and C. Wu, “Airborne LiDAR technique for estimating biomass components of maize: A case study in Zhangye City, Northwest China,” Ecol. Indic. 57, 486–496 (2015).
[Crossref]

W. Li, Z. Niu, C. Wang, W. Huang, H. Chen, S. Gao, D. Li, and S. Muhammad, “Combined Use of Airborne LiDAR and Satellite GF-1 Data to Estimate Leaf Area Index, Height, and Aboveground Biomass of Maize During Peak Growing Season,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(9), 4489–4501 (2015).
[Crossref]

S. Luo, C. Wang, X. Xi, and F. Pan, “Estimating FPAR of maize canopy using airborne discrete-return LiDAR data,” Opt. Express 22(5), 5106–5117 (2014).
[Crossref] [PubMed]

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]

Wang, J. D.

C. Y. Wu, Z. Niu, J. D. Wang, S. A. Gao, and W. J. Huang, “Predicting leaf area index in wheat using angular vegetation indices derived from in situ canopy measurements,” Can. J. Rem. Sens. 36(4), 301–312 (2010).
[Crossref]

Weiss, M.

I. Jonckheere, S. Fleck, K. Nackaerts, B. Muys, P. Coppin, M. Weiss, and F. Baret, “Review of methods for in situ leaf area index determination,” Agric. For. Meteorol. 121(1-2), 19–35 (2004).
[Crossref]

Wu, C.

W. Li, Z. Niu, N. Huang, C. Wang, S. Gao, and C. Wu, “Airborne LiDAR technique for estimating biomass components of maize: A case study in Zhangye City, Northwest China,” Ecol. Indic. 57, 486–496 (2015).
[Crossref]

Wu, C. Y.

C. Y. Wu, Z. Niu, J. D. Wang, S. A. Gao, and W. J. Huang, “Predicting leaf area index in wheat using angular vegetation indices derived from in situ canopy measurements,” Can. J. Rem. Sens. 36(4), 301–312 (2010).
[Crossref]

Wu, M.

Wynne, R. H.

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, 54–65 (2012).
[Crossref]

Xi, X.

S. Nie, C. Wang, P. Dong, and X. Xi, “Estimating leaf area index of maize using airborne full-waveform lidar data,” Remote Sens. Lett. 7(2), 111–120 (2016).
[Crossref]

S. Luo, C. Wang, F. Pan, X. Xi, G. Li, S. Nie, and S. Xia, “Estimation of wetland vegetation height and leaf area index using airborne laser scanning data,” Ecol. Indic. 48, 550–559 (2015).
[Crossref]

S. Luo, C. Wang, X. Xi, and F. Pan, “Estimating FPAR of maize canopy using airborne discrete-return LiDAR data,” Opt. Express 22(5), 5106–5117 (2014).
[Crossref] [PubMed]

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]

Xia, S.

S. Luo, C. Wang, F. Pan, X. Xi, G. Li, S. Nie, and S. Xia, “Estimation of wetland vegetation height and leaf area index using airborne laser scanning data,” Ecol. Indic. 48, 550–559 (2015).
[Crossref]

Yao, W.

Y. Qin, W. Yao, T. Vu, S. Li, Z. Niu, and Y. Ban, “Characterizing Radiometric Attributes of Point Cloud Using a Normalized Reflective Factor Derived From Small Footprint LiDAR Waveform,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(2), 740–749 (2015).
[Crossref]

Zhao, D.

S. Gao, Z. Niu, G. Sun, D. Zhao, K. Jia, and Y. Qin, “Height Extraction of Maize Using Airborne Full-Waveform LIDAR Data and a Deconvolution Algorithm,” IEEE Geosci. Remote. 12(9), 1978–1982 (2015).
[Crossref]

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).
[Crossref]

Agric. For. Meteorol. (3)

I. Jonckheere, S. Fleck, K. Nackaerts, B. Muys, P. Coppin, M. Weiss, and F. Baret, “Review of methods for in situ leaf area index determination,” Agric. For. Meteorol. 121(1-2), 19–35 (2004).
[Crossref]

Y. Qi, F. Li, Z. Liu, and G. Jin, “Impact of understory on overstorey leaf area index estimation from optical remote sensing in five forest types in northeastern China,” Agric. For. Meteorol. 198–199, 72–80 (2014).
[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]

Can. J. Rem. Sens. (2)

C. Y. Wu, Z. Niu, J. D. Wang, S. A. Gao, and W. J. Huang, “Predicting leaf area index in wheat using angular vegetation indices derived from in situ canopy measurements,” Can. J. Rem. Sens. 36(4), 301–312 (2010).
[Crossref]

C. Hopkinson, L. E. Chasmer, G. Sass, I. F. Creed, M. Sitar, W. Kalbfleisch, and P. Treitz, “Vegetation class dependent errors in lidar ground elevation and canopy height estimates in a boreal wetland environment,” Can. J. Rem. Sens. 31(2), 191–206 (2005).
[Crossref]

Ecol. Indic. (2)

W. Li, Z. Niu, N. Huang, C. Wang, S. Gao, and C. Wu, “Airborne LiDAR technique for estimating biomass components of maize: A case study in Zhangye City, Northwest China,” Ecol. Indic. 57, 486–496 (2015).
[Crossref]

S. Luo, C. Wang, F. Pan, X. Xi, G. Li, S. Nie, and S. Xia, “Estimation of wetland vegetation height and leaf area index using airborne laser scanning data,” Ecol. Indic. 48, 550–559 (2015).
[Crossref]

For. Ecol. Manage. (1)

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, 54–65 (2012).
[Crossref]

Forests (1)

W. Li, Z. Niu, S. Gao, N. Huang, and H. Y. Chen, “Correlating the Horizontal and Vertical Distribution of LiDAR Point Clouds with Components of Biomass in a Picea crassifolia Forest,” Forests 5(8), 1910–1930 (2014).
[Crossref]

IEEE Geosci Remote Sens. (1)

Y. Qin, T. T. Vu, and Y. F. Ban, “Toward an Optimal Algorithm for LiDAR Waveform Decomposition,” IEEE Geosci Remote Sens. 9(3), 482–486 (2012).
[Crossref]

IEEE Geosci Remote. (1)

W. Ni-Meister, D. L. B. Jupp, and R. Dubayah, “Modeling lidar waveforms in heterogeneous and discrete canopies,” IEEE Geosci Remote. 39(9), 1943–1958 (2001).
[Crossref]

IEEE Geosci. Remote. (1)

S. Gao, Z. Niu, G. Sun, D. Zhao, K. Jia, and Y. Qin, “Height Extraction of Maize Using Airborne Full-Waveform LIDAR Data and a Deconvolution Algorithm,” IEEE Geosci. Remote. 12(9), 1978–1982 (2015).
[Crossref]

IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. (2)

W. Li, Z. Niu, C. Wang, W. Huang, H. Chen, S. Gao, D. Li, and S. Muhammad, “Combined Use of Airborne LiDAR and Satellite GF-1 Data to Estimate Leaf Area Index, Height, and Aboveground Biomass of Maize During Peak Growing Season,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(9), 4489–4501 (2015).
[Crossref]

Y. Qin, W. Yao, T. Vu, S. Li, Z. Niu, and Y. Ban, “Characterizing Radiometric Attributes of Point Cloud Using a Normalized Reflective Factor Derived From Small Footprint LiDAR Waveform,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8(2), 740–749 (2015).
[Crossref]

Int. J. Appl. Earth. Obs. (3)

K. K. Singh, A. J. Davis, and R. K. Meentemeyer, “Detecting understory plant invasion in urban forests using LiDAR,” Int. J. Appl. Earth. Obs. 38, 267–279 (2015).
[Crossref]

S. Gao, Z. Niu, N. Huang, and X. Hou, “Estimating the Leaf Area Index, height and biomass of maize using HJ-1 and RADARSAT-2,” Int. J. Appl. Earth. Obs. 24, 1–8 (2013).
[Crossref]

A. Kross, H. McNairn, D. Lapen, M. Sunohara, and C. Champagne, “Assessment of RapidEye vegetation indices for estimation of leaf area index and biomass in corn and soybean crops,” Int. J. Appl. Earth. Obs. 34, 235–248 (2015).
[Crossref]

Int. J. Remote Sens. (2)

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

V. H. Duong, R. Lindenbergh, N. Pfeifer, and G. Vosselman, “Single and two epoch analysis of ICESat full waveform data over forested areas,” Int. J. Remote Sens. 29(5), 1453–1473 (2008).
[Crossref]

ISPRS J. Photogramm. Remote Sens. (1)

K. D. Fieber, I. J. Davenport, M. A. Tanase, J. M. Ferryman, R. J. Gurney, V. M. Becerra, J. P. Walker, and J. M. Hacker, “Validation of Canopy Height Profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment,” ISPRS J. Photogramm. Remote Sens. 104, 144–157 (2015).
[Crossref]

J. Appl. Remote Sens. (1)

L. A. Magruder, A. L. Neuenschwander, and S. P. Marmillion, “Lidar waveform stacking techniques for faint ground return extraction,” J. Appl. Remote Sens. 4(1), 043501 (2010).
[Crossref]

J. Exp. Bot. (1)

N. J. J. Bréda, “Ground-based measurements of leaf area index: a review of methods, instruments and current controversies,” J. Exp. Bot. 54(392), 2403–2417 (2003).
[Crossref] [PubMed]

Opt. Express (3)

Plant Cell Environ. (1)

J. M. Chen and T. A. Black, “Defining leaf area index for non-flat leaves,” Plant Cell Environ. 15(4), 421–429 (1992).
[Crossref]

Remote Sens. Environ. (7)

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]

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]

H. Tang, R. Dubayah, A. Swatantran, M. Hofton, S. Sheldon, D. B. Clark, and B. Blair, “Retrieval of vertical LAI profiles over tropical rain forests using waveform lidar at La Selva, Costa Rica,” Remote Sens. Environ. 124, 242–250 (2012).
[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]

S. Martinuzzi, L. A. Vierling, W. A. Gould, M. J. Falkowski, J. S. Evans, A. T. Hudak, and K. T. Vierling, “Mapping snags and understory shrubs for a LiDAR-based assessment of wildlife habitat suitability,” Remote Sens. Environ. 113(12), 2533–2546 (2009).
[Crossref]

D. J. Harding, M. A. Lefsky, G. G. Parker, and J. B. Blair, “Laser altimeter canopy height profiles - Methods and validation for closed-canopy, broadleaf forests,” Remote Sens. Environ. 76(3), 283–297 (2001).
[Crossref]

J. Armston, M. Disney, P. Lewis, P. Scarth, S. Phinn, R. Lucas, P. Bunting, and N. Goodwin, “Direct retrieval of canopy gap probability using airborne waveform lidar,” Remote Sens. Environ. 134, 24–38 (2013).
[Crossref]

Remote Sens. Lett. (4)

W. Li, G. Sun, Z. Niu, S. Gao, and H. Qiao, “Estimation of leaf biochemical content using a novel hyperspectral full-waveform LiDAR system,” Remote Sens. Lett. 5(8), 693–702 (2014).
[Crossref]

T. Hermosilla, N. C. Coops, L. A. Ruiz, and L. M. Moskal, “Deriving pseudo-vertical waveforms from small-footprint full-waveform LiDAR data,” Remote Sens. Lett. 5(4), 332–341 (2014).
[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]

S. Nie, C. Wang, P. Dong, and X. Xi, “Estimating leaf area index of maize using airborne full-waveform lidar data,” Remote Sens. Lett. 7(2), 111–120 (2016).
[Crossref]

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Figures (5)

Fig. 1
Fig. 1 The study site of Huailai area with field plots overlain on the Google Earth image.
Fig. 2
Fig. 2 The main methodological workflow for this study.
Fig. 3
Fig. 3 The Gaussian-fitted waveform and corresponding residuals based on the pseudo large footprint waveform.
Fig. 4
Fig. 4 The distribution of LAIs along the vertical direction in (a) a high LAI plot and (b) a low LAI plot retrieved from the pseudo large waveforms.
Fig. 5
Fig. 5 The observed and retrieved (a) Hover (m); (b) Hunder (m); (c) LAIover; (d) LAIunder; and (e) LAItotal. The red dashed line represents the 1:1 line. **p<0.01.

Tables (4)

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Table 1 Specifications of airborne LiDAR flights in the Huailai area.

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Table 2 Main attributes of the field plots

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Table 3 Basic statistics of field-measured leaf area index (LAI) and canopy height for the different layers in the orchard plots (N = 20)

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Table 4 Basic statistics of the retrieved canopy height and LAI for the field plots (N = 20)

Equations (10)

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V norm, i = V i V T
V T = i = 1 N V i
f ( t i ) = h i exp [ ( t i α i ) 2 w i 2 ]
f ( t ) = i = 1 n f ( t i )
P ( θ ) = e G ( θ ) * L A I / cos ( θ )
P ( z ) = 1 f c o v e r ( z ) = 1 R v ( z ) R v ( 0 ) 1 1 + ρ v ρ g R g R v ( 0 )
F app ( z ) = d log P ( z ) d z
L A I cum ( z ) = C * z 0 z F app ( z ) G d z
R M S E = 1 n i = 1 n ( p i p i ) 2
r R M S E = R M S E p ¯

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