Estimation of Spruce Needle-Leaf Chlorophyll Content Based on DART and PARAS Canopy Reflectance Models

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Volumn 8, Issue 4, 2015, Pages 1534-1544

  Yáñez Rausell, Lucia ^a,b   Malenovský, Zbyněk ^c,d   Rautiainen, Miina ^e   Clevers, Jan G P W ^a   Lukeš, Petr ^e   Hanuš, Jan ^f   Schaepman, Michael E ^b  

^a WAGENINGEN UNIVERSITY   (Netherlands)

^b UNIVERSITY OF ZURICH   (Switzerland)

^c UNIVERSITY OF WOLLONGONG   (Australia)

^d UNIVERSITY OF TASMANIA   (Australia)

^e UNIVERSITY OF HELSINKI   (Finland)

^f CVGZ AV R CzechGlobe   (Czech Republic)

Author keywords

Chlorophyll a + b estimation; CHRIS PROBA; coniferous forest; continuum removal; discrete anisotropic radiative transfer model (DART); needle leaf, Norway spruce; optical indices; PARAS, PROSPECT; radiative transfer; recollision probability

Indexed keywords

ANISOTROPY; CHLOROPHYLL; FORESTRY; NEEDLES; PLANTS (BOTANY); REFLECTION;

CHLOROPHYLL A; CHRIS-PROBA; CONIFEROUS FORESTS; CONTINUUM REMOVAL; NORWAY SPRUCE; OPTICAL INDICES; PARAS, PROSPECT; RADIATIVE TRANSFER MODEL; RECOLLISION PROBABILITY;

RADIATIVE TRANSFER;

CANOPY REFLECTANCE; CHLOROPHYLL A; CONIFEROUS FOREST; ESTIMATION METHOD; LEAD; MODELING; OPTICAL PROPERTY; PROBABILITY; RADIATIVE TRANSFER; SATELLITE IMAGERY;

ANISOTROPY; CHLOROPHYLLS; FORESTS; PROBABILITY; SOFTWOODS;

PICEA; PICEA ABIES;

EID: 84973375928     PISSN: 19391404     EISSN: 21511535     Source Type: Journal    
DOI: 10.1109/JSTARS.2015.2400418     Document Type: Article

References (37)

1. M. Chen et al., "A red-shifted chlorophyll," Science, vol. 329, pp. 1318-1319, 2010.
2. G. A. Blackburn, "Hyperspectral remote sensing of plant pigments," J. Exp. Bot., vol. 58, pp. 855-867, 2007.
3. S. L. Ustin et al., "Retrieval of foliar information about plant pigment systems from high resolution spectroscopy," Remote Sens. Environ., vol.113, pp. S67-S77, 2009.
4. G. le Maire et al., "Calibration and validation of hyperspectral indices for the estimation of broadleaved forest leaf chlorophyll content, leaf mass per area, leaf area index and leaf canopy biomass," Remote Sens. Environ., vol. 112, pp. 3846-3864, 2008.
5. J. L. Widlowski et al., "Third radiation transfer model intercomparison (RAMI) exercise: Documenting progress in canopy reflectance models," J. Geophys. Res. D Atmos., vol. 112, 2007.
6. J. Verrelst, M. E. Schaepman, B. Koetz, and M. Kneubühler, "Angular sensitivity analysis of vegetation indices derived from CHRIS/PROBA data," Remote Sens. Environ., vol. 112, pp. 2341-2353, 2008.
7. J. M. Chen, "Optically-based methods for measuring seasonal variation of leaf area index in boreal conifer stands," Agric. For. Meteorol., vol.80, pp. 135-163, 1996.
8. P. Stenberg, "Correcting LAI-2000 estimates for the clumping of needles in shoots of conifers," Agric. For. Meteorol., vol. 79, pp. 1-8, 1996.
9. P. Stenberg, "A note on the G-function for needle leaf canopies," Agric. For. Meteorol., vol. 136, pp. 76-79, 2006.
10. T. Nilson, "Inversion of gap frequency data in forest stands," Agric. For. Meteorol., vol. 98-99, pp. 437-448, 1999.
11. M. Rautiainen and P. Stenberg, "Application of photon recollision probability in coniferous canopy reflectance simulations," Remote Sens. Environ., vol. 96, pp. 98-107, 2005.
12. S. G. Leblanc, P. Bicheron, J. M. Chen, M. Leroy, and J. Cihlar, "Investigation of directional reflectance in boreal forests with an improved four-scale model and airborne POLDER data," IEEE Trans. Geosci. Remote Sens., vol. 37, no. 3, pp. 1396-1414, May 1999.
13. J. P. Gastellu-Etchegorry, E. Martin, and F. Gascon, "DART: A 3D model for simulating satellite images and studying surface radiation budget," Int. J. Remote Sens., vol. 25, pp. 73-96, 2004.
14. Z. Malenovský et al., "Retrieval of spruce leaf chlorophyll content from airborne image data using continuum removal and radiative transfer," Remote Sens. Environ., vol. 131, pp. 85-102, 2013.
15. R. Hernández-Clemente, R. M. Navarro-Cerrillo, and P. J. Zarco-Tejada, "Carotenoid content estimation in a heterogeneous conifer forest using narrow-band indices and PROSPECT+DART simulations," Remote Sens. Environ., vol. 127, pp. 298-315, 2012.
16. P. Stenberg, M. Mõttus, and M. Rautiainen, "Modeling the spectral signature of forests: Application of remote sensing models to coniferous canopies," in Advances in Land Remote Sensing, S.Liang, Ed. New York, NY, USA: Springer, 2008, pp. 147-171.
17. G. Schaepman-Strub, M. E. Schaepman, T. H. Painter, S. Dangel, and J. V. Martonchik, "Reflectance quantities in optical remote sensing-definitions and case studies," Remote Sens. Environ., vol. 103, pp. 27-42, 2006.
18. S. Smolander and P. Stenberg, "A method to account for shoot scale clumping in coniferous canopy reflectance models," Remote Sens. Environ., vol. 88, pp. 363-373, 2003.
19. M. Rautiainen et al., "Coupling forest canopy and understory reflectance in the Arctic latitudes of Finland," Remote Sens. Environ., vol. 110, pp. 332-343, 2007.
20. J. Heiskanen, M. Rautiainen, L. Korhonen, M. Mõttus, and P. Stenberg, "Retrieval of boreal forest LAI using a forest reflectance model and empirical regressions," Int. J. Appl. Earth Observ. Geoinf., vol. 13, pp. 595-606, 2011.
21. M. A. Cutter, D. R. Lobb, and R. A. Cockshott, "Compact high resolution imaging spectrometer (CHRIS)," Acta Astronaut., vol. 46, pp. 263-268, 2000.
22. P. Lukeš, M. Rautiainen, P. Stenberg, and Z. Malenovský, "Empirical test of the spectral invariants theory using imaging spectroscopy data from a coniferous forest," Int. J. Appl. Earth Observ. Geoinf., vol. 13, pp. 668-675, 2011.
23. Z. Malenovský et al., "Influence of woody elements of a Norway spruce canopy on nadir reflectance simulated by the DART model at very high spatial resolution," Remote Sens. Environ., vol. 112, pp. 1-18, 2008.
24. R. Pokorný, I. Tomáškova, and K. Havrankova, "Temporal variation and efficiency of leaf area index in young mountain Norway spruce stand," Eur. J. For. Res., vol. 127, pp. 359-367, 2008.
25. L. Homolová et al., "Comparison of different ground techniques to map leaf area index of Norway spruce forest canopy," in Proc. 10th Int. Symp. Phys. Meas. Spectral Signatures Remote Sens. (ISPMSRS), Davos, Switzerland, 2007, pp. 499-504.
26. R. Pokorný and M. V. Marek, "Test of accuracy of LAI estimation by LAI-2000 under artificially changed leaf to wood area proportions," Biol. Plant., vol. 43, pp. 537-544, 2000.
27. S. Jacquemoud and F. Baret, "PROSPECT: A model of leaf optical properties spectra," Remote Sens. Environ., vol. 34, pp. 75-91, 1990.
28. Z. Malenovský et al., "Applicability of the PROSPECT model for Norway spruce needles," Int. J. Remote Sens., vol. 27, pp. 5315-5340, 2006.
29. L. Homolova, Z. Malenovský, Z. Lhotáková, V. Kaplan, and J. Hanuš, "Optical differences between sun exposed and shaded Norway spruce needles," in Proc. 5th Eur. Assoc. Remote Sens. Lab. (EARSeL) Workshop Imag. Spectrosc., Bruges, Belgium, 2007.
30. M. Rautiainen, P. Stenberg, and T. Nilson, "Estimating canopy cover in scots pine stands," Silva Fennica, vol. 39, pp. 137-142, 2005.
31. M. Mõttus and P. Stenberg, "A simple parameterization of canopy reflectance using photon recollision probability," Remote Sens. Environ., vol. 112, pp. 1545-1551, 2008.
32. P. Stenberg, P. Lukeš, M. Rautiainen, and T. Manninen, "A new approach for simulating forest albedo based on spectral invariants," Remote Sens. Environ., vol. 137, pp. 12-16, 2013.
33. A. Kuusk and T. Nilson, "A directional multispectral forest reflectance model," Remote Sens. Environ., vol. 72, pp. 244-252, 2000.
34. R. Pokorný and I. Tomáškova, "Allometric relationships for surface area and dry mass of young Norway spruce aboveground organs," J. For. Sci., vol. 53, pp. 548-554, 2007.
35. M. N. Merzlyak, T. B. MelÃ, and K. Razi Naqvi, "Estimation of leaf transmittance in the near infrared region through reflectance measurements," J. Photochem. Photobiol. B Biol., vol. 74, pp. 145-150, 2004.
36. Z. Malenovský et al., "A new hyperspectral index for chlorophyll estimation of a forest canopy: Area under curve Normalized to Maximal Band depth between 650-725 nm," in eProc. Eur. Assoc. Remote Sens. Lab. (EARSeL), 2006, vol. 5, pp. 161-172.
37. C. J. Willmott, "On the validation of models," Phys. Geogr., vol. 2, pp. 184-194, 1981.