A modeling approach for studying forest chlorophyll content in relation to canopy composition

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives

Volumn 37, Issue , 2008, Pages 25-30

  Verrelst, J ^a   Schaepman, M E ^a   Clevers, J G P W ^a  

^a WAGENINGEN UNIVERSITY   (Netherlands)

Author keywords

Canopy structure; Chlorophyll content; FLIGHT; Non Photosynthetic Vegetation; PROSPECT; Woody elements

Indexed keywords

CHLOROPHYLL; RADIATIVE TRANSFER; REMOTE SENSING;

CANOPY STRUCTURE; CHLOROPHYLL CONTENTS; FLIGHT; NON-PHOTOSYNTHETIC VEGETATION; PROSPECT;

FORESTRY;

EID: 84893652489     PISSN: 16821750     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (28)

1. Asner, G.P. 1998. Biophysical and biochemical sources of variability in canopy reflectance. Remote Sensing of Environment, 64(3), pp. 234-253.
2. Asner, G.P., Townsend, A.R., Bustamante, M.M.C., Nardoto, G.B. & Olander, L.P. 2004. Pasture degradation in the central Amazon: Linking changes in carbon and nutrient cycling with remote sensing. Global Change Biology, 10(5), pp. 844-862.
3. Barnsley, M.J., Settle, J.J., Cutter, M.A., Lobb, D.R. & Teston, F. 2004. The PROBA/CHRIS mission: A low-cost smallsat for hyperspectral multiangle observations of the earth surface and atmosphere. IEEE Transactions on Geoscience and Remote Sensing, 42(7), pp. 1512-1520.
4. Bowyer, P. & Danson, F.M. 2004. Sensitivity of spectral reflectance to variation in live fuel moisture content at leaf and canopy level. Remote Sensing of Environment, 92(3), pp. 297-308.
5. Carter, G.A. & Knapp, A.K. 2001. Leaf optical properties in higher plants: Linking spectral characteristics to stress and chlorophyll concentration. American. Journal of Botany., 88(4), pp. 67-684.
6. Chen, J.M., Pavlic, G., Brown, L., Cihlar, J., Leblanc, S.G., White, H.P., Hall, R.J., Peddle, D.R., King, D.J., Trofymow, J.A., Swift, E., Van Der Sanden, J. & Pellikka, P.K.E. 2002. Derivation and validation of Canada-wide coarse-resolution leaf area index maps using high-resolution satellite imagery and ground measurements. Remote Sensing of Environment, 80(1), 165-184.
7. Franklin, J.F., Spies, T.A., Pelt, R.V., Carey, A.B., Thornburgh, D.A., Berg, D.R., Lindenmayer, D.B., Harmon, M.E., Keeton, W.S., Shaw, D.C., Bible, K. & Chen, J. 2002. Disturbances and structural development of natural forest ecosystems with silvicultural implications, using Douglas-fir forests as an example. Forest Ecology and Management, 155(1-3), pp. 399-423.
8. Gitelson, A. & Merzlyak, M.N. 1994. Spectral relfectance changes associated with autumn senescence of Aesculus hippocastanum L. and Acer platanoides L. leaves. Spectral features and relation to chlorophyll estimation. Journal of Plant Physiology, 143(3), pp. 286-292.
9. Jach, M.E. & Ceulemans, R. 2000. Effects of season, needle age and elevated atmospheric CO2 on photosynthesis in Scots pine (Pinus sylvestris). Tree Physiology, 20(3), pp. 145-157.
10. Jacquemoud, S., Bacour, C., Poilve, H. & Frangi, J.P. 2000. Comparison of four radiative transfer models to simulate plant canopies reflectance: Direct and inverse mode. Remote Sensing of Environment, 74(3), pp. 471-481.
11. Jacquemoud, S., Ustin, S.L., Verdebout, J., Schmuck, G., Andreoli, G. & Hosgood, B. 1996. Estimating leaf biochemistry using the PROSPECT leaf optical properties model. Remote Sensing of Environment, 56(3), pp. 194-202.
12. Jonasova, M. & Prach, K. 2004. Central-European mountain spruce (Picea abies (L.) Karst.) forests: Regeneration of tree species after a bark beetle outbreak. Ecological Engineering, 23(1), 15-27.
13. Jia, G.J., Burke, I.C., Goetz, A.F.H., Kaufmann, M.R. & Kindel, B.C. 2006. Assessing spatial patterns of forest fuel using AVIRIS data. Remote Sensing of Environment, 102(3-4), pp. 318-327.
14. Hapke, B. 1981. Bidirectional reflectance spectroscopy. 1. Theory. Journal of Geophysical Research., 86(4B), 3039-3054.
15. th International Symposium on Physical Measurements and Signatures in Remote Sensing, ISPMSRS 2007, Davos, Switserland, 12.3-14.3.2007
16. Kötz, B., Morsdorf, F., Itten, K., Schaepman, M., Bowyer, P. & Allgöwer, B. 2004. Radiative transfer modeling within a heterogeneous canopy for estimation of forest fire fuel properties. Remote Sensing of Environment, 92(3), pp. 332-344.
17. Malenovsky, Z., Martin, E., Homolova, L., Gastellu-Etchegorry, J.P., Zurita-Milla, R., Schaepman, M.E., Pokorny, R., Clevers, J.G.P.W. & Cudlin, P. 2008. Influence of woody elements of a Norway spruce canopy on nadir reflectance simulated by the DART model at very high spatial resolution. Remote Sensing of Environment, 112(1), pp. 1-18.
18. North, P.R.J. 1996. Three-dimensional forest light interaction model using a Monte Carlo method. Ieee Transactions on Geoscience and Remote Sensing, 34(4), pp. 946-956.
19. Radeloff, V.C., Mladenoff, D.J. & Boyce, M.S. 1999. Detecting jack pine budworm defoliation using spectral mixture analysis: Separating effects from determinants. Remote Sensing of Environment, 69(2), pp. 156-169.
20. Rautiainen, M., Stenberg, P., Nilson, T. & Kuusk, A. 2004. The effect of crown shape on the reflectance of coniferous stands. Remote Sensing of Environment, 89(1), pp. 41-52.
21. Siitonen, J. 2001. Forest management, coarse woody debris and saproxylic organisms: Fennoscandian boreal forests as an example. Ecological Bulletins, 49, pp. 11-41.
22. Sims, D.A. & Gamon, J.A. 2002. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages. Remote Sensing of Environment, 81(2-3), 337-354.
23. Song, C. & Woodcock, C.E. 2002. The spatial manifestation of forest succession in optical imagery: The potential of multiresolution imagery. Remote Sensing of Environment, 82(2-3), pp. 271-284.
24. Thomas, J.R. & Gausman, H.W. 1977. Leaf reflectance vs. leaf chlorophyll and carotenoid concentrations for eight crops. Agronomy Journal, 69, 799-802.
25. Trotter, G.M., Whitehead, D. & Pinkney, E.J. 2002. The photochemical reflectance index as a measure of photosynthetic light use of efficiency for plants with varying foliar nitrogen contents. International Journal of Remote Sensing, 23(6), pp. 1207-1212.
26. Ustin, S.L., Roberts, D.A., Gamon, J.A., Asner, G.P. & Green, R.O. 2004. Using imaging spectroscopy to study ecosystem processes and properties. BioScience, 54(6), pp. 523-534.
27. Verrelst, J., Schaepman, M.E., Koetz, B. & Kneubuhler, M. 2008. Angular sensitivity analysis of vegetation indices derived from CHRIS/PROBA data. Remote Sensing of Environment, 112(5), pp. 2341-2353.
28. White, J.C., Wulder, M.A., Brooks, D., Reich, R. & Wheate, R.D. 2005. Detection of red attack stage mountain pine beetle infestation with high spatial resolution satellite imagery. Remote Sensing of Environment, 96(3-4), 340-351.