Evaluation of leaf area index estimated from medium spatial resolution remote sensing data in a broadleaf deciduous forest in southern England, UK

Canadian Journal of Remote Sensing

Volumn 37, Issue 4, 2012, Pages 333-347

  Ogutu, Booker ^a   Dash, Jadunandan ^a   Dawson, Terence P ^b  

^a UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

^b UNIVERSITY OF DUNDEE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

RADIOMETERS; REMOTE SENSING; SURFACE MEASUREMENT;

BIO-PHYSICAL VARIABLES; BROADLEAF DECIDUOUS FORESTS; ENGLAND; GROWING SEASON; IN-SITU MEASUREMENT; LAND SURFACE FLUXES; LEAF AREA INDEX; PERFORMANCE; REMOTE SENSING DATA; SPATIAL RESOLUTION;

FORESTRY;

ALGORITHMS; FORESTRY; PHENOLS; REMOTE SENSING;

EID: 84870027158     PISSN: 07038992     EISSN: 17127971     Source Type: Journal    
DOI: 10.5589/m11-043     Document Type: Article

References (53)

1. Abuelgasim A.A., Fernandes, R.A., and Leblanc, G.S. 2006. Evaluation of national and global LAI products derived from optical remote sensing instruments over Canada. IEE Transactions on Geoscience and Remote Sensing, Vol. 44, pp. 1872-1884. doi: 10.1109/TGRS.2006. 874794.
2. Ahl, D.E., Gower, S.T., Burrows, S.N., Shabanov, N.V, Myneni, R.B., and Knyazikhin, Y. 2006. Monitoring spring canopy phenology of a deciduous broadleaf forest using MODIS. Remote Sensing of Environment, Vol. 104, pp. 88-95. doi: 10.1016/j.rse.2006.05.003.
3. Aragao, L.E.O.C., Shimabukuro, YE., Espirito-Santo, F.D.B., and Williams, M. 2005. Spatial validation of collection 4 MODIS LAI product in Eastern Amazon. IEEE Transactions on Geoscience and Remote Sensing, Vol. 43, pp. 2526-2534. doi: 10.1109/TGRS.2005.856632.
4. Bacour, C., Baret, F., Beal, D., Weiss, M., and Pavageau, K. 2006. Neural network estimation of LAI, fAPAR, fCover and LAI x Cab, from top of canopy meris reflectance data: Principles and validation. Remote Sensing of Environment, Vol. 105, pp. 313-325. doi: 10.1016/j.rse.2006.07.014.
5. Baret, F., Hagolle, O., Geiger, B., Bicheron, P, Miras, B., Huc, M., Berthelot, B., Nino, F., Weiss, M., Samain, O., Roujean, J.L., and Leroy, M. 2007. LAI, fAPAR and fCover cyclopes global products derived from vegetation: Part 1: Principles of the algorithm. Remote Sensing of Environment, Vol. 110, pp. 275-286. doi: 10.1016/j.rse. 2007.02.018.
6. Bartholome, E., and Belward, A.S. 2005. GLC2000: a new approach to global land cover mapping from Earth observation data. International Journal of Remote Sensing, Vol. 26, pp. 1959-1977. doi: 10.1080/01431160412331291297.
7. Breda, J.J.N. 2003. Ground-based measurements of leaf area index: a review of methods, instruments and current controversies. Journal of Experimental Botany, Vol. 54, No. 392, pp. 2403-2417. doi: 10.1093/jxb/erg263.
8. Buermann, W, Dong, J., Zeng, X., Myneni, R.B., and Dickson, R.E. 2001. Evaluation of the utility of satellite-based vegetation leaf area index data for climate simulations. Journal of Climate, Vol. 14, pp. 3536-3550.
9. Canisius, F., Fernandes, R., and Chen, J. 2010. Comparison and evaluation of medium resolution imaging spectrometer leaf area index products across a range of land use. Remote Sensing of Environment, Vol. 114, pp. 950-960. doi: 10.1016/j.rse.2009.12.010.
10. Chen, J.M., and Black, T.A. 1992. Defining leaf area index for non-flat leaves. Plant, Cell and Environment, Vol. 15, pp. 421-429. doi: 10.1111/j.1365-3040.1992.tb00992.x.
11. Chen, J.M., and Cihlar, J. 1995. Plant canopy gap-size analysis theory for improving optical measurements of leaf-area index. Journal of Applied Optics, Vol. 34, pp. 6211-6222. doi: 10.1364/AO.34.006211.
12. Chen, J.M., and Cihlar, J. 1996. Retrieveing leaf area index for boreal conifer forests using Landsat TM images. Remote Sensing of Environment, Vol. 55, pp. 153-162. doi: 10.1016/0034-4257(95) 00195-6.
13. Chen, J.M. 1996. Optically-based methods for measuring seasonal variation of leaf area index in boreal conifer stands. Agricultural and Forest Meteorology, Vol. 80, pp. 135-163. doi: 10.1016/0168-1923(95) 02291-0.
14. Chen, J.M., and Leblanc, S.G. 2001. Multiple-scattering scheme useful for geometric optical modeling. Geoscience and Remote Sensing, IEEE Transactions on, Vol. 39, pp. 1061-1071. doi: 10.1109/36.921424.
15. Chen, J.M., Menges, C.H., and Leblanc, S.G. 2005. Global mapping of foliage clumping index using multi-angular satellite data. Remote Sensing of Environment, Vol. 97, pp. 447-457. doi: 10.1016/j.rse.2005. 05.003.
16. Cohen, W.B., and Justice, C.O. 1999. Validating MODIS terrestrial ecology products linking in situ and satellite measurements. Remote Sensing of Environment, Vol. 70, pp. 1-3. doi: 10.1016/S0034-4257(99) 00053-X.
17. Dawson, T.P., North, PR.J., Plummer, S.E., and Curran, PJ. 2003. Forest ecosystem chlorophyll content: Implications for remotely sensed estimates of net primary productivity. International Journal of Remote Sensing, Vol. 24, pp. 611-618. doi: 10.1080/01431160304984.
18. Decagon Devices 1994. Sunfleck ceptometer manual. Decagon, Incorporated, Pullman, Wash.
19. Deng, D., Chen, J.M., Plummer, S., Chen, M., and Pisek, J. 2006. Global LAI algorithm integrating the bidirectional information. IEEE Transactions on Geoscience and Remote Sensing, Vol. 44, pp. 2219-2229. doi: 10.1109/TGRS.2006.872100.
20. Fassnacht, K.S., Gower, S.T., Norman, J.M., and Mcmurtric, R.E. 1994. A comparison of optical and direct methods for estimating foliage surface area index in forests. Agricultural and Forest Meteorology, Vol. 71, pp. 183-207. doi: 10.1016/0168-1923(94)90107-4.
21. Fernandes, R., and Leblanc, G.S. 2005. Parametric (modified least squares) and non-parametric (Theil-Sen) linear regressions for predicting biophysical parameters in the presence of measurement errors. Remote Sensing of Environment, Vol. 95, pp. 303-316. doi: 10.1016/j.rse.2005. 01.005.
22. Garrigues, S., Lacaze, R., Baret, F., Morisette, J.T., Weiss, M., Nickeson, J.E., Fernandes, R., Plummer, S., Shabanov, N.V, Myneni, R.B., Knyazikhin, Y, and Yang, W 2008. Validation and intercomparison of global leaf area index products derived from remote sensing data. Journal of Geophyisical Research, Vol. 113, G02028.
23. Gobron, N., and Verstraete, M.M. 2009. Assessment of the status of the development of the standard for the terrestrial essential climate variables: Leaf area index (LAI). GTOS secretariat Food and Agriculture Organization (FAO), Rome (ITALY) GTOS 66.
24. Gower, S.T., Kucharik, C.J., and Norman, J.M. 1999. Direct and indirect estimation of leaf area index, fapar, and net primary production of terrestrial ecosystems. Remote Sensing of Environment, Vol. 70, pp. 2951. doi: 10.1016/S0034-4257(99)00056-5.
25. Jacquemoud, S., and Baret, F. 1990. Prospect: A model of leaf optical properties spectra. Remote Sensing of Environment, Vol. 34, pp. 75-91. doi: 10.1016/0034-4257(90)90100-Z.
26. Jonckheere, I., Fleck, S., Nackaerts, K., Muys, B., Coppin, P., Weiss, M., and Baret, F. 2004. Review of methods for in situ leaf area index determination: Part I. Theories, sensors and hemispherical photography. Agricultural and Forest Meteorology, Vol. 121, pp. 19-35. doi: 10.1016/j.agrformet.2003.08.027.
27. Knyazikhin, Y, Martonchik, J.V, Myneni, R.B., Diner, D.J., and Running, S.W 1998. Synergistic algorithm for estimating vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from MODIS and MISR data. Journal of Geophyisical Research, Vol. 103, pp. 257-276. doi: 10.1029/97JA02771.
28. Leblanc S.G., Chen, J.M., and Kwong, M. 2005. Tracing radiation and architecture of canopies manual version 2.1.4. Natural Resources Canada.
29. Li-Cor 1991. LAI-2000 Plant canopy analyzer operating manual. Lincoln. Neb.
30. Morisette, J.T., Baret, F., Privette, J.L., Myneni, R.B., Nickeson, J.E., Garrigues, S., Shabanov, N.V, Weiss, M., Fernandes, R.A., Leblanc, S.G., Kalacska, M., Sanchez-Azofeifa, G.A., Chubey, M., Rivard, B., Stenberg, P, Rautiainen, M., Voipio, P, Manninen, T., Pilant, A.N., Lewis, T.E., Iiames, J.S., Colombo, R., Meroni, M., Busetto, L., Cohen, W.B., Turner, D.P, Warner, E.D., Petersen, G.W, Seufert, G., and Cook, R. 2006. Validation of global moderate-resolution LAI products: A framework proposed within the CEOS land product validation subgroup, IEEE Transactions on. Geoscience and Remote Sensing, Vol. 44, pp. 1804-1817.
31. Myneni, R.B., Hoffman, S., Knyazikhin, Y, Privette, J.L., Glassy, J., Tian, Y, Wang, Y, Song, X., Zhang, Y, Smith, G.R., Lotsch, A., Friedl, M., Morisette, J.T., Votava, P, Nemani, R.R., and Running, S.W. 2002. Global products of vegetation leaf area and fraction absorbed par from year one of modis data. Remote Sensing of Environment, Vol. 83, pp. 214-231. doi: 10.1016/S0034-4257(02)00074-3.
32. Patenaude G., Milne R., and Dawson T.P 2005. Synthesis of remote sensing approaches for forest carbon estimation: reporting to the Kyoto Protocol. Environmental Science and Policy, Vol. 8 pp. 161-178. doi: 10.1016/j.envsci.2004.12.010.
33. Pisek, J., and Chen, J.M. 2007. Comparison and validation of modis and vegetation global LAI products over four bigfoot sites in North America. Remote Sensing of Environment, Vol. 109, pp. 81-94. doi: 10.1016/j.rse.2006.12.004.
34. Plummer, S., Arino, O., Ranera, F., Tansey, K., Chen J., and Dedieu G., 2007. An update on the GlobCarbon Initiative: Multi-sensor estimation of global biophysical products for global terrestrial carbon studies, Proceedings ENVISAT Symposium, 23-27 April 2007, Montreux, Switzerland.
35. Rahman, H., and Dedieu, G. 1994. SMAC: A simplified method for the atmospheric correction of satellite measurements in the solar spectrum. International Journal of Remote Sensing, Vol. 15, pp. 123-143. doi: 10.1080/01431169408954055.
36. Riario, D., Valladares, F., Condes, S., and Chuvieco, E. 2004. Estimation of leaf area index and covered ground from airborne laser scanner (Lidar) in two contrasting forests. Agricultural and Forest Meteorology, Vol. 124, pp. 269-275. doi: 10.1016/j.agrformet.2004.02.005.
37. Rich, P.M. 1990. Characterizing plant canopies with hemispherical photographs. Remote Sensing Reviews, Vol. 5, pp. 13-29. doi: 10.1080/02757259009532119.
38. Richardson, J.J., Moskal, M.L., and Kim, S.-H. 2009. Modelling approaches to estimate effective leaf area index from aerial discrete-return LIDAR. Agricultural and Forest Meteorology, Vol. 149, pp. 1152-1160. doi: 10.1016/j.agrformet.2009.02.007.
39. Saunier, S., and Goryl, P 2004. MERIS absolute geo location status. European Space Agency, ESRIN, ITALY, No. 15993/02/I-LG.
40. Seller, P.J. 1987. Canopy reflectance photosynthesis and transpiration II. The role of biophysics in the linearity of their interdependence. Remote Sensing of Environment, Vol. 21, pp. 143-183. doi: 10.1016/0034-4257(87)90051-4.
41. Sen, PK. 1968. Estimate of the regression coefficient based on Kendall’s tau. Journal of American Statistical Association, vol. 63, pp. 1379-1389. doi: 10.2307/2285891.
42. Shabanov, N.V., Huang, D., Yang, WZ., Tan, B., Knyazikhin, Y., Myneni, R.B., Ahl, D.E., Gower, S.T., Huete, A.R., Aragao, L., and Shimabukuro, Y.E. 2005. Analysis and optimization of the MODIS leaf area index algorithm retrievals over broadleaf forests. IEEE Transactions on Geoscience and Remote Sensing, Vol. 43, pp. 1855-1865. doi: 10.1109/TGRS.2005.852477.
43. Solberg, S., Nssset, E., Hanssen, K.H., and Christiansen, E. 2006. Mapping defoliation during a severe insect attack on pine using airborne laser scanning. Remote Sensing of Environment, Vol. 102, pp. 364-376. doi: 10.1016/j.rse.2006.03.001.
44. Sylvander, S., Albert-Grousset, I., and Henry, P. 2003. Geometrical performances of the VEGETATION products. IGRASS 2003, CD, IEEE, Toulouse, France.
45. Theil, H. 1950. A rank-invariant method of linear and polynomial regression analysis. Indagationes Mathematicae, Vol. 12, pp. 85-91.
46. Tian, Y, Woodcock, C.E., Wang, Y, Privette, J.L., Shabanov, N.V., Zhou, L., Zhang, Y, Buermann, W., Dong, J., Veikkanen, B., Hame, T., Andersson, K., Ozdogan, M., Knyazikhin, Y., and Myneni, R.B. 2002. Multiscale analysis and validation of the MODIS LAI: I. Uncertainty assessment. Remote Sensing of Environment, Vol. 83, pp. 414-430. doi: 10.1016/S0034-4257(02)00047-0.
47. Verhoef, W 1984. Light scattering by leaf layers with application to canopy reflectance modelling: The SAIL model. Remote Sensing of Environment, Vol. 16, pp. 125-141. doi: 10.1016/0034-4257(84)90057-9.
48. Wang, Q., Tenhunen, J., Dinh, N.Q., Reichstein, M., Otieno, D., Granier, A., and Pilegarrd, K. 2005. Evaluation of seasonal variation of modis derived leaf area index at two European deciduous broadleaf forest sites. Remote Sensing of Environment, Vol. 96, pp. 475-484. doi: 10.1016/j.rse.2005.04.003.
49. Wang, Y, Woodcock, C.E., Buermann, W, Stenberg, P, Voipio, P, Smolander, H., Hame, T., Tian, Y., Hu, J., Knyazikhin, Y., and Myneni, R.B. 2004. Evaluation of the MODIS LAI algorithm at a coniferous forest site in Finland. Remote Sensing of Environment, Vol. 91, pp. 114-127. doi: 10.1016/j.rse.2004.02.007.
50. Weiss, M., Baret, F., Garrigues, S., and Lacaze, R. 2007. LAI andfAPAR CYCLOPES global products derived from vegetation. Part 2: Validation and comparison with MODIS collection 4 products. Remote Sensing of Environment, Vol. 110, pp. 317-331. doi: 10.1016/j.rse.2007.03.001.
51. Weiss, M., Baret, F., Smith, G.J., Jonckheere, I., and Coppin, P. 2004. Review of methods for in situ leaf area index (LAI) determination: Part II. Estimation of LAI, errors and sampling. Agricultural and Forest Meteorology, Vol. 121, pp. 37-53. doi: 10.1016/j.agrformet.2003. 08.001.
52. Wilcox R.R. 2004. Some results on extensions and modifications of the Theil-Sen regression estimator. British Journal of Mathematical and Statistical Psychology, Vol. 57, pp. 265-280. doi: 10.1348/000711004 2307230.
53. Wolfe, R.E., Nishihama, M., Fleig, A.J., Kuyper, J.A., Roy, D.P, Storey, J.C., and Patt, F.S. 2002. Achieving sub-pixel geolocation accuracy in support of MODIS land science. Remote Sensing of Environment, Vol. 83, pp. 31-49. doi: 10.1016/S0034-4257(02)00085-8.