Error and quality assessment for remotely sensed estimates of leaf area index

Canadian Journal of Remote Sensing

Volumn 35, Issue 2, 2009, Pages 141-151

  McAllister, D M ^a   Valeo, C ^a  

^a UNIVERSITY OF CALGARY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ESTIMATION; FORESTRY; IMAGE RECONSTRUCTION; INTELLIGENT SYSTEMS; MONTE CARLO METHODS; PLANTS (BOTANY); RADIOMETERS; REMOTE SENSING; SATELLITE IMAGERY; SENSITIVITY ANALYSIS;

LINEAR SPECTRAL MIXTURE ANALYSIS; MODERATE RESOLUTION IMAGING SPECTRORADIOMETER DATUM; MULTI SCALE ANALYSIS; REMOTE SENSING DATA; SATELLITE POUR L'OBSERVATION DE LA TERRE; SENSITIVITY TO VARIATIONS; SPATIAL STATISTICAL ANALYSIS; SPECTRAL VEGETATION INDICES;

QUALITY CONTROL;

EID: 77952749573     PISSN: 07038992     EISSN: 17127971     Source Type: Journal    
DOI: 10.5589/m09-004     Document Type: Article

References (21)

1. Bailey, T., and Gatrell, A. 1995. Interactive spatial data analysis. Pearson Education Press, Harlow, Essex, UK.
2. Baret, F., and Guyot, G. 1991. Potentials and limits of spectral vegetation indices for LAI and APAR assessment. Remote Sensing of Environment, Vol. 35, pp. 161-173.
3. Bonan, G. 1993. Importance of LAI and forest type when estimating photosynthesis in boreal forests. Remote Sensing of Environment, Vol. 43, pp. 303-314.
4. Brown, L., Chen, J., Leblanc, S., and Cihlar, J. 2000. A shortwave infrared modification to the simple ratio for LAI retrieval in boreal forests: an image and model analysis. Remote Sensing of Environment, Vol. 71, pp. 16-25.
5. Chen, J. 1996. Evaluation of spectral vegetation indices and a modified simple ratio for boreal applications. CanadianJournal ofRemote Sensing, Vol. 22, No. 3, pp. 229-242.
6. Eklundh, L., Harrie, L., and Kuusk, A. 2001. Investigating relationships between Landsat ETM+ sensor data and LAI in a boreal conifer forest. Remote Sensing of Environment, Vol. 78, pp. 239-251.
7. Eklundh, L., Hall, K., Eriksson, H., Ardo, J., and Pilesjo, P. 2003. Investigating the use of Landsat thematic mapper data for estimation of forest LAI in southern Sweden. Canadian Journal of Remote Sensing, Vol. 29, No. 3, pp. 349-362.
8. Franklin, S., Lavigne, M., Deuling, M., Wulder, M., and Hunt, E. 1997. Estimation of forest LAI using remote sensing and GIS data for modeling net primary production. International Journal ofRemote Sensing, Vol. 18, No. 16, pp. 3459-3471.
9. Hu, B., Miller, J., Chen, J., and Hollinger, A. 2004. Retrieval of the canopy LAI in the BOREAS flux tower sites using linear spectral mixture analysis. Remote Sensing of Environment, Vol. 89, pp. 176-188.
10. Kergoat, L. 1998. Model for hydrological equilibrium of LAI on a global scale. Journal of Hydrology, Vol. 212-213, pp. 268-286.
11. Leblanc, S., Chen, J., and Kwong, M. 2002. Tracing radiation and architecture of canopies: TRAC manual 2.1.3. Canada Centre for Remote Sensing, Natural Resources Canada, Ottawa, Ont. 25 pp.
12. McAllister, D.M., and Valeo, C. 2007. Introduction to a new robust method for the remote estimation of LAI in montane and boreal forests. International Journal of Remote Sensing, Vol. 28, No. 7-8, pp. 1891-1905.
13. Nemani, R., Pierce, L., Running, S., and Band, L. 1993. Forest ecosystem processes at the watershed scale: sensitivity to remotely-sensed LAI estimates. International Journal of Remote Sensing, Vol. 14, No. 13, pp. 2519-2534.
14. Peddle, D., and Johnson, R. 2000. Spectral mixture analysis of airborneremote sensing imagery for improved prediction of LAI in mountainous terrain, Kananaskis, Alberta. Canadian Journal of Remote Sensing, Vol. 26, No. 3, pp. 177-188.
15. Peddle, D., Hall, F., and LeDrew, E. 1999. Spectral mixture analysis and geometric-optical reflectance modeling of boreal forest biophysical structure. Remote Sensing of Environment, Vol. 67, pp. 288-297.
16. Peddle, D., Brunke, S., and Hall, F. 2001. A comparison of spectral mixture analysis and ten spectral vegetation indices for estimating boreal forest biophysical information from airborne data. Canadian Journal of Remote Sensing, Vol. 27, No. 6, pp. 627-635.
17. Rock, B.N., Vogelmann, J.E., Williams, D.L., Vogelmann, A.F., and Hoshizaki, T. 1986. Remote detection of forest damage. BioScience, Vol. 36, No. 7, pp. 439-445.
18. Running, S., and Coughlan, J. 1988. A general model of forest ecosystem processes for regional applications. I. Hydrologic balance, canopy gas exchange and primary production processes. Ecological Modeling, Vol. 42, pp. 125-154.
19. Running, S., and Gower, S. 1991. FOREST-BGC, a general model of forest ecosystem processes for regional applications: II. Dynamic carbon allocation and nitrogen budgets. Tree Physiology, Vol. 9, pp. 147-160.
20. Seed, E., and King, D. 2003. Shadow brightness and shadow fraction relations with effective LAI: importance of canopy closure and view angle in mixedwood boreal forest. Canadian Journal of Remote Sensing, Vol. 29, No. 3, pp. 324-335.
21. Spanner, M., Pierce, L., Peterson, D., and Running, S. 1990. Remote sensing of temperate coniferous forest LAI: the influence of canopy closure, understory vegetation and background reflectance. International Journal of Remote Sensing, Vol. 11, No. 1, pp. 95-111.