Scale transformation of Leaf Area Index product retrieved from multiresolution remotely sensed data: Analysis and case studies

International Journal of Remote Sensing

Volumn 30, Issue 20, 2009, Pages 5383-5395

  Tao, Xin ^a,b   Yan, Binyan ^a   Wang, Kai ^c   Wu, Daihui ^a   Fan, Wenjie ^a   Xu, Xiru ^a   Liang, Shunlin ^b  

^a PEKING UNIVERSITY   (China)

^b UNIVERSITY OF MARYLAND   (United States)

^c BEIJING NORMAL UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

CLIMATE MODELS; IMAGE RESOLUTION; REFLECTION; REMOTE SENSING; VEGETATION;

HIGHER RESOLUTION IMAGES; HYBRID REFLECTANCE MODELS; LAND SURFACE PARAMETERS; REMOTE SENSING IMAGES; REMOTELY SENSED DATA; SCALE TRANSFORMATION; SPATIAL RESOLUTION; VEGETATION DISTRIBUTION;

METADATA;

ALGORITHM; IMAGE ANALYSIS; IMAGE RESOLUTION; LEAF AREA INDEX; MODIS; REMOTE SENSING; SATELLITE IMAGERY; SPATIAL RESOLUTION; SPOT;

EID: 70449392340     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431160903130978     Document Type: Article

References (24)

1. BONAN, G.B., POLLARD, D. and THOMPSON, S.L., 1993, Influence of subgrid-scale heterogeneity in leaf area index, stomatal resistance and soil moisture on grid-scale land-atmosphere interactions. Journal of Climatology, 6, pp. 1882-1897.
2. CHEN, J.M., 1999, Spatial scaling of a remotely sensed surface parameter by contexture. Remote Sensing of Environment, 69, pp. 30-42.
3. CHEN, J.M. and BLACK, T.A., 1992, Defining leaf area index for non-flat leaves. Plant Cell and Environment, 15, pp. 421-429.
4. FRIEDL, M.A., 1997, Examining the effects of sensor resolution and sub-pixel heterogeneity on vegetation spectral indices: implications for biophysical modelling. In Scale in Remote Sensing and GIS, D.A. Quattrochi and M.F. Goodchild (Eds), pp. 113-139 (Boca Raton, FL: Lewis).
5. GARRIGUES, S., ALLARD, D., BARET, F. and WEISS, M., 2006, Influence of landscape spatial heterogeneity on the non-linear estimation of leaf area index from moderate spatial resolution remote sensing data. Remote Sensing of Environment, 105, pp. 286-298.
6. HAPKE, B., 1981, Bidirectional reflectance spectroscopy: 1 Theory. Journal of Geophysical Research, 86, pp. 3039-3054.
7. JIN, H., TAO, X., FAN, W., XU, X., and LI, P., 2007a, Monitoring the spatial distribution of highresolution leaf area index using observations from DMC+4. In Proceedings of International Geoscience and Remote Sensing Symposium, 23-27 July 2007, Barcelona, Spain, pp. 3681-3684 (Institute of Electrical and Electronics Engineers).
8. JIN, H., TAO, X., FAN, W., XU, X., and LI, P., 2007b, Monitoring the spatial distribution of highresolution Leaf Area Index using DMC+4 image. Progress in Natural Science, 17, pp. 1229-1234 (in Chinese).
9. LACAZE, R. and ROUJEAN, J.L., 2001, G-function and HOt SpoT (GHOST) reflectance model application to multi-scale airborne POLDER measurements. Remote Sensing of Environment, 76, pp. 67-80.
10. LACAZE, R., CHEN, J., ROUJEAN, J.L., and LEBLANC, S.G., 2002, Retrieval of vegetation clumping index using hot spot signatures measured by POLDER instrument. Remote Sensing of Environment, 79, pp. 84-95.
11. LI, X. and STRAHLER, A.H., 1986, Geometric-optical bidirectional reflectance modeling of a coniferous forest canopy. IEEE Transactions on Geoscience and Remote Sensing, 24, pp. 906-919.
12. LIANG, S., 2000, Numerical experiments on the spatial scaling of land surface albedo and leaf area index. Remote Sensing Reviews, 19, pp. 225-242.
13. LIANG, S., 2004, Quantitative Remote Sensing of Land Surfaces (New Jersey: Wiley-Interscience).
14. LIU, X., FAN, W., TIAN, Q., and XU, X., 2008, Comparative analysis among different methods of leaf area index inversion. Acta Scientiarum Naturalium Universitatis Pekinensis, 44, pp. 827-834.
15. LIU, Z., WANG, C. and LUO, C., 2004, Estimation of CBERS-1 point spread function and image restoration. Journal of Remote Sensing, 8, pp. 234-237.
16. NILSON, T. and KUUSK, A., 1989, A reflectance model for the homogeneous plant canopy and its inversion. Remote Sensing of Environment, 27, pp. 157-167.
17. RASTETTER, E.B., KING, A.W., COSBY, B.J., HORNBERGER, G.M., O'NEILL, R.V. and HOBBIE, J.E., 1992, Aggregating fine-scale ecological knowledge to model coarser-scale attributes of ecosystems. Ecological Applications, 2, pp. 55-70.
18. TAO, X., YAN, B., WU, D., FAN, W., and XU, X., 2008, A scale transform method for Leaf Area Index retrieved from multi-resolutions remote sensing data. In Proceedings of the 8th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, J. Zhang and M.F. Goodchild (Eds.), 25-27 June 2008, Shanghai, China, pp. 176-182 (World Academic Union Ltd).
19. TIAN, Y.H., WOODCOCK, C.E. and WANG Y.J., 2002, Multiscale analysis and validation of the MODIS LAI product I. Uncertainty assessment. Remote Sensing of Environment, 83, pp. 414-430.
20. TOWNSHEND, J.R.G. and JUSTICE, C.O., 1988, Selecting the spatial resolution of satellite sensors required for global monitoring of land transformations. International Journal of Remote Sensing, 9, pp. 187-236.
21. VERMOTE, E.F., TANRE, D., DEUZE, J.L., HERMAN, M., and MORCRETTE, J.J., 1997, Second simulation of the satellite signal in the solar spectrum, 6S: An overview. IEEE Transactions on Geoscience and Remote Sensing, 35, pp. 675-686.
22. WALSH, S.J., MOODY, A., ALLEN, T.R., and BROWN, D.G., 1997, Scale dependence of NDVI and its relationship to mountainous terrain. In Scale in Remote Sensing and GIS, D.A. Quattrochi and M.F. Goodchild (Eds), pp. 27-55 (Boca Raton, FL: Lewis).
23. XU, X., 2005, Physics of Remote Sensing, pp. 47-49 (Bejing: Peking University).
24. XU, X., FAN, W. and TAO, X., 2009, The spatial scaling effect of continuous canopy Leaves Area Index retrieved by remote sensing. Science in China Series D-Earth Sciences, 52, pp. 393-401.