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

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Evaluation of leaf area index estimated from medium spatial resolution remote sensing data in a broadleaf deciduous forest in southern England, UK. / Ogutu, Booker; Dash, Jadunandan; Dawson, Terence P.

In: Canadian Journal of Remote Sensing, Vol. 37, No. 4, 2011, p. 333-347.

Research output: Contribution to journalArticle

Harvard

Ogutu, B, Dash, J & Dawson, TP 2011, '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, vol 37, no. 4, pp. 333-347.

APA

Ogutu, B., Dash, J., & Dawson, T. P. (2011). 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, 37(4), 333-347.

Vancouver

Ogutu B, Dash J, Dawson TP. 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. 2011;37(4):333-347.

Author

Ogutu, Booker; Dash, Jadunandan; Dawson, Terence P. / Evaluation of leaf area index estimated from medium spatial resolution remote sensing data in a broadleaf deciduous forest in southern England, UK.

In: Canadian Journal of Remote Sensing, Vol. 37, No. 4, 2011, p. 333-347.

Research output: Contribution to journalArticle

Bibtex - Download

@article{715470de4ac3430eafbbb16b01ea0605,
title = "Evaluation of leaf area index estimated from medium spatial resolution remote sensing data in a broadleaf deciduous forest in southern England, UK",
author = "Booker Ogutu and Jadunandan Dash and Dawson, {Terence P.}",
year = "2011",
volume = "37",
number = "4",
pages = "333--347",
journal = "Canadian Journal of Remote Sensing",
issn = "1712-7971",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Evaluation of leaf area index estimated from medium spatial resolution remote sensing data in a broadleaf deciduous forest in southern England, UK

A1 - Ogutu,Booker

A1 - Dash,Jadunandan

A1 - Dawson,Terence P.

AU - Ogutu,Booker

AU - Dash,Jadunandan

AU - Dawson,Terence P.

PY - 2011

Y1 - 2011

N2 - <p>Leaf area index (LAI) is a key biophysical variable influencing land surface fluxes. Different algorithms have been developed to estimate LAI from remote sensing data. This prompts the need for an evaluation of their comparability and performance. We present an evaluation of the comparability of four products (i.e., MODIS (MOD15A2), NNMERIS, CYCLOPES, and GLOBCARBON) and their performance against in situ LAI for an entire growing season in a broadleaf deciduous forest. All the LAI products detected the phenological trend of this biome reasonably accurately, albeit with differences in absolute values. The MODIS LAI was higher than the in situ LAI throughout the growing season whereas the GLOBCARBON LAI was higher in the summer months. The NN-MERIS was closest to the in situ measurements whereas the CYCLOPES product was lower than the in situ measurements. The NN-MERIS and CYCLOPES LAI were closely matched (RMSE = 0.45), whereas MODIS and CYCLOPES LAI were the most divergent (RMSE = 1.57). All the algorithms were significantly different (p &lt; 0.05) indicating a need for more efforts to harmonize these algorithms. Finally, the spatial consistency between the NN-MERIS LAI and in situ LAI revealed a season dependency trend. Better spatial agreement was observed during the summer season as opposed to early spring and autumn seasons.</p>

AB - <p>Leaf area index (LAI) is a key biophysical variable influencing land surface fluxes. Different algorithms have been developed to estimate LAI from remote sensing data. This prompts the need for an evaluation of their comparability and performance. We present an evaluation of the comparability of four products (i.e., MODIS (MOD15A2), NNMERIS, CYCLOPES, and GLOBCARBON) and their performance against in situ LAI for an entire growing season in a broadleaf deciduous forest. All the LAI products detected the phenological trend of this biome reasonably accurately, albeit with differences in absolute values. The MODIS LAI was higher than the in situ LAI throughout the growing season whereas the GLOBCARBON LAI was higher in the summer months. The NN-MERIS was closest to the in situ measurements whereas the CYCLOPES product was lower than the in situ measurements. The NN-MERIS and CYCLOPES LAI were closely matched (RMSE = 0.45), whereas MODIS and CYCLOPES LAI were the most divergent (RMSE = 1.57). All the algorithms were significantly different (p &lt; 0.05) indicating a need for more efforts to harmonize these algorithms. Finally, the spatial consistency between the NN-MERIS LAI and in situ LAI revealed a season dependency trend. Better spatial agreement was observed during the summer season as opposed to early spring and autumn seasons.</p>

UR - http://pubs.casi.ca/doi/abs/10.5589/m11-043

M1 - Article

JO - Canadian Journal of Remote Sensing

JF - Canadian Journal of Remote Sensing

SN - 1712-7971

IS - 4

VL - 37

SP - 333

EP - 347

ER -

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