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Journal of Applied Remote Sensing

Leaf area index estimation in semiarid mixed grassland by considering both temporal and spatial variations
Author(s): Zhaoqin Li; Xuling Guo
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Paper Abstract

Leaf area index (LAI) estimation in a mixed grassland ecosystem is limited by temporal and spatial variations controlled by land surface heterogeneity and ecological parameters. Therefore, simply estimated LAI usually has difficulty in meeting the requirements of the land surface–atmosphere interaction models. We estimated LAI based on the relationship between LAI and normalized difference vegetation index (NDVI) by considering temporal and spatial variations. Spatial variations of both LAI and NDVI were investigated using the Morlet wavelet approach. Based on the ground reflectance data, LAI estimation can be greatly improved by taking temporal and spatial variations into account. The coefficient of determination (r 2 ) values of the LAI-NDVI equations were increased by 0.28, 0.51, and 0.44 in the early, maximum, and late growing seasons, respectively. LAI estimation from SPOT 4/5 and Landsat TM 5 images confirmed the applicability of the proposed estimation approach.

Paper Details

Date Published: 7 May 2013
PDF: 18 pages
J. Appl. Remote Sens. 7(1) 073567 doi: 10.1117/1.JRS.7.073567
Published in: Journal of Applied Remote Sensing Volume 7, Issue 1
Show Author Affiliations
Zhaoqin Li, Univ. of Saskatchewan (Canada)
Xuling Guo, Univ. of Saskatchewan (Canada)


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