Leaf area index estimation in semiarid mixed grassland by considering both temporal and spatial variations

被引:2
作者
Zhaoqin [1 ]
Guo, Xulin [1 ]
机构
[1] Univ Saskatchewan, Dept Geog & Planning, Saskatoon, SK S7N 5C8, Canada
来源
JOURNAL OF APPLIED REMOTE SENSING | 2013年 / 7卷
基金
加拿大自然科学与工程研究理事会;
关键词
leaf area index estimation; temporal variation; spatial variation; semiarid mixed grassland; VEGETATION; MODEL; ECOSYSTEMS; SCALE; MAPS; DERIVATION; INVERSION; VARIABLES; ALGORITHM; RADIATION;
D O I
10.1117/1.JRS.7.073567
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)
引用
收藏
页数:17
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