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)
机构:
Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
Joint Ctr Global Change Studies, Beijing 100875, Peoples R ChinaChinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
Zeng, Yelu
Li, Jing
论文数: 0引用数: 0
h-index: 0
机构:
Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
Joint Ctr Global Change Studies, Beijing 100875, Peoples R ChinaChinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
Li, Jing
Liu, Qinhuo
论文数: 0引用数: 0
h-index: 0
机构:
Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
Joint Ctr Global Change Studies, Beijing 100875, Peoples R ChinaChinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
Liu, Qinhuo
Qu, Yonghua
论文数: 0引用数: 0
h-index: 0
机构:
Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R ChinaChinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
Qu, Yonghua
Huete, Alfredo R.
论文数: 0引用数: 0
h-index: 0
机构:
Univ Technol Sydney, Plant Funct Biol & Climate Change Cluster C3, Sydney, NSW 2007, AustraliaChinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
Huete, Alfredo R.
Xu, Baodong
论文数: 0引用数: 0
h-index: 0
机构:
Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R ChinaChinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
Xu, Baodong
Yin, Geofei
论文数: 0引用数: 0
h-index: 0
机构:
Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R ChinaChinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
Yin, Geofei
Zhao, Jing
论文数: 0引用数: 0
h-index: 0
机构:
Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R ChinaChinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China