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- Title
Forest canopy leaf area index in Maoershan Mountain: Ground measurement and remote sensing retrieval.
- Authors
Gao-long Zhu; Wei-min Ju; Chen, J. M.; Wen-yi Fan; Yan-lian Zhou; Xian-feng Li; Ming-ze Li
- Abstract
Leaf area index (LAI) is one of the most important structural parameters of terrestrial ecosystem, while the remote sensing retrieval and the ground optical instrument measurement and based on canopy gap model are the effective approaches to rapidly obtain LAI. However, these two approaches can only acquire effective LAI (LAIe) , due to the clumping of vegetation canopy. Taking the experimental forest farm of Northeast Forestry University at Maoershan Mountain in Hei-longjiang Province of Northeast China as study site, this paper measured the forest canopy LAIe by LAI2000, and estimated the LAI by the combination of TRAC (tracing radiation and architecture of canopies) measurement of foliage clumping index. A LAI remote sensing retrieval model was constructed through the analysis of the relationships between different vegetation indices calculated from Landsat5-TM and measured LAIe. The results showed that at the study site, the LAI of broad leaved forests was close to the LAIe, but the LAI of needle leaved forests was 27 % larger than the LAIe. Reduced simple ratio index ( RSR) had the highest relationship with measured LAIe(R =0. 763, n= 23) , which could be used as the best predictor of LAI. The LAI at study site increased rapidly with increasing elevation when the elevation was below 400 m, but had a slow increase when the elevation was from 400 m to 750 m. When the elevation was above 750 m, the LAI decreased. There was a significant correlation between the forest canopy LAI and aboveground biomass.
- Subjects
HEILONGJIANG Sheng (China); CHINA; LEAF area index; BIOTIC communities; REMOTE sensing; FOREST canopy gaps; FOREST biomass
- Publication
Yingyong Shengtai Xuebao, 2010, Vol 21, Issue 8, p2117
- ISSN
1001-9332
- Publication type
Article