NDLI: Estimating leaf AREA index of qinghai spruce forest in qilian mountain using quickbird satellite data

Content Provider	IEEE Xplore Digital Library
Author	Zhongren Nan Zhuanjun Zhao Chuanyan Zhao Xianglin Zheng
Copyright Year	2010
Description	Author affiliation: National Laboratory of Western China's Environmental System, Lanzhou University, 730000, China (Zhuanjun Zhao) \|\| Key Laboratory of Arid and Grassland Ecology with the Ministry of Education, Lanzhou University, 730000, China (Chuanyan Zhao; Xianglin Zheng) \|\| Environment Science Department, Lanzhou University, 730000, China (Zhongren Nan)
Abstract	Leaf area has important influence on the exchange of energy, water vapor and carbon dioxide between terrestrial ecosystems and the atmosphere. So, most distributed ecosystem process models that simulate carbon and hydrologic cycles require Leaf area index (LAI) as an input variable. However, there has been a lack of effective methods for its spatial estimation. Qinghai spruce (Picea crassifolia) is the dominant species in the forest ecosystem of Qilian Mountains and is critical to the eco-hydrological processes of the ecosystem. In this study, our objective is to retrieve the spatial distribution of canopy leaf area index of Qinghai spruce forests in the study area by QuickBird data. Generally, the canopy LAI was underestimated by instruments because of the clumping factor of conifer forests. In order to adjust the LAI measured and obtain the spatial distribution of LAI, the study was conducted as follows: First the clumping index of Qinghai spruce forest was measured by Tracing Radiation and Architecture of Canopies (TRAC). Then the adjusting coefficient was calculated by the clumping index, which was used to adjust LAI value measured by LAI-2000 canopy analyzer. Finally, the relationship between adjusted LAI and vegetation indexes retrieved by high resolution remote sensing data (QuickBird) was built to estimate the spatial distribution of canopy LAI of Qinghai spruce in the study. From the study, the conclusion can be drawn that LAI-2000 canopy analyzer underestimated the canopy LAI of the forest about 3.14–3.86 times. The statistical models between adjusted LAI and vegetation indexes (VIs) were built. Among them the optimal model, that is, relationship between NDVI and LAI, was selected through validating.
Starting Page	2055
Ending Page	2058
File Size	259870
Page Count	4
File Format	PDF
ISBN	9781424495658
ISSN	21537003
e-ISBN	9781424495665
e-ISBN	9781424495641
DOI	10.1109/IGARSS.2010.5650872
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Indexes Biological system modeling Vegetation mapping Soil Instruments Biomass Remote sensing Mountains Canopy leaf area index Qinghai spruce (Picea crassifolia) remote sensing data (QuickBird) Qilian
Content Type	Text
Resource Type	Article

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