Assessing Performance of Leaf Area Index in a Monitored Mountain Ecosystem on Mount Elgon-Uganda

2017 ◽

Vol 8 (1) ◽

pp. 64-80 ◽

Cited By ~ 1

Author(s):

Tonny Oyana ◽

Ellen Kayendeke ◽

Samuel Adu-Prah

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Global Climate ◽

Field Measurements ◽

Area Index ◽

Temporal Differences ◽

Mountain Ecosystem ◽

Mount Elgon

This study investigated the performance of leaf area index (LAI) and photosynthetically active radiation (PAR) in a mountain ecosystem. The authors hypothesized that significant spatial and temporal differences exist in LAI and PAR values in the Manafwa catchment on Mt. Elgon. This was accomplished through field measurements of actual LAI and PAR values of diverse vegetation types along a ~900m altitudinal gradient (1141–2029 masl) in the catchment. In-situ measurements were obtained from 841 micro-scale study plots in 28 sampling plots using high resolution LAI sensors. The findings showed a significant positive relationship exists between elevation and observed LAI (r = 0.45, p = 0.01). A regression model further shows that elevation and curvature of the landscape slope were highly significant (p < 0.00002) predictors of LAI. Finally, the authors detected significant spatial and temporal differences in LAI and PAR values in the study area. The study provides a critical basis for setting up long-term monitoring plans to understand mountain ecosystems and global climate change.

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GLOBAL LEAF AREA INDEX DATA FROM FIELD MEASUREMENTS, 1932-2000

ORNL Distributed Active Archive Center Datasets ◽

10.3334/ornldaac/584 ◽

2001 ◽

Cited By ~ 2

Author(s):

G. P. ASNER ◽

S. T. GOWER ◽

J. M. O. SCURLOCK

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Field Measurements ◽

Area Index ◽

Index Data

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An automated procedure for estimating the leaf area index (LAI) of woodland ecosystems using digital imagery, MATLAB programming and its application to an examination of the relationship between remotely sensed and field measurements of LAI

Functional Plant Biology ◽

10.1071/fp08045 ◽

2008 ◽

Vol 35 (10) ◽

pp. 1070 ◽

Cited By ~ 46

Author(s):

Sigfredo Fuentes ◽

Anthony R. Palmer ◽

Daniel Taylor ◽

Melanie Zeppel ◽

Rhys Whitley ◽

...

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Gap Analysis ◽

Digital Camera ◽

Field Measurements ◽

Accurate Estimation ◽

Image Capture ◽

Area Index ◽

Modis Lai ◽

Matlab Programming

Leaf area index (LAI) is one of the most important variables required for modelling growth and water use of forests. Functional–structural plant models use these models to represent physiological processes in 3-D tree representations. Accuracy of these models depends on accurate estimation of LAI at tree and stand scales for validation purposes. A recent method to estimate LAI from digital images (LAID) uses digital image capture and gap fraction analysis (Macfarlane et al. 2007b) of upward-looking digital photographs to capture canopy LAID (cover photography). After implementing this technique in Australian evergreen Eucalyptus woodland, we have improved the method of image analysis and replaced the time consuming manual technique with an automated procedure using a script written in MATLAB 7.4 (LAIM). Furthermore, we used this method to compare MODIS LAI values with LAID values for a range of woodlands in Australia to obtain LAI at the forest scale. Results showed that the MATLAB script developed was able to successfully automate gap analysis to obtain LAIM. Good relationships were achieved when comparing averaged LAID and LAIM (LAIM = 1.009 – 0.0066 LAID; R2 = 0.90) and at the forest scale, MODIS LAI compared well with LAID (MODIS LAI = 0.9591 LAID – 0.2371; R2 = 0.89). This comparison improved when correcting LAID with the clumping index to obtain effective LAI (MODIS LAI = 1.0296 LAIe + 0.3468; R2 = 0.91). Furthermore, the script developed incorporates a function to connect directly a digital camera, or high resolution webcam, from a laptop to obtain cover photographs and LAI analysis in real time. The later is a novel feature which is not available on commercial LAI analysis softwares for cover photography. This script is available for interested researchers.

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