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Sensitivity analysis for leaf area index (LAI) estimation from CHRIS/PROBA data |
Jianjun CAO1,2, Zhujun GU2( ), Jianhua XU1, Yushan DUAN1, Yongmei LIU2, Yongjuan LIU2, Dongliang LI2 |
1. The Key Laboratory of GIScience of the Education Ministry PRC, East China Normal University, Shanghai 200062, China 2. School of Bio-chemical and Environmental Engineering, Nanjing Xiaozhuang University, Nanjing 211171, China |
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Abstract Sensitivity analyses were conducted for the retrieval of vegetation leaf area index (LAI) from multi-angular imageries in this study. Five spectral vegetation indices (VIs) were derived from Compact High Resolution Imaging Spectrometer onboard the Project for On Board Autonomy (CHRIS/PROBA) images, and were related to LAI, acquired from in situ measurement in Jiangxi Province, China, for five vegetation communities. The sensitivity of LAI retrieval to the variation of VIs from different observation angles was evaluated using the ratio of the slope of the best-fit linear VI-LAI model to its root mean squared error. Results show that both the sensitivity and reliability of VI-LAI models are influenced by the heterogeneity of vegetation communities, and that performance of vegetation indices in LAI estimation varies along observation angles. The VI-LAI models are more reliable for tall trees than for low growing shrub-grasses and also for forests with broad leaf trees than for coniferous forest. The greater the tree height and leaf size, the higher the sensitivity. Forests with broad-leaf trees have higher sensitivities, especially at oblique angles, while relatively simple-structured coniferous forests, shrubs, and grasses show similar sensitivities at all angles. The multi-angular soil and/or atmospheric parameter adjustments will hopefully improve the performance of VIs in LAI estimation, which will require further investigation.
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| Keywords
CHRIS/PROBA
LAI
sensitivity
vegetation index
vegetation type
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Corresponding Author(s):
Zhujun GU
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Issue Date: 04 July 2014
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