Influence of Terrain on MODIS and GLASS Leaf Area Index (LAI) Products in Qinling Mountains Forests

Leaf Area Index (LAI), as a pivotal parameter in characterizing the structural properties of vegetation ecosystems, holds significant importance in assessing the carbon sink function. Given the availability of multiple long-term LAI products, validating these LAI products with consideration of topographic factors is a prerequisite for enhancing the quality of LAI products in mountainous areas. Therefore, this study aims to evaluate the performance of MODIS LAI and GLASS LAI products from 2001 to 2021 by comparing and validating them with ground-measured LAI data, focusing on the spatio-temporal and topographic aspects in the Qinling Mountains. The results show that the GLASS LAI product is a better choice for estimating LAI in the Qinling Mountains. The GLASS LAI product has better completeness and generally higher values compared to the MODIS LAI product. The time-series curve of the GLASS LAI product is more continuous and smoother than the MODIS LAI product. Both products, however, face challenges in quantifying LAI values of evergreen vegetation during winter. The MODIS and GLASS LAI products exhibit differences between sunny and shady slopes, with mean LAI values peaking on sunny slopes and reaching their lowest on shady slopes. When the slope ranges from 0 to 10°, the mean values of GLASS LAI product show a higher increasing trend compared to the MODIS LAI product. At elevations between 1450 and 2450 m, the mean LAI values of the GLASS LAI product are higher than the MODIS LAI product, primarily in the southern Qinling Mountains. Compared to ground-measured LAI data, the GLASS LAI product (R² = 0.33, RMSE = 1.62, MAE = 0.61) shows a stronger correlation and higher accuracy than the MODIS LAI product (R² = 0.24, RMSE = 1.61, MAE = 0.68).

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Publication Details

Journal
Forests
Published
2024-10-25
DOI
https://doi.org/10.3390/f15111871
Citations
3
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
1.38

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article

Influence of Terrain on MODIS and GLASS Leaf Area Index (LAI) Products in Qinling Mountains Forests

Mou Leong Tan, Mengyuan Wang, Liang Mingyue, Xiaoping Wang et al.
3 citations
Forests
Remote Sensing in Agriculture
1.38
article

Influence of Terrain on MODIS and GLASS Leaf Area Index (LAI) Products in Qinling Mountains Forests

Mou Leong Tan, Mengyuan Wang, Liang Mingyue, Xiaoping Wang, J.Y. Zheng, Mengyun Liu, Yuyang Gao
article en
3 citations

Abstract

Leaf Area Index (LAI), as a pivotal parameter in characterizing the structural properties of vegetation ecosystems, holds significant importance in assessing the carbon sink function. Given the availability of multiple long-term LAI products, validating these LAI products with consideration of topographic factors is a prerequisite for enhancing the quality of LAI products in mountainous areas. Therefore, this study aims to evaluate the performance of MODIS LAI and GLASS LAI products from 2001 to 2021 by comparing and validating them with ground-measured LAI data, focusing on the spatio-temporal and topographic aspects in the Qinling Mountains. The results show that the GLASS LAI product is a better choice for estimating LAI in the Qinling Mountains. The GLASS LAI product has better completeness and generally higher values compared to the MODIS LAI product. The time-series curve of the GLASS LAI product is more continuous and smoother than the MODIS LAI product. Both products, however, face challenges in quantifying LAI values of evergreen vegetation during winter. The MODIS and GLASS LAI products exhibit differences between sunny and shady slopes, with mean LAI values peaking on sunny slopes and reaching their lowest on shady slopes. When the slope ranges from 0 to 10°, the mean values of GLASS LAI product show a higher increasing trend compared to the MODIS LAI product. At elevations between 1450 and 2450 m, the mean LAI values of the GLASS LAI product are higher than the MODIS LAI product, primarily in the southern Qinling Mountains. Compared to ground-measured LAI data, the GLASS LAI product (R² = 0.33, RMSE = 1.62, MAE = 0.61) shows a stronger correlation and higher accuracy than the MODIS LAI product (R² = 0.24, RMSE = 1.61, MAE = 0.68).

ForestsVol. 15(11)
Universiti Sains Malaysia (MY), Northwest A&F University (CN)
Young Scientist Award of Shaanxi Province, National Key Research and Development Program of China
Life in Land
Openalex Percentile: Top 18%
Remote Sensing in Agriculture
1.38
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