Long-Term Variation of Global GEOV2 and MODIS Leaf Area Index (LAI) and Their Uncertainties: An Insight into the Product Stabilities

Hongliang Fang,Sijia Li,Yinghui Zhang,Yao Wang

doi:10.34133/2021/9842830

Abstract

Leaf area index (LAI) is an essential climate variable that is crucial to understand the global vegetation change. Long-term satellite LAI products have been applied in many global vegetation change studies. However, these LAI products contain various uncertainties that are not been fully considered in current studies. The objective of this study is to explore the uncertainties in the global LAI products and the uncertainty variations. Two global LAI datasets—the European Geoland2 Version 2 (GEOV2) and Moderate Resolution Imaging Spectroradiometer (MODIS) (2003-2019)—were investigated. The qualitative quality flags (QQFs) and quantitative quality indicators (QQIs) embedded in the product quality layers were analyzed to identify the temporal anomalies in the quality profile. The results show that the global GEOV2 (0.042/10a) and MODIS (0.034/10a) LAI values have steadly increased from 2003 to 2019. The global LAI uncertainty (0.016/10a) and relative uncertainty (0.3%/10a) from GEOV2 have also increased gradually, especially during the growing season from April to October. The uncertainty increase is larger for woody biomes than for herbaceous types. Contrastingly, the MODIS LAI product uncertainty remained stable over the study period. The uncertainty increase indicated by GEOV2 is partly attributed to the sensor shift in the product series. Further algorithm enhancement is necessary to improve the cross-sensor performance. This study highlights the importance of studying the LAI uncertainty and the uncertainty variation. Temporal variations in the LAI products and the product quality revealed herein have significant implications on global vegetation change studies.

Highlights

Leaf area index (LAI) is defined as one half of the total green leaf area per unit ground surface area [1]
Geoland2 Version 2 (GEOV2) (1.16) exhibits a lower average LAI than the GEOV1 (1.55), whereas the Moderate Resolution Imaging Spectroradiometer (MODIS) average LAI remains nearly unchanged in different releases (1.43 vs. 1.28 for C5 and collection 6 (C6), respectively)
The GEOV2 average uncertainty for evergreen broadleaf forest (EBF) (0.37) has significantly decreased as compared to that of the GEOV1 (0.66), which leads to much higher percentage of pixels that are below the Globe Climate Observing System (GCOS)-2011 quality requirement than the earlier release (Figure 10)

Summary

Introduction

Leaf area index (LAI) is defined as one half of the total green leaf area per unit ground surface area [1]. LAI has been recognized as a critical parameter to understand the terrestrial energy, carbon, and water cycles [2,3,4]. The global LAI has gradually increased, consistent with the global temperature change, since the industrial period [5, 6]. Global long-term LAI products derived from satellite data show that the increasing trend has accelerated since 1982 [1, 7, 8]. The global LAI is projected to further increase in the 21st century under future climate change scenarios [9]. Regional decline of LAI exists in Eurasia, North and South America, and Southeast Asia caused by land use and land cover change (e.g., due to deforestation) [5, 10]

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Results

Discussion

Conclusion