scholarly journals Analysis of a multiyear global vegetation leaf area index data set

2002 ◽  
Vol 107 (D22) ◽  
Author(s):  
Wolfgang Buermann
2020 ◽  
Vol 12 (7) ◽  
Author(s):  
Qinchuan Xin ◽  
Xuewen Zhou ◽  
Nan Wei ◽  
Hua Yuan ◽  
Zurui Ao ◽  
...  

2019 ◽  
Vol 11 (2) ◽  
pp. 675-686
Author(s):  
Eric Mougin ◽  
Mamadou Oumar Diawara ◽  
Nogmana Soumaguel ◽  
Ali Amadou Maïga ◽  
Valérie Demarez ◽  
...  

Abstract. The leaf area index of Sahelian rangelands and related variables such as the vegetation cover fraction, the fraction of absorbed photosynthetically active radiation and the clumping index were measured between 2005 and 2017 in the Gourma region of northern Mali. These variables, known as climate essential variables, were derived from the acquisition and the processing of hemispherical photographs taken along 1 km linear sampling transects for five contrasted canopies and one millet field. The same sampling protocol was applied in a seasonally inundated Acacia open forest, along a 0.5 km transect, by taking photographs of the understorey and the tree canopy. These observations collected over more than a decade, in a remote and not very accessible region, provide a relevant and unique data set that can be used for a better understanding of the Sahelian vegetation response to the current rainfall changes. The collected data can also be used for satellite product evaluation and land surface model development and validation. This paper aims to present the field work that was carried out during 13 successive rainy seasons, the measured vegetation variables, and the associated open database. Finally, a few examples of data use are shown. DOI of the referenced data set: https://doi.org/10.17178/AMMA-CATCH.CE.Veg_Gh.


Land ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 274
Author(s):  
Yuzhen Zhang ◽  
Shunlin Liang ◽  
Zhiqiang Xiao

Chinese croplands have changed considerably over the past decades, but their impacts on the environment remain underexplored. Meanwhile, understanding the contributions of human activities to vegetation greenness has been attracting more attention but still needs to be improved. To address both issues, this study explored vegetation greening and its relationships with Chinese cropland changes and climate. Greenness trends were first identified from the normalized difference vegetation index and leaf area index from 1982–2015 using three trend detection algorithms. Boosted regression trees were then performed to explore underlying relationships between vegetation greening and cropland and climate predictors. The results showed the widespread greening in Chinese croplands but large discrepancies in greenness trends characterized by different metrics. Annual greenness trends in most Chinese croplands were more likely nonlinearly associated with climate compared with cropland changes, while cropland percentage only predominantly contributed to vegetation greening in the Sichuan Basin and its surrounding regions with leaf area index data and, in the Northeast China Plain, with vegetation index data. Results highlight both the differences in vegetation greenness using different indicators and further impacts on the nonlinear relationships with cropland and climate, which have been largely ignored in previous studies.


2012 ◽  
Vol 58 (2) ◽  
pp. 141-146 ◽  
Author(s):  
Sivasathivel Kandasamy ◽  
Philippe Neveux ◽  
Aleixandre Verger ◽  
Samuel Buis ◽  
Marie Weiss ◽  
...  

Improving the Consistency and Continuity of MODIS 8 Day Leaf Area Index Products Time Series Analysis of Leaf Area Index (LAI) is vital to the understanding of global vegetation dynamics. The LAI time series derived from satellite observations are usually not complete and noisy due to cloud contamination and uncertainties in the retrieval techniques. In this paper, the continuity and consistency of the MODIS 8 day LAI products are improved using a method based on Caterpillar Singular Spectrum Analysis. The proposed method is compared with other standard methods: Savitzky-Golay filter, Empirical Mode Decomposition, Low Pass filtering and Asymmetric Gaussian fitting. The experiment demonstrates the smoothing and gapfilling ability of the developed method, which is more robust across the biomes both in terms of root mean square error metrics and bias metrics as compared to the standard methods.


Author(s):  
Christoph Rüdiger ◽  
Clément Albergel ◽  
Jean-François Mahfouf ◽  
Jean-Christophe Calvet ◽  
Jeffrey P. Walker

2001 ◽  
Vol 14 (17) ◽  
pp. 3536-3550 ◽  
Author(s):  
Wolfgang Buermann ◽  
Jiarui Dong ◽  
Xubin Zeng ◽  
Ranga B. Myneni ◽  
Robert E. Dickinson

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