Using satellite based soil moisture to quantify the water driven variability in NDVI: A case study over mainland Australia

Chen, Tao; Jeu, R. A. M. de; Liu, Y.Y.; Werf, Guido R. van der; Dolman, A. J.

doi:10.1016/j.rse.2013.08.022

Cited by 291 publications

(174 citation statements)

References 70 publications

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“…In the case of Central Australia the main driver of vegetation growth is soil moisture content. This was already shown in Chen et al [2014], who compared a long time series of soil moisture and satellite-derived NDVI and found that in arid, moisture-limited regions with low vegetation cover, NDVI strongly correlates with soil moisture, with a typical lag time of 1 month. This is also what is shown in the SIF signal, which lags behind soil moisture.…”

Section: Discussionsupporting

confidence: 59%

Anomalous carbon uptake in Australia as seen by GOSAT

Detmers

Hasekamp

Aben

et al. 2015

Geophysical Research Letters

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One of the unanswered questions of climate change is how the biospheric uptake of carbon responds to events such as droughts and floods. Especially, semiarid regions have received interest recently, as they can respond very rapidly to changing environmental conditions. Here we report on a large enhanced carbon sink over Australia from the end of 2010 to early 2012 detected using the Greenhouse Gases Observing SATellite (GOSAT). This enhanced sink coincides with the strong La Niña episode, accompanied by record‐breaking amounts of precipitation. This precipitation led to an enhanced growth of vegetation, resulting in large increases in biospheric carbon uptake in line with increased levels of vegetation fluorescence. An inversion based on the satellite retrievals confirms this strong anomaly in the sink of roughly 0.21 ± 0.03 Pg C yr−1 or 0.41 ± 0.5 Pg C in total for the April 2010 to December 2011 period, which corresponds to 7% of the multiyear annual average gross primary production of the Australian biosphere.

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Section: Discussionsupporting

confidence: 59%

Anomalous carbon uptake in Australia as seen by GOSAT

Detmers

Hasekamp

Aben

et al. 2015

Geophysical Research Letters

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“…A previous study by Yang et al (2014) showed that GRACE is a superior indicator of surface greenness than soil moisture or precipitation, which were earlier used as indicators (Chen et al, 2014;Huxman, 2004). Temporal decomposition of GRACE TWS * produces a new temporal dimension that allow the data to be analysed to their full potential.…”

Section: Discussionmentioning

confidence: 99%

“…Most commonly, precipitation and soil moisture have been used as defining variables (Chen et al, 2014;Huxman, 2004;Méndez-Barroso et al, 2009;Wang et al, 2007). Both of these have shown generally meaningful correlations with ecosystem performance (by various measures such as the normalised difference vegetation index, NDVI, and above-ground net primary production).…”

Section: Introductionmentioning

confidence: 99%

Large-scale vegetation responses to terrestrial moisture storage changes

Andrew

Guan

Batelaan

2017

Hydrol. Earth Syst. Sci.

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Abstract. The normalised difference vegetation index (NDVI) is a useful tool for studying vegetation activity and ecosystem performance at a large spatial scale. In this study we use the Gravity Recovery and Climate Experiment (GRACE) total water storage (TWS) estimates to examine temporal variability of the NDVI across Australia. We aim to demonstrate a new method that reveals the moisture dependence of vegetation cover at different temporal resolutions. Time series of monthly GRACE TWS anomalies are decomposed into different temporal frequencies using a discrete wavelet transform and analysed against time series of the NDVI anomalies in a stepwise regression. The results show that combinations of different frequencies of decomposed GRACE TWS data explain NDVI temporal variations better than raw GRACE TWS alone. Generally, the NDVI appears to be more sensitive to interannual changes in water storage than shorter changes, though grassland-dominated areas are sensitive to higher-frequencies of water-storage changes. Different types of vegetation, defined by areas of land use type, show distinct differences in how they respond to the changes in water storage, which is generally consistent with our physical understanding. This unique method provides useful insight into how the NDVI is affected by changes in water storage at different temporal scales across land use types.

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“…They discuss the co-variation of NDVI and soil moisture, stating coherent trend changes [39]. Furthermore, other authors showed that a soil moisture NDVI pixel-wise residual trend indicates land degradation [17].…”

Section: Environmental Variablesmentioning

confidence: 99%

Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013

et al. 2016

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Ukraine has experienced immense environmental and institutional changes during the last three decades. We have conducted this study to analyze important land surface dynamics and to assess processes underlying the changes. This research was conducted in two consecutive steps. To analyze monotonic changes we first applied a Mann-Kendall trend analysis of the Normalized Difference Vegetation Index (NDVI3g) time series. Gradual and abrupt changes were studied by fitting a seasonal trend model and detecting the breakpoints. Secondly, essential environmental factors were used to quantify their possible relationships with land surface changes. These factors included soil moisture as well as gridded air temperature and precipitation data. This was done using partial rank correlation analysis based on annually aggregated time-series. Our results demonstrate that positive NDVI trends characterize approximately one-third of Ukraine's land surface, located in the northern and western areas of the country. Negative trends occurred less frequently, covering less than 2% of the area and are distributed irregularly across the country. Monotonic trends were rarely found; shifting trends were identified with a greater frequency. Trend shifts were seen to occur with an increased frequency following the period of the 2000s. We determined that land surface dynamics and climate variability are functionally interdependent; however, the relative influence of the drivers varies in different locations. Among the factors analyzed, the air temperature variable explains the largest portion of NDVI variability. High air temperature/NDVI correlation coefficients (r = 0.36´0.77) are observed over the entire country. The soil moisture content is of significant influence in the eastern portion of Ukraine (r = 0.68); precipitation (r = 0.65) was most influential in the central regions of the country. These results increase our understanding of ecosystem responses to climatic changes and anthropogenic activities.

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Using satellite based soil moisture to quantify the water driven variability in NDVI: A case study over mainland Australia

Cited by 291 publications

References 70 publications

Anomalous carbon uptake in Australia as seen by GOSAT

Anomalous carbon uptake in Australia as seen by GOSAT

Large-scale vegetation responses to terrestrial moisture storage changes

Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013

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