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Discussion papers
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: data description paper 15 Apr 2019

Submitted as: data description paper | 15 Apr 2019

Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Earth System Science Data (ESSD).

The Global Long-term Microwave Vegetation Optical Depth Climate Archive VODCA

Leander Moesinger1, Wouter Dorigo1, Richard de Jeu2, Robin van der Schalie2, Tracy Scanlon1, Irene Teubner1, and Matthias Forkel1 Leander Moesinger et al.
  • 1Vienna University of Technology, Department of Geodesy and Geoinformation, Gußhausstraße 27–29, 1040 Vienna, Austria
  • 2VanderSat, Wilhelminastraat 43A, 2011 VK Haarlem, the Netherlands

Abstract. Since the late 1970s, spaceborne microwave sensors have been providing measurements of radiation emitted by the Earth's surface. From these measurements it is possible to derive vegetation optical depth (VOD), a model-based indicator related to vegetation density and its relative water content. Because of its high temporal resolution and long availability, VOD can be used to monitor short- to long-term changes in vegetation. However, studying long-term VOD dynamics is generally hampered by the relatively short time span covered by the individual microwave sensors. This can potentially be overcome by merging multiple VOD products into a single climate data record. But, combining multiple sensors into a single product is challenging as systematic differences between input products, e.g. biases, different temporal and spatial resolutions and coverage, need to be overcome.

Here, we present a new series of long-term VOD products, which combine multiple VOD data sets derived from several sensors (SSM/I, TMI, AMSR-E, Windsat, and AMSR-2) using the Land Parameter Retrieval Model. We produce separate VOD products for microwave observations in different spectral bands, namely Ku-band (period 1987–2017), X-band (1997–2018), and C-band (2002–2018). In this way, our multi-band VOD products preserve the unique characteristics of each frequency with respect to the structural elements of the canopy. Our approach to merge the single-sensor VOD products is similar to the one of the ESA CCI Soil Moisture products (Liu et al., 2012; Dorigo et al., 2017): First, the data sets are co-calibrated via cumulative distribution function matching using AMSR-E as scaling reference. We apply a new matching technique that scales outliers more robustly than ordinary piece-wise linear interpolation. Second, we aggregate the data sets by taking the arithmetic mean between temporally overlapping observations of the scaled data, generating a VOD Climate Archive (VODCA).

The characteristics of VODCA are assessed for self-consistency and against other products: spatio-temporal patterns and anomalies of the merged products show consistency between frequencies and both with observations of Leaf Area Index derived from the MODIS instrument as well as Vegetation Continuous Fields from AVHRR instruments. Trend analysis shows that since 1987 there has been a decline in VOD in the tropics and in large parts parts of east-central and north Asia along with a strong increase in India, large parts of Australia, south Africa, southeastern China and central north America. Using an autocorrelation analysis, we show that the merging of the multiple data sets successfully reduces the random error compared to the input data sets. In summary, VODCA shows vast potential for monitoring spatio-temporal ecosystem behaviour complementary to existing long-term vegetation products from optical remote sensing.

The VODCA products (Moesinger et al., 2019) are open access and available under Attribution 4.0 International at

Leander Moesinger et al.
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Status: final response (author comments only)
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Leander Moesinger et al.
Data sets

The Global Long-term Microwave Vegetation Optical Depth Climate Archive VODCA L. Moesinger, W. Dorigo, R. De Jeu, R. Van der Schalie, T. Scanlon, I. Teubner, and M. Forkel

Leander Moesinger et al.
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Short summary
Vegetation optical depth (VOD) is measured by satellites and is related to the density of vegetation and its water content. VOD has a wide range of uses, including drought, wildfire danger, biomass and carbon stock monitoring. For the past 30 years there exist various VOD datasets derived from space-borne microwave sensors, but biases between them prohibit a combined use. We removed these biases and merged the data to create the global long-term VOD Climate Archive (VODCA).
Vegetation optical depth (VOD) is measured by satellites and is related to the density of...