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Remote Sens. 2015, 7(3), 3274-3292; doi:10.3390/rs70303274

Assessing MODIS GPP in Non-Forested Biomes in Water Limited Areas Using EC Tower Data

1
GEOINCA-202, Universidad de León, Campus de Ponferrada C/ Avda. de Astorga s/n, 24401 Ponferrada, León, Spain
2
Department of Natural Resources, Faculty of ITC, University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands
3
Luxembourg Institute of Science and Technology (LIST), Department for Environmental Research and Innovation, 41, rue du Brill, L-4422 Belvaux, Luxembourg
*
Author to whom correspondence should be addressed.
Academic Editors: Dengsheng Lu, Guomo Zhou, Conghe Song, Guangxing Wang, Josef Kellndorfer and Prasad S. Thenkabail
Received: 16 December 2014 / Revised: 23 February 2015 / Accepted: 17 March 2015 / Published: 20 March 2015
(This article belongs to the Special Issue Carbon Cycle, Global Change, and Multi-Sensor Remote Sensing)
View Full-Text   |   Download PDF [649 KB, uploaded 20 March 2015]   |  

Abstract

Although shrublands, savannas and grasslands account for 37% of the world’s terrestrial area, not many studies have analysed the role of these ecosystems in the global carbon cycle at a regional scale. The MODIS Gross Primary Production (GPP) product is used here to help bridge this gap. In this study, the agreement between the MODIS GPP product (GPPm) and the GPP Eddy Covariance tower data (GPPec) was tested for six different sites in temperate and dry climatic regions (three grasslands, two shrublands and one evergreen forest). Results of this study show that for the non-forest sites in water-limited areas, GPPm is well correlated with GPPec at annual scales (r2 = 0.77, n = 12; SEE = 149.26 g C∙m−2∙year−1), although it tends to overestimate GPP and it is less accurate in the sites with permanent water restrictions. The use of biome-specific models based on precipitation measurements at a finer spatial resolution than the Data Assimilation Office (DAO) values can increase the accuracy of these estimations. The seasonal dynamics and the beginning and end of the growing season were well captured by GPPm for the sites where (i) the productivity was low throughout the year or (ii) the changes in the flux trend were abrupt, usually due to the restrictions in water availability. The agreement between GPPec and GPPm in non-forested sites was lower on a weekly basis than at an annual scale (0.44 ≤ r2 ≤ 0.49), but these results were improved by including meteorological data at a finer spatial scale, and soil water content and temperature measurements in the model developed to predict GPPec (0.52 ≤ r2 ≤ 0.65). View Full-Text
Keywords: grasslands; shrublands; carbon; water limited; Eddy covariance; remote sensing grasslands; shrublands; carbon; water limited; Eddy covariance; remote sensing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Álvarez-Taboada, F.; Tammadge, D.; Schlerf, M.; Skidmore, A. Assessing MODIS GPP in Non-Forested Biomes in Water Limited Areas Using EC Tower Data. Remote Sens. 2015, 7, 3274-3292.

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