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Earth System Science Data The Data Publishing Journal
https://doi.org/10.5194/essd-2017-74
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
 
04 Aug 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Earth System Science Data (ESSD).
Gross and net land cover changes based on plant functional types derived from the annual ESA CCI land cover maps
Wei Li1, Natasha MacBean2, Philippe Ciais1, Pierre Defourny3, Céline Lamarche3, Sophie Bontemps3, Richard A. Houghton4, and Shushi Peng5 1Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
2School of Natural Resources and the Environment, The University of Arizona, Tucson, AZ, 85721, USA
3Earth and Life Institute-Environmental Sciences, Université catholique de Louvain, Louvain-la-Neuve, Belgium
4Woods Hole Research Center, Falmouth, Massachusetts, USA
5Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
Abstract. Land-use and land-cover change (LULCC) impacts local energy and water balance and contributes at global scale to a net carbon emission to the atmosphere. The newly released annual ESA CCI land cover maps provide continuous land cover changes at 300 m resolution from 1992 to 2015, and can be used in land surface models (LSMs) to simulate LULCC effects on carbon stocks and on surface energy budgets. Here we investigate the absolute areas, gross and net changes of different plant functional types (PFTs) derived from ESA CCI products. The results are compared with other datasets. Global areas of forest, cropland and grassland PFTs from ESA are 30.4, 19.3 and 35.7 million km2 in 2000. The global forest area is lower than that from LUH2v2h (Hurtt et al., 2011), Hansen et al. (2013) and Houghton and Nassikas (2017) while cropland area is higher than LUH2v2h (Hurtt et al., 2011), in which cropland area is from HYDE3.2 (Klein Goldewijk et al., 2016). Gross forest loss and gain during 1992–2015 are 1.5 and 0.9 million km2 respectively, resulting in a net forest loss of 0.6 million km2, mainly occurring in South and Central America. The magnitudes of gross changes of forest, cropland and grassland PFTs in ESA CCI are smaller than those in other datasets. The magnitude of global net cropland gain for the whole period is consistent with HYDE3.2 (Klein Goldewijk et al., 2016), but most of the increases happened before 2004 in ESA while after 2007 in HYDE3.2. Brazil, Bolivia and Indonesia are the countries with the largest net forest loss from 1992 to 2015, and the decreased areas are generally consistent with those from Hansen et al. (2013) based on Landsat 30 m resolution images. Despite discrepancies compared to other datasets, and uncertainties in converting into PFTs, the new ESA CCI products provide the first detailed long time-series of land-cover change and can be implemented in LSMs to characterize recent carbon dynamics, and in climate models to simulate land-cover change feedbacks on climate. The annual ESA CCI land cover products can be downloaded from http://maps.elie.ucl.ac.be/CCI/viewer/download.php (Land Cover Maps – v2.0.7; see details in Section 2.5).

Citation: Li, W., MacBean, N., Ciais, P., Defourny, P., Lamarche, C., Bontemps, S., Houghton, R. A., and Peng, S.: Gross and net land cover changes based on plant functional types derived from the annual ESA CCI land cover maps, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2017-74, in review, 2017.
Wei Li et al.
Wei Li et al.

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Short summary
We evaluated the land cover changes based on plant functional types (PFTs) derived from the newly released annual ESA land cover maps. We addressed the geographical distributions and temporal trends of the translated PFT maps and compared with other datasets commonly used by the land surface model community. Different choices of these datasets for the applications in land surface models are proposed depending on the research purposes.
We evaluated the land cover changes based on plant functional types (PFTs) derived from the...
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