Sophie Bontemps has become an associate member of the ECOLAND lab. She is working as a post-doctoral researcher at the Earth and Life Institute of the Université catholique de Louvain (UCL) in Belgium. Her main background is in remote sensing while she has also advanced skills in GIS. She is involved in two projects funded by the European Space Agency (ESA) for which she has scientific and management responsibilities.
The CCI Land Cover project is part of the Climate Change Initiative (CCI) initiated by ESA to respond the need for information in support to climate science expressed by the GCOS. Recently, 50 Essential Climate Variables (ECVs) have been selected in the atmosphere, ocean and terrestrial to be critical for a full understanding of the climate system and currently ready for global implementation on a systematic basis. Land Cover is one of these variables: it is one of the most obvious and commonly used indicators for land surface and the associated human induced or naturally occurring processes, while it also plays a significant role in climate forcing.
The CCI Land Cover project aims at addressing the characterization of this variable. During the 3 first years (2011-2013), it has generated global land cover products at 300m-1000m spatial resolution over the 1998-2012 period that match the needs of the climate modeling community. From now up to 2016, the project will continue improving this set of products, using new sensors and covering an extended period. The project consortium includes various European labs of image processing as well as 3 Earth System modelling teams. These 3 teams perform model simulations to evaluate the improvements using the new LC_CCI dataset.
The Sentinel-2 for Agriculture project is also about land cover classification using remote sensing dataset but it focuses on the agriculture monitoring domain and relies on high spatial resolution imagery. Achieving sustainable food security for all people is one of the eight Millennium Development Goals but remains a global challenge. Earth Observation (EO) can contribute to agricultural monitoring as a proven source for transparent, timely and consistent information on the agricultural productivity at global and regional scale. The up-coming Sentinel-2 mission has the optimal capacity for regional to global agriculture monitoring in terms of resolution (10-20 meter), revisit frequency (5 days) and coverage (global). Further, its compatibility to the Landsat missions will allow building on a long historic time series of observations. The Sentinel-2 for Agriculture project is starting now and aims at preparing the Sentinel-2 exploitation for agriculture monitoring. Algorithms will be developed and validated to derive products in an operational manner for major worldwide representative agriculture systems. Four key products have been defined as relevant by key users of the domain: cloud free surface reflectance composites, cropland mask, crop type map and area estimate, vegetation status. In 2014 and 2015, proxy datasets (SPOT 4 Take 5, Landsat, RapidEye) will be used to simulate Sentinel-2 and generate prototype products while in 2016, the products will be demonstrated with Sentinel-2.