A conceptual model for assessing rainfall and vegetation trends in Sub-Saharan Africa from satellite data (Articolo in rivista)

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Label
  • A conceptual model for assessing rainfall and vegetation trends in Sub-Saharan Africa from satellite data (Articolo in rivista) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1002/joc.4231 (literal)
Alternative label
  • Hoscilo A., Balzter H., Bartholomè E., Boschetti M., Brivio P.A., Brink A., Clerici M., Pekel J.F. (2014)
    A conceptual model for assessing rainfall and vegetation trends in Sub-Saharan Africa from satellite data
    in International journal of climatology (Online); John Wiley & Sons Ltd., Chichester (Regno Unito)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Hoscilo A., Balzter H., Bartholomè E., Boschetti M., Brivio P.A., Brink A., Clerici M., Pekel J.F. (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://onlinelibrary.wiley.com/journal/10.1002/%28ISSN%291097-0088 (literal)
Rivista
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • A. Hoscilo (a), H. Balzter (b) E. Bartholomé(c) M. Boschetti(d) P. A. Brivio (d) A. Brink (c) M. Clerici(c), J. F. Pekel(c). a Remote Sensing Centre, Institute of Geodesy and Cartography, Warsaw, Poland b Department of Geography, University of Leicester, Centre for Landscape and Climate Research, UK c JRC-EC, Institute for Environment and Sustainability, Ispra, Italy d CNR-IREA, Institute of Electromagnetic Sensing of Environment, Milan, Italy (literal)
Titolo
  • A conceptual model for assessing rainfall and vegetation trends in Sub-Saharan Africa from satellite data (literal)
Abstract
  • Policymakers, governments and aid agencies require operational environmental monitoring in support of evidence-based policy-making and resource deployment in crisis situations. For Africa, this is only feasible at sub-continental scale with a large network of automated meteorological stations, a large number of highly coordinated field observers or with satellite remote sensing. The challenge with satellite data lies in the derivation of meaningful environmental indicators. This article describes a conceptual framework for understanding satellite-derived indicators of rainfall and vegetation greenness trends over Africa. It attributes observed vegetation changes to climatic (i.e. rainfall linked) and non-climatic drivers. A decade of annual rainfall and vegetation data over sub-Saharan Africa was analysed using satellite-based rainfall estimates [Famine Early Warning System Rainfall Estimation 2.0 (FEWSNET RFE 2.0)] from National Oceanic and Atmospheric Administration's (NOAA's) Climate Prediction Centre and the Normalized Difference Vegetation Index (NDVI) obtained from the Satellite Pour l'Observation de la Terre Vegetation (SPOT-VGT) sensor. Rainfall and vegetation greenness trends were analysed for 759 administrative regions of sub-Saharan Africa to identify those regions that have experienced a negative, positive or stable rainfall/vegetation trend over the period 2001-2010. The character of the relationship between the annual rainfall and max NDVI trends were examined to identify areas where the changes in greenness could be attributed to climatic (rainfall) and non-climatic (human land use or ecological disturbance) changes. Regions where increasing rainfall was associated with vegetation greening were found in West Africa, Central African Republic, West Cameroon and northeastern part of South Africa, whereas areas with evidence of 'climatic vegetation degradation' were located in Southern Madagascar, Nigeria, Kenya and the Garden Route region of South Africa. (literal)
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