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Spatial time series breakpoint and coherency analysis of climate-vegetation relationship in eastern Africa

Crisci A.1, Grasso V. 1,Capecchi V. 1,Genesio L.1, Bacci M.1, Tarchiani V.1,Di Vecchia A.1 and Vignaroli P.2

1 National Research Council of Italy - Istitute of Biometeorology (CNR-IBIMET) ; 2 Climate and Sustainability Foundation (FCS)

Introduction

Food security in East Africa region essentially depends on the stability of rain-fed crops farming, which renders its society vulnerable to climatic fluctuations. These ones in Africa are most widely and directly related to rainfall. The CPSZ2 project is an initiative of Joint Research Centre of European Union to upgrade ad modernize the Crop Production System Zones Database of the IGAD Region (CPSZ). The CPSZ database, realized by FAO and co-funded by the Italian Cooperation is a unique information system for the agricultural monitoring and early warning activities on the seven countries of the Horn of Africa: Djibouti, Eritrea, Ethiopia, Kenya, Sudan, Somalia and Uganda.

ResultsFocusing on Ethiopia country, where agriculture sector accounts for 47% of the GDP, provides 85% of employment and 90% of foreign currency earning, some preliminary results obtained using this methodology are shown.

Methods

The relationships between recent spatial rainfall variability and vegetation dynamics has been investigated for East Africa territories. NDVI (Normalized Difference Vegetation Index) from SPOT-4 Vegetation satellite 1 km resolution and RFE (Rainfall Estimates) from Famine Early Warning Systems Network (FEWS NET) are used. The survey is performed at administrative level scale using 10-day summaries extracted from raster dataset for each spatial area unit, thanks to specific polygonal theme. Data time span covers two different periods: 1996-2009 for rainfall estimates and 1999-2009 for NDVI. BFAST breakpoint analysis ( Verbesselt et al, 2010) on 10-day rainfall estimates and on NDVI time series for each administrative unit has been carried out for IGAD regions. Moreover to understand the spatial and temporal patterns of ecosystem dynamics in response to climatic variability, NDVI–rainfall relationships are investigated using wavelet spectral coherence between time series (Maraun and Kurths, 2004) . Hot spot detection methodology is obtained from time series analysis carried out on the RFE and NDVI time series. The main drivers for hot spot detection are: (i) the significant annual breakpoints detected and (ii) the temporal range of coherence between NDVI and rainfall. These ones indicates the zones where and when significant changes in agricultural production systems might have occurred. For each mapping unit, the significant breaks detected over the time series of indicators could be related to the response of vegetation and to the agro-climatic conditions. The score framework built using the two techniques provides three classes of magnitude of change: low, medium and high level; the results are incorporated as theme layer trough GIS procedure. To facilitate the dissemination and sharing of information an interactive map has been implemented with Google Earth® (GE) mash-up. Finally a Web ArchiveNews Google service has been nested inside the GE mash-up to give further informative reading keys on hystorical variation occurred in the investigated areas.A demo on Ethiopia is shown in the results section

ReferencesGoogle ArchiveSearch 2009 http://news.google.com/archivesearch/advanced_searchVerbesselt J., Rob Hyndman R., Zeileis A., Culvenor D, Phenological change detection while accounting for abrupt and gradual trends in satellite image time series, 2010, Remote Sensing of Environment, Volume 114, Issue 12, ISSN 0034-4257, DOI:10.1016/j.rse.2010.08.003. Maraun, D., & Kurths, J. 2004, Nonlinear Process. in Geophys., 11, 505

IGAD NDVI climatology IGAD Potential Evapotraspiration IGAD Length of season map

Contacts

Legend

Eth_g2

Time Series Analysis

Priority MUs

No changes

Low

Medium

High

In four different district ( Gambella, Oromia, Afar and SNNP) some administrative unit have shown significant breakpoints in indicators series as highlighted in orange and red in the map. Years presenting breakpoints are: 2000, 2002, 2004/2005, with slight differences in function of the methodology employed. In the period 1999-2009, driving forces of high impact events as reported by Google News ArchiveSearch queries, are evaluated to be different for each area both from quantitative and qualitative point of view.In Gambella unit sociological factor linked to refugees displacement have prevailed, while in other areas major drought episodes signature ( 1999/2000 and 2002/2003) or heavy floods (2006) have emerged. GE mash–up main elements are shown for the Oromia-Arsi units as demonstration in the following figures.

www.ibimet.cnr.itAfrica projects & initiatives: Patrizio Vignaroli, p.vignaroli@ibimet.cnr.it

Lorenzo Genesio, l.genesio@ibimet.cnr.it Statistical Methodology: Alfonso Crisci, a.crisci@ibimet.cnr.itCommunication: Valentina Grasso, vgrasso@ibimet.cnr.it

Google News ArchiveSearch 1999-2009 annual frequency reports NDVI-rainfall time series

wavelets coherencyNDVI-rainfall time serieswavelets phase

BFAST breakpoints analisys rainfall

BFAST breakpoints analisys NDVI

Oromia Arsi

FONDAZIONE PER IL CLIMA E LA SOSTENIBILITA’