spatial data and analysis in support of improved policy and planning an aciar example using africa
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Australian Centre for International Agricultural Research ACIAR. Spatial Data and Analysis in Support of Improved Policy and Planning – An ACIAR example using Africa. Christopher Auricht [email protected] ACFID Canberra 21 August 2012. Current status of spatial data and applications.

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spatial data and analysis in support of improved policy and planning an aciar example using africa
Australian Centre for International Agricultural Research ACIAR

Spatial Data and Analysis in Support of Improved Policy and Planning – An ACIAR example using Africa

Christopher Auricht [email protected]



21 August 2012

current status of spatial data and applications
Current status of spatial data and applications
  • Applications now matured to point where such systems:
    • Can and are being used in various capacities. For example -
      • Humanitarian scenarios (especially as they relate to malnutrition, morbidity and mortality)
      • Economic scenarios  with and without interventions at differing stages i.e. decision support systems e.g. pre-emptive, resilience building / risk management interventions v’s emergency response triggered by high mortality or threat i.e. once a crisis has eventuated
    • Have ability to look at multiple scales( local, national, regional) and longitudinally (forwards and backwards)

See for example – FAO FIVIMS and World Bank sites

percentage urban and urban agglomerations by size class
Percentage urban and urban agglomerations by size class




Source: UN Pop Division World Urbanisation Prospects, 2011 Revision


urban agglomerations by size class and potential risk of drought
Urban agglomerations by size class and potential risk of drought




Source: UN Pop Division World Urbanisation Prospects, 2011 Revision

talk outline sub saharan africa example
Talk outline – Sub-Saharan Africa Example
  • Context and Background
  • Need for a strategic approach
  • Issues and status of spatial data
  • Methodology used in developing an updated farming systems dataset and analysis for Sub-Saharan Africa
  • Food Security and Nutrition AIFSC
stitch in time saves nine
Stitch in time saves nine
  • Spatial data and systems can help inform where the stitch is needed and the type of stitch required
  • According to CGIAR analysis
    • One billion of the worlds poor within Africa and Asia (those living on less than $1 per day) are fed primarily by:
      • hundreds of millions of small-holder farmers (often with less than 2 ha of land, several crops, and a cow or two), or
      • Herders (most with fewer than five large animals)

Solution ?

  • Develop sustainable farming systems that improve efficiency gains to produce increased food production
scale of rural hunger
Scale of Rural Hunger

Trends in maize shortage in Zambia

Percentage of farm households with maize shortage

  • Nearly one billion people experience debilitation, health-threatening hunger each year
  • 4 out of 5 of these people are rural farmers

The Hunger Period

  • ‘Business-as-usual’ investments in agriculture unlikely to deliver sustainable solutions in many countries
  • Numerous obstacles to progress e.g. inefficiencies in program delivery, political uncertainty etc. These are not the only problem!
  • Existing systems (often under stress) have been/ are expected to continue to accommodate large increases in population, increasing urbanisation, rising demand for animal products, plus competition for land and water
  • Forecasts suggest that current practices will not stay abreast with population growth, environmental change and increasing demand for animal products.
population 2000 and 2040 sub saharan africa millions
Population 2000 and 2040 Sub-Saharan Africa (Millions)

Source: UN Pop Division World Urbanisation Prospects, 2011 Revision and FAOStat and

  • Requires a strategic approach, an appreciation of scale, and an understanding of the interactions between and within systems
the current aciar ssa farming systems project
The current ACIAR SSA Farming Systems project

  • Builds on the work of Dixon et al 2001
2001 farming systems and poverty
2001 Farming Systems and Poverty
  • Widely accepted as pioneering body of work – looked at things as a ‘surface’ across landscape not confined by country borders – often problems are regional
  • Largely driven by LGP/AEZ and market access, supplemented by expert opinion
  • Extensively used to guide investment at the program level and frame analysis in numerous global studies
  • Approach focused on high level farming systems within six developing regions
  • Involved use of various thematic data layers to underpin the delineation, characterisation / description and subsequent analysis of systems
sub saharan update
Sub-Saharan Update
  • Is there a demand for this information? Farming systems website in FAO still one of the most visited sites within the organisation – up to 4,000 hits per month (Site > 10 years old!)
  • Consistent seamless datasets somewhat limited in original work
  • In need of updating as spatial extent of systems and frame conditions changed e.g. climate, population, urbanisation, market access, economics etc.
  • Many updated and new datasets available
  • Capture and use data and information in an manner that informs decisions in a simple fashion
  • Maintain rigour and transparency
  • Establishing an enduring infrastructure/framework to enable changes to be monitored over time
  • Ability to support numerous policy initiatives – Principle: collect it once – use it many
current situation
Current Situation
  • 2012 – Large quantity of potential datasets – approx. 300 alone in the Harvest Choice database  temporal and some predictive data now available
  • GAEZ 3.0 - 1,000’s of datasets representing 100’s of thematic layers
  • Question - which ones to use and how
  • Strategic approach
    • Access and collation
    • Assess (fit-for-purpose) and Prioritise (currency, coverage, scale etc)
    • Process  Products
    • Disseminate

Delineate new Farming System Boundaries – Iterative process based on concept of central tendency

  • Work in collaborative fashion with authors and other large data providers e.g. IFPRI – Harvest Choice, UN-FAO, ILRI, ICRAF, IIASA, CGIAR others


  • Characterise and describe systems

Spatial and Tabular Data

Statistics and Analysis

  • Integration of new datasets –
    • LGP and Market access
  • Supporting Datasets
    • Population (rural, urban, total)
    • Livestock – cattle, sheep, goats, poultry, LU and TLU
    • Crop areas and production
    • Yield gaps
    • Protected areas
    • Poverty  $2.00 and $1.25 /day
    • Nutrition
hunger poverty productivity spatial covariates proxies analytical flow
Hunger, Poverty & Productivity Spatial Covariates/Proxies & Analytical Flow

Terrain, Demography,

Infrastructure, Admin Units


Environment &



Systems & Performance

Linkage to





Crop Distribution & Yields

Settlements, ports, markets

Crop Suitability: Rainfed Wheat

Agroecological Zones

Port travel times & costs

Market travel times & costs

Slope, aspect, drainage

Road, rail, river, ICT networks


Administrative Units

Yield Responses to Inputs, Management, CC

Drought Incidence & Severity


Pests & Diseases (Maize Stem Borer)

Cropland extent & intensity

Farming Systems

Value of Production per Rural Person

Profitability of small scale irrigation

Quantity of Nutrients Removed

Aggregate to FPUs

Fertilizer Profitability

Distribution of Welfare Benefits

Source: HarvestChoice 2010

big questions for management and policy
Big questions for management and policy
  • What is it?
  • Where is it?
  • What are its characteristics and how does it operate ?
  • What are the risks/threats ?
  • What are the opportunities (Research / Extension) ?
  • How are these issues changing with time ?
  • Evaluation and Performance
spatial data
Spatial data
  • Tool to support process
  • Understand
  • Analyse
  • Develop interventions
  • Monitor
  • Not the answer in itself 
    • has limitations
    • Fit for purpose
    • Complement with expert knowledge
spatial data and aciar activities
Spatial data and ACIAR Activities
  • Update of Farming Systems for Sub-Saharan Africa
  • Informing development of policy and program development as part of the ACIAR ‘Australian International Food Security Centre (AIFSC)’
    • Announced by Prime Minister Gillard October 2011- International focus, recognising the significance of food security to developing countries.
    • Providing a bridge between agriculture (technologies, policies and practices) and their adoption by smallholder farmers (including livestock keepers). Increase adoption  increase productivity and diversity and generate additional income
  • Research gaps in terms of food security, agriculture and nutrition in line with the AIFSC strategy and African priorities
  • Support in determining how AIFSC could best complement work being undertaken by partners in target countries and where we should invest
  • Nutrition indicators – under-nutrition, child nutrition, maternal under-nutrition, micronutrient deficiencies
  • Nutrition interventions , regional analysis, country snapshots
  • Acknowledgements
    • ACIAR
    • IFPRI – Harvest Choice
    • CGIAR
    • ILRI
    • ICRAF
    • FAO
    • IIASA
    • others
  • Questions & Discussion