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Development Domain Analysis

Agricultural PotentialLand Cover

Market Access

Crop Systems Modeling

Farm-gate Price Modeling

Spatial Analysis at IFPRI

ZHE GUO*, EMILY SCHMIDT, JAWOO KOO, RIA TENORIO

* GIS COORDINATOR ([email protected])

Environment and Production Technology Division

International Food Policy Research Institute

AAGW2010/NAIROBI9 JUNE 2010
mailto:[email protected]:[email protected]


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AAGW2010/NAIROBI | 9 JUNE 2010

DOMAIN ANALYSISOverview


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To use a set of domain criteria to identify focus area and

regions which have similarity or dissimilarity of conditions of

relevance to agricultural development.

To capture and analyze the region patterns of agriculture

productivity and potentials.

Ag-potential

Land cover

Market access

Development Domain Analysis


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Development domain analysis Development domains

o Existing: land cover * Rural Population *[Market access]

o

Potential: Ag-potential (eg. LGP, NDVI) * Rural Population*[Market access] Further economic analysis (e.g. DREAM model)

existi

ng cropland *ruralpopulation density

potential cropland *ruralpopulation density

Potential cropland

density are derived

from statistical

variables (e.g. mean,

min, max, standard

deviation) of monthly

NDVI and classified

into high, med, low .

The rural population

density is classified

into high, med and low

classes. Development

domain classes are

developed from theintersection of the two

variables.

Existing cropland

density is derived fromAfri-cover datasets

and are classified into

high and low classes.

The rural population

density is classified

into high, med and low

classes. Domain

classes (2*3=6) are

developed from the

intersection of the two

variables.


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AGRICULTURAL POTENTIALDomain Analysis


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Ag-potential variables


7/27AAGW2010/NAIROBI | 9 JUNE 2010

PLANTING

WINDOW

OF

RAINFED CROPS

SSA

MODIS

Greenness Up/DownSeason A/B

Weekly window

KATE SEBASTIAN [email protected]



LAND COVERDomain Analysis



Existing cropland variables

GLC2000

(2000)

Africover(~2000)

MODIS

(2001)

Globcover

(2005)



Existing cropland variables


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M k



Market access



CROP SYSTEMS MODELINGBiophysical Evaluation


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SIMULATED

CLIMATE CHANGE

IMPACTS ON

CROP YIELD

2000 and 2050

DSSAT 4.5Maize

Subsistence

FutureClim 1.0MIROC 3.2 (IPCC4)

A2 SRES

TIM THOMAS [email protected]


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By 2050, the decline in calorie availability

will increase child malnutrition by 20percent relative to a world with no climate

change.

Thus, aggressive agricultural productivity

investments of US$7.17.3 billion are

needed to raise calorie consumption

enough to offset the negative impacts ofclimate change on the health and well-

being of children.

IFPRI Food Policy Report 21 Climate change impact on

agriculture and costs of adaptation

ASSESSING

CLIMATE CHANGE

IMPACT ON AGRICULTURE

AND

COSTS OF ADAPTATION

IMPACTPartial equilibrium ag. sector model

Base year 2005; projection to 2050

Model changes in crop area and yields

production, value of production,food availability per capita,

child malnutrition and hunger impacts

DSSAT 4.02Yield changes of staple crops

JERRY NELSON [email protected]


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SIMULATED

LONG-TERM

CHANGES IN

CROP YIELD

Rainfed

Maize

SSA

DSSAT 4.51965-2000

Climate: CRU-Mashup

Soil: HC27

1965

2000

JAWOO KOO [email protected]


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SIMULATED

LONG-TERM

CHANGES IN

CROP YIELD

Rainfed

Maize

Ethiopia

DSSAT 4.51961-2000

Climate: CRU-Mashup

Soil: HC27

Cultivar:

- Traditional

- Hybrid

Cumulative

Probability (%)

0

20

40

60

80

100

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6

2.8

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

5.0

5.2

5.4

5.6

5.8

6.0

6.2

Average Yield (t/ha)

Dekalb XL71 (USA, Hybrid) with 10 kg[N]/ha

Dekalb XL71 (USA, Hybrid) with 40 kg[N]/ha

Long maturity (Generic, Traditional) with 10 kg[N]/ha

Long maturity (Generic, Traditional) with 40 kg[N]/ha

mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]


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MAIZE PRICE MODELINGEstimating Farm Gate Prices


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Price modeling overview

20

Road networks

Road types

Border locations

Transportcost surface

Fertilizer landed price

Bagging fee

Border crossing fee

Loading cost

Fertilizerdelivery cost

Farm and market locations

Market maize price

Farm to market transport costs

Border crossing fee

Maizedelivery cost

Ports locations

Land cover types

Elevation and Slope

Regulation cost

Storage cost

Marketing Margins

F i i d li


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Farm-gate maize price modeling


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SPATIAL ANALYSIS AT IFPRIIFPRI Spatial Ignite | 3 June 2010


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SPATIAL

ECONOMETRIC

ANALYSES

Recent Studies (2009-2010)

Accounting for spillover in household agricultural production

Is agricultural production spillover the rationale behind CAADP framework?

Poverty rate and government income transfers: a spatial simultaneous equation approach

1991-2006

Neighbors Growth Effect (%)

JOHN ULIMWENGU [email protected]
mailto:[email protected]:[email protected]:[email protected]


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AGRICULTURAL

WATER

MANAGEMENT

SOLUTIONS

SPAM

SWAT

EPIC

HUA XIE [email protected]


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AGRICULTURE

AND

MALARIA

RISK

Maize, tree crops, and cattle

Household survey 20067,426 households

14,000 parcels

Geographically-weighted

regressionLow Risk?: No

Agriculture

within 2-km

radius

High Risk?:

Cattle and

Maize within

2-km radius

BEN WIELGOSZ [email protected]


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MODELING

ACCESSIBILITY TO

HEALTH CARE

SERVICES

Yemen

Gravity model

AccessibilityHospitals

Rural health centers

Educational programs

JOSE FUNES [email protected]


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DATA

VISUALIZATION

Tableau Publichttp://tableausoftware.com

http://tableausoftware.com/mailto:[email protected]:[email protected]:[email protected]://tableausoftware.com/

aagw2010 june 09 zhe guo spatial analysis at ifpri

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