Integration of agricultural statistics into national statistical system

From Area Frame Sampling to an integrated geographic information system : Moroccan experience

Redouane ARRACH / Chief of Statistic Division (Ministry of agriculture, Morocco)

STRATEGY FOR IMPROVING AGRICULTURAL AND RURAL STATISTICSISI Satellite meeting in Maputo on 13-14 August 2009

Selected zones: first stage samplingArea subdivided to zones : PSU base

Zones are subdivided to segments

segment : Secondary Sampling unit

Stratification based on soil occupation

Field step :

segment Location for survey

Fix borders on ground with owners or farmers

Steps to settle an area frame sampling

Stratum 10 : annual crops in rainfaid area Stratum 20 : irrigated annual crops Stratum 30 : fruit trees area Stratum 40 : Forest Stratum 50 : Grazing lands Stratum 60 : small cities Stratum 70 : Big cities Stratum 80 : Big villages

119

40 %

13 %

6 %

7 %

7 %

7 %

Strate 10

Strate 20

Strate 30

Strate 40

Strate 50

Strate 60

Strate 70

Strate 80

40 %

119

7 %

7 %

7 %

6 % 13 % Strate 10

Strate 20

Strate 30

Strate 40

Strate 50

Strate 60

Strate 70

Strate 80

Land occupation surveys more than 50000

Livestock surveys 25000

Forecast survey 10000

Producers prices 3000

The Moroccan area frame sampling count for 3000 segments (SSU) and cover 19 millions Ha (90% of land with agricultural potentiel) only 10% for list sheet.

Annual Surveys calendar with strict dealines is carried out with area frame sample

The area frame sampling method has reflected main changes in moroccan agriculture

1978

-79

1980

-81

1982

-83

1984

-85

1986

-87

1988

-89

1990

-91

1992

-93

1994

-95

1996

-97

1998

-99

2000

-01

2002

-03

2004

-05

2006

-07

0

500

1000

1500

2000

2500

soft wheat area 1000 Ha

1978-79

1981-82

1984-85

1987-88

1990-91

1993-94

1996-97

1999-00

2002-03

2005-06 500

700

900

1100

1300

1500

Hard wheat area 1000 Ha

1978-79

1981-82

1984-85

1987-88

1990-91

1993-94

1996-97

1999-00

2002-03

2005-06 0

100

200

300

400

500

corn area (1000 Ha)

19801982

19841986

19881990

19921994

19961998

20002002

0500

1000150020002500300035004000

CATTLE (1000 HEADS)

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

500070009000

1100013000150001700019000

SHEEP (1000 HEADS)

-15 000

-10 000

-5 000

0

5 000

10 000

1,00

1,50

2,00

2,50

3,00

3,50VSTOCK

Prix

•Changes in soil occupation due to expansion of cities

•Grazing lands are cultivated more and more

•Expansion of irrigation (new crops : fruit trees, vegetables, foder crops…etc)

• farmers are seek and tired of enumerators (difficult to reach all the sample

Samples are getting old

With a classical procedures, updating Costs are high

•Area frame sampling has been established with more than 20 engeneers and 800 survey satff in regional services.

•Skilled staff with a large knowledge of rural area is going to retirement

Statistical services

(projection to 2015)

%

2 persons or less

20 54%

3 To 5 persons 11 30%

More than 5 persons

6 16%

Experience tell us that many concepts in area frame sampling are to revise

• Adapt stratification to production context : To improve quality of statistics comming from area frame samples , the use of production systems and agro climatique maps will be more relevant and will give statistics with low variance

• Some strata are not to survey each year (forets , grazing lands, cities…etc)

•Segment size to conceive with taking in acount the ground reality

•New demands on statistics at county level (commune rurale)

Out of area frame samplingSettle a statistical infrastructure to built foundation for an intergrated Agricultural information system.

Catch and map knowledge detained by skilled field staff and producers

Adopt statistics on soil occupoation and livestock to different level (admininistrative, agro ecological zones, produc tion systems…etc)

Update the area frame sampling with new technological tools

Census based on maps (ex: citrus census)

Forecast and use of remote sensing

Study epidemic animal disease and simulate their propagation

Inssurance and natural catastrophes

Geographic information for climate change studies

Use multiple information layers for integrated statistics and relevant analysis

Spot 5 image 2.5m color : we cover until now 15 millions Ha in 2008 for following purpuses :

Forest

fodder cropsDairy farms

city

Suggar beet and cereals

cerealsvegetables

New and accurate stratification to update and make easy area frame samples to design and to maintain

- Photo-interprétation at 1/10000 scale

- Field work to verify photo interpretation and identify more details on soil

occupation

- Digitalizing border of polygons and entring corresponding data (All

caracteristics possible collected on the ground)

- SIG solution

Fruit trees census to be carried out this year with this maps at 1/10000 and

1/5000 scale

12

Moroccan Citrus census 2006 based on ortho photo 1/5000

Digital plateform permit to update samples with a new approche

A large possibilities to overlap information layers (agronomic, economic, demographic, ..etc) to produce statistics at very low level

We developed an application to generate automaticaly samples regarding to area frame sample steps: theses samples are georeferenced and mapped