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 STATISTICS ISI Satellite meeting in Maputo on August 2009

Selected zones: first stage sampling Area 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 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

Land occupation surveys more than Livestock surveys Forecast survey 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

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 2054% 3 To 5 persons 1130% More than 5 persons 616%

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 sampling Settle 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 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 crops Dairy farms city Suggar beet and cereals cereals vegetables 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