Agricultural Census Sampling Frames and Sampling

1. Agricultural Census Sampling Frames and Sampling Section B

2. Crop Production Reports • Country experiences have shown that periodic field reports on area cultivated by crop and yield tend to be biased • Subjective methods of estimating crop production are not reliable, even with available check data • Objective measurement surveys are the more reliable method to gather current agricultural data

3. Agricultural Survey Sample Considerations • Type of estimates required – administrative level and unit of analysis • Stratification –the topic under investigation determines the strata • Sampling within strata – depends upon frame, data required and quality of field staff • Sample stages and sampling units – normally multi-stage samples with ultimate unit of analysis being the holding or field

4. Selecting Holdings and Fields • Holdings can be selected from lists fairly easily, lists of fields would be constructed for each selected holding • If detailed maps, aerial photography or satellite imagery is available, a grid can be overlaid with dots that would mark field for selection, thus using probability proportionate to size

5. Area Segment Sampling • Area segments selected at first-stage, fields selected as second-stage by laying grids with dots over detailed maps or imagery • Field that fall under a dot are in sample • Open segment approach – Area segment is first-stage sample, and all fields having a uniquely defined point in the selected segment is in sample

6. Area Segment Sampling • Weighted segment approach is better for holdings – all holdings having any land in the selected segment are in sample • Data from each holding are weighted based on proportion of holding inside the segment • Closed segment approach includes only fields or parts of fields inside the sample segments • Doesn’t provide data by holding

7. Estimation of Area Procedures Object measures of area usually involve direct measures, however other methods may be needed for inaccessible areas or due to cost and time constraints: • Indirect measures start with a scale drawing or imagery • Measuring the area of land for regular shapes is straightforward, irregular shapes require different methods

8. Area Estimation Methods • Planimetering – an outline of the area is drawn/digitized and the instrument/software calculates the area • Gridding – division of a scale map imagery into grids of known area, counting of squares provides area – simple and fast • Dot counting – same as gridding but uses equally spaced dots or counting of pixels in imagery

9. Observation of Land Uses • A sample of points is selected and marked on maps or imagery using stratification and clustering techniques • Send observers to locate sample points in field and record crop or other land use • For each stratum tally points by land use category • Multiply the known total are of the stratum by the proportion of sample points for that land use • Sum over all strata

10. Ratio Estimation and Double Sampling • After measuring holdings in the sample, total estimates can be calculated using the appropriate estimation procedure for the sample design • In double sampling, data is obtained for a large sample of the population and the more expensive and accurate measurement technique is used on a subsample - again ratio estimation is used

11. Objective Measurement of Yield • Estimates crop yields on a unit basis using the total area planted by crop • Plot is randomly selected and crop is cut and weighed at harvest time (crop cutting) • There are no rules to guide crop estimation so objective measures are required

12. Crop Cutting Pilot Studies • New methods should be piloted alongside old methods for at least a year • Ensures new method is superior and feasible • Allows for measurement of bias in old method • Data users can more accurately track trends over time

13. Crop Yield Variability • Crop variability within and among fields affects sampling considerations based on: • Variability of plot yields by size and shape • Variability among plots of same size within fields • Normally, a minimum of two plots per field is required to measure within field variability

14. Size and Shape of Plot • Precise instructions must be determined for evaluating plot size and how to take measurements • Small plots are more efficient since within field variability is small compared to intra field variability • Small plots are also more efficient in terms of time, staff and resources

15. Small Plot Biases • Measurement biases are more pronounced with smaller plant sizes: • Crop conditions tend to influence the field worker’s selection of plot, this effect is magnified with smaller plots • Inclusion of boundary plants has a greater impact when the perimeter is larger compared to total area

16. Locating Plot in Field Provide specific procedures to mitigate subjective plot selection bias • Place field within rectangular shape defined by rows and/or units of measure along two sides • Field worker chooses random numbers less than length and width of field • Start at specified corner and pace to random x point, then enter field and pace to random y point • Layout plot according to procedures from the random point within the field

17. Locating Plot in Field How to prevent sample plots from overlapping field boundaries? • Harvest only plot portions that fall within field • Difficult for irregular sized plots/fields • Restrict random selection numbers to those that will allow plot to fall within field boundaries or reject samples that overlap boundaries • Can introduce bias if yields differ significantly on boundaries of fields

18. Harvesting Procedure • Field workers can harvest small plots, sending a subsample back to the central office • Best to replicate field conditions by harvest with same methods and timing as holder • Alternatively holders can provide yield estimates to compare with crop cutting yields • Supplementary check data should be used where possible

19. Adjustment to Actual Production • Biases are introduced by independent harvesting of sample plots and harvest timing • Harvest a subsample of fields using normal procedures • Carry out post harvest gleaning operation to estimate losses • Conduct pilot study on adjustments needed for various harvest times • Adjust for moisture by drying sample and comparing to biological yield weights

20. Operational Considerations Pilot studies are necessary to identify and test solutions for operational problems, including: • Availability and quality of field staff • Facilities for drying crops • Equipment for measuring, weighing, recording • Coordination with holder’s harvesting activities

21. Section B Quiz • What factors must be considered when designing observational survey samples? • What are the four types of area segment sampling that were discussed? • How does ratio estimation and double sampling benefit area estimations? • Name four factors that cause variability and or bias in crop cutting surveys?