The Seasonal Agriculture Survey (SAS) is a study conducted annually by the National Institute of Statistics of Rwanda from November to September of the following year to gather up-to-date information for monitoring progress on agriculture programs and policies in Rwanda.
The SAS 2019 covered three agricultural seasons:
- Agricultural Season A: starts from September 2018 to February 2019;
- Agricultural Season B: starts from March to June 2019; and
- Agricultural Season C: starts from July to august 2019.
The main objective of the Seasonal Agricultural Survey is to provide timely, accurate, reliable and comprehensive agricultural statistics that describe the structure of agriculture in Rwanda mainly in terms of land use, crop area, yield and crop production to monitor current agricultural and food supply conditions and to facilitate evidence-based decision making for the development of the agricultural sector.
The National Institute of Statistics of Rwanda (NISR) has been conducting an annual agricultural survey since November 2012 for the estimation of the national agricultural crop area and production estimates. In 2019/2020 agricultural year, the NISR conducted the second edition of theUpgraded Seasonal Agricultural Survey (USAS) covering the three agricultural seasons. The USAS incorporated an increased sample size to provide more precise estimates. The USAS allows information for monitoring progress on agriculture programs and policies in Rwanda.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
The scope of 2019 Seasonal Agriculture Survey concerned farm characteristics (Area, yield, production; use of production, agricultural practices; agriculture inputs and land tenure).
National coverage allowing district-level estimation of key indicators
The SAS 2020 targeted potential agricultural land and large scale farmers.
Producers and sponsors
National Institute of Statistics of Rwanda
Ministry of Finance and Economic Planning
National Institute of Statistics of Rwanda
Ministry of Agriculture and Animal Resources
Rwanda Agricultural Board
National Agriculture Export Board
Government of Rwanda
The USAS used a Multiple-Frame Sampling (MFS) methodology providing the basis for conducting probability surveys. This approach is mainly based on complete coverage of the area and enables to avail agricultural data with precise survey estimates. The methodology encompasses two sample frames: the area frame from which the main survey sample is drawn and a list frame of large-scale farmers (LSF)to complement the area frame, with the aim to cover crops mostly grown by large scale farmers which are not easily covered in the area frame. The large-scale farmer should have at least 10 hectares of agricultural holdings to be included. The process of area frame construction is a three-pronged process involving the following steps: land cover classification, land stratification and sampling of segment.
Based on the stratified two-stage sample design used with the new area frame, the first stage sampling probability for the sample segments in each stratum is calculated as:
p1h = nh/Nh
p1h = probability of selection of sample segments in stratum h (district by stratum)
nh =number of sample segments selected in stratum h
Nh = Total number of segments in the area frame for stratum h in each stratum
The second stage probability was calculated at the plot level based on the assumption that the plots within
each sample segment were implicitly selected with PPS using the area of the plot as the measure of size.
Therefore, the second stage probability of selection can be expressed as follows:
p2hi = Ghi x Ahij/Ahi x Ghij
p2h= Probability of selection of the plot in segment h
ghi = Number of grid squares selected in the i-th sample segment of stratum h;
Ahij = Area of the j-th sample plot selected in the i-th sample segment of stratum h
Ahi = Area of the i-th sample segment of stratum h;
ghij = Number of selected grid squares in the j-th sample plot of the i-th sample segment of stratum h
The weight of a sample plot is equal to the inverse of the first and second stage probabilities of selection:
Wphij = 1/p1h x p2hi = Nh x Ahi x G hij / Nh x Ghi x Ahij
WPhij =weight for the j-th sample plot in the i-th sample segment in stratum h
Dates of Data Collection
Data Collection Mode
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