RWANDA - Rwanda Seasonal Agricultural Survey 2025

To provide the basis for conducting probability-based surveys that comprehensively capture farm-level
data and to enhance the precision of survey estimates, the Seasonal Agricultural Survey employs a Multiple
Frame Sampling (MFS) methodology. This approach involves constructing an area frame from which the
survey sample is selected. In addition, a list frame of Large-Scale Farmers (LSF), defined as those operating
at least 10 hectares of agricultural land is done to complement the area frame. This ensures comprehensive
coverage of crops predominantly cultivated by large-scale farmers, which might not be adequately represented using an area frame alone.
The construction of the area frame involves several steps, including land
cover classification, land stratification and the sampling of segments.

Land classification serves as the first step in designing the sampling frame for the Seasonal Agriculture Survey.
This process involves categorizing the total available land in the country into distinct land use or land
cover types. The primary purpose is to enhance sampling precision by ensuring the appropriate targeting
of the adequate land. This classification was achieved through a combination of available national different
spatial layers with the photo-interpretation of a time series of high-resolution (50 to 30 cm) satellite images
spanning from 2010 to 2023.the country’s total land was divided into 14 distinct land cover
classes and Among 14 land cover classes, only 6 are related to agricultural activities include agricultural land on hillside,
non-rice agricultural Wetland, mixed rangeland, low-density built-up area, wetlands designated for paddy
rice and tea plantation.The subsequent step involves constructing the area frame which includes grouping the land cover classes
linked to agricultural activities into strata to identify agricultural strata to be considered in the sampling
frame.

The stratification is a result of a combination of sampling units (clusters) and land use/land cover.
The stratification assigns each cluster a stratum based on the predominant land class type. Among the fourteen land
cover classes, four are included in the agricultural survey frame, while the others are excluded.
The included land cover classes comprise hillside agricultural land, non-rice agricultural land, mixed rangeland,
and low-density built-up areas (which retain potential for agricultural production, such as kitchen gardens, fruit trees, and livestock).
However, specific agricultural land classes are excluded from the sampling
frame. For example, tea plantations are omitted due to regular monitoring by the National Agricultural Export
Development Board (NAEB). Similarly, wetlands designated for paddy rice cultivation are typically considered
under the Large-Scale Farmers component, thereby integrating them into the survey frame.
Moreover, beginning in 2024, a new land cover class called “Exclusive Rangeland” has been introduced specifically to
idintify areas used for pastoral activities. This class is also excluded from the sampling frame.


The stratified two-stage sample design used with the new area frame, the first stage sampling probability for the sample
segments in each stratum was calculated.

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.