Page 105 - Contributed Paper Session (CPS) - Volume 7

CPS2042 Anna Christine D. et al.
available satellite images at the time of the study, are likely candidates for
future research.

Keywords
Agriculture; Area Frames; Sampling Methods; Satellite Images

1. Introduction
Timely and reliable agricultural statistics are critical for monitoring
government agricultural development plans and mitigating the effects of
extreme weather and climate change. The preparation of national accounts,
evaluation of agricultural interventions, and the development of early warning
systems to address climatic and non-climatic vulnerabilities in the agricultural
sector, rely on high- quality and disaggregated agricultural data. In the
absence of good quality data, inefficient allocation of resources is likely which
would lead to a failure in resolving critical development problems (Kelly et al.
1995).
The compilation of official agricultural statistics relies on data collected
using administrative records or probability-based field surveys. The
advantages of these methods lie in its lower implementation cost, but
estimates derived are likely to be biased and prone to large measurement
errors. Household and/or agricultural surveys can provide better estimates,
when objectively designed and conducted. Both agricultural and population-
based census frames are commonly used in developing countries as a basis
for designing multistage sample agricultural and household surveys (Grosh
and Munoz 1996). However, in some countries, a complete frame is not
available if the reference is a census with low coverage, or the existing lists of
sampling units change rapidly rendering the list frame out of date (Griffin
2014). Field listing activities may not be accurate if households systematically
over or under reporting agricultural holdings.
An alternative to the list frame approach is the area frame approach. In
the area frame approach, the final stage sampling units are land areas and the
selection probabilities are proportional to their area measures. A multistage
stratified approach can then be implemented based on an area frame to select
a sample of grids within each stratum of land cover and/or land use,
depending on the survey objective (Faulkenberry and Garoui 1991).
To fill in the gap in the existing literature, this study utilizes an area frame
approach through the innovative combination of satellite data, GIS methods,
and crop cutting to estimate paddy rice area, yield, and production for the
2015 rainy season in selected provinces of three pilot countries—Lao People’s

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