Improving Paddy Rice Statistics Using Area Sampling Frame Technique

Abstract

Traditional sampling strategies for paddy rice statistics rely on outdated list frames, incomplete holding information, or administrative data that are prone to numerous biases. The objective of this study is to test the utility of an area frame developed using remote sensing data in three pilot provinces—Savannakhet (Lao People’s Democratic Republic), Ang Thong (Thailand), and Thai Binh (Viet Nam). Direct estimates of total paddy rice area and production are calculated from area frame using two methods––one involving measurement of plot size using a Global Positioning System instrument and the other utilizing a digitized map of farmer-identified plot boundaries on a high-resolution Google Earth image. A third method involving the calculation of ratio estimates using independent mesh-level measures is compared with the first two methods involving direct estimates, and with the estimates generated from administrative data from the countries. Our study finds that ratio estimation significantly improves the level of precision of paddy rice statistics. Substantial deviations are also observed between official statistics and the statistics generated through direct estimation.