Abstract:

In this paper, a new stratified adaptive cluster sampling method is proposed based on the adjusted Horvitz-Thompson estimator with the network nonoverlapping strata.The mean and variance estimator are proved to be unbiased． Nine sampling methods were used for estimating the density of Hedysarum scoparium in Ulanbuh Desert edge in China，simple random sampling，stratified simple random sampling，adaptive cluster sampling based on the adjusted Hansen-Hurwitz estimator，adaptive cluster sampling based on the adjusted Horvitz-Thompson estimator，stratified adaptive cluster sampling I (ACSI) based on the adjusted Hansen-Hurwitz estimator with the network overlapping strata，stratified adaptive cluster sampling II (ACSII) based on the adjusted Hansen-Hurwitz estimator with the network overlapping strata，stratified adaptive cluster sampling based on the adjusted Horvitz-Thompson estimator with the network overlapping strata，stratified adaptive cluster sampling based on the adjusted Horvitz-Thompson estimator with the network nonoverlapping strata．The precisions of the nine sampling methods were compared．The result showed that the new stratified adaptive cluster sampling method based on the adjusted Horvitz-Thompson estimator with the network nonoverlapping strata was more effective than the others，and the sampling in stratified populations was more effective than the sampling in non-stratified populations．

Key words: Hedysarum scoparium, stratified adaptive cluster sampling, Horvitz-Thompson estimator, Hansen-Hurwitz estimator, simulation sampling, Ulanbuh Desert