The researchers developed a method called stratified adaptive cluster sampling to improve the accuracy of estimating population density for rare and clustered groups. By using auxiliary information, they created estimators that have the least error compared to other sampling methods. This new approach helps in obtaining more precise estimates for hard-to-reach populations.