Sample designers and data collectors have always been working for assuring high quality standards of survey data. Although much has been written about statistical quality assurance methods, notably in the industry setting, few resources in the literature address the problem of assessing survey's quality. Sample Design for Survey's Quality Evaluation approaches such a relevant topic focusing on the design of probabilistic samples for data collection quality monitoring and measurement error evaluation of longitudinal surveys. In both cases, the theoretical developments are motivated by potential applications to the U.S. National Resources Inventory. Nevertheless, the employed process of investigation as well as the results presented in the book can be applied to several other survey scenarios. The properties of several classes of sample designs for data quality monitoring are investigated and the problem of designing a subsample to estimate the measurement error contribution to the variance of the Horvitz-Thompson estimator is studied. The covered subjects make this book an essential source for any professional involved in quality evaluation studies of sample surveys.