The book "Resampling Methods for Dependent Data" offers a comprehensive analysis of bootstrap and related resampling methods specifically designed for temporal and spatial data with various dependencies. It addresses the challenges that arise in the statistical analysis of dependent data and provides tools that do not require strict structural assumptions. This is particularly important since model misspecification is more common with dependent data, and traditional statistical methods often react sensitively to deviations from model assumptions. The book highlights the development of resampling methods since the early approaches in the 1980s and describes the advancements in theory and methodology achieved over the last two decades. It is aimed at professionals and students in the fields of mathematics and natural sciences who seek a deeper understanding of the statistical analysis of dependent data.