Total Socioenvironmental Systems [electronic resource] : An Analytical Framework for Human-Natural Interactions and Sustainability / by Yichun Xie.

Chapter 1 -Theoretical Foundations of Total Socioenvironmental System (TSES) -- Chapter 2-Analytical Frameworks of TSES -- Chapter 3 - Building Temporally Compatible TSES Dataset -- Chapter 4 - Empirically investigating time-series causality between grassland productivity and socio-environmental factors, Inner Mongolia as a Case Study -- Chapter 5 - Empirical evaluation of urban sustainability from underlying causal structures and legacy effects: The prefecture cities in China as a Case Study -- Chapter 6 - Constructing Spatially Compatible TSES Dataset: Examining Urban Declining in Southeast Michigan as the case study -- Chapter 7 -Empirically examining spatial processes of urban declining: Southeast Michigan as the case study -- Chapter 8 - Modeling grassland deterioration considering spatial variations and time-lag effects at a finer geographical scale -- Chapter 9 - Innovations, Limitations, and Future Directions of TSES.

This book presents a new analytical framework and several newly developed quantitative methods to investigate the interactions between climatic, ecological, and socioeconomic factors as a total socioenvironmental system (TSES). Facing the increasingly imperiled ecosystems around the world, understanding the complex relationships between humans and environments is of utmost importance. This book offers several solutions to these challenges based on the author's research and illustrates them with case studies and annotated data sets. It develops the conceptual framework of a TSES, emphasizing the identification of causal relationships as a starting point to investigating the interactions between biophysical phenomena and socioeconomic factors. The book experiments with various spatial data assimilation techniques such as GIS for matching diverged areal units over which biophysical and socioeconomic datasets are collected. Trend extraction methods including machine learning for synchronizing distinct temporal rhythms hidden in biophysical and socioeconomic phenomena to augment their causal relationships are explored as well. The book also examines sustainability in urban systems, social systems, and ecosystems. This volume will be useful to readers across many disciplines, including but not limited to geographic information science, ecological informatics, environmental informatics, regional and urban modeling, quantitative social sciences and planning.