Na Zhao

This book describes the basic contents of eco-environmental informatics (EEI) systematically. It consists of ten chapters: development history of the groundworks of knowledge, data and models for the EEI emergence since the early 1850s, the core principles of EEI including methods for high-accuracy surface modelling and the fundamental theorem for eco-environmental surface modelling, spatial interpolations, scale-transformations, data fusion, and model-data assimilation, as well as their applications connecting ecology, environmental science, and geographical science. It is used as a textbook for advanced undergraduate and graduate students in the field of EEI. It also serves as a reference book for researchers involved in geographical information science, ecological informatics, environmental informatics, computer-aided design, and planetary surface modelling.

This book focuses on the robustness analysis of high accuracy surface modeling method (HASM) to yield good performance of it. Understanding the sensitivity and uncertainty is important in model applications. The book aims to advance an integral framework for assessing model error that can demonstrate robustness across sets of possible controls, variable definitions, standard error, algorithm structure, and functional forms. It is an essential reference to the most promising numerical models. In areas where there is less certainty about models, but also high expectations of transparency, robustness analysis should aspire to be as broad as possible. This book also contains a chapter at the end featuring applications in climate simulation illustrating different implementations of HASM in surface modeling. The book is helpful for people involved in geographical information science, ecological informatics, geography, earth observation, and planetary surface modeling.

This book focuses on the robustness analysis of high accuracy surface modeling method (HASM) to yield good performance of it. Understanding the sensitivity and uncertainty is important in model applications. The book aims to advance an integral framework for assessing model error that can demonstrate robustness across sets of possible controls, variable definitions, standard error, algorithm structure, and functional forms. It is an essential reference to the most promising numerical models. In areas where there is less certainty about models, but also high expectations of transparency, robustness analysis should aspire to be as broad as possible. This book also contains a chapter at the end featuring applications in climate simulation illustrating different implementations of HASM in surface modeling. The book is helpful for people involved in geographical information science, ecological informatics, geography, earth observation, and planetary surface modeling.