Landscape Research has been established as an interdisciplinary field dealing with complex environmental processes at multiple spatial and temporal scales. During the course of its history, various societal, technological and philosophical stimuli have shaped Landscape Research, e.g. the declaration of Landscape Ecology in the 1930s and contemporary global technological and societal developments.

Modern landscape research presently uses mathematics, statistics and advanced simulation techniques to combine empirical observations with known theories from ecology, physics, geography, social science and so on. Knowledge is thus updated and quantified via models that are used for estimation, hypothesis testing, prediction and assessment of scenarios. Advances in the computational sciences (e.g. fast computers and vast array of software), space science (e.g. remote sensing) and biological sciences (e.g. genetics) as well as new perspectives in the social sciences play important roles. Research findings are implemented in conservation management, urban planning and global change mitigation strategies.

This book identifies emerging fields and new challenges that are discussed within the framework of the a ~driving forcesa (TM) of Landscape Development. Rather than offering a comprehensive overview of all fields of Landscape Research, the book addresses a ~hot topicsa (TM) emphasizing major contemporary trends in these fields.

Long-memory processes are known to play an important part in many areas of science and technology, including physics, geophysics, hydrology, telecommunications, economics, finance, climatology, and network engineering. In the last 20 years enormous progress has been made in understanding the probabilistic foundations and statistical principles of such processes. This book provides a timely and comprehensive review, including a thorough discussion of mathematical and probabilistic foundations and statistical methods, emphasizing their practical motivation and mathematical justification. Proofs of the main theorems are provided and data examples illustrate practical aspects. This book will be a valuable resource for researchers and graduate students in statistics, mathematics, econometrics and other quantitative areas, as well as for practitioners and applied researchers who need to analyze data in which long memory, power laws, self-similar scaling or fractal properties are relevant.

Landscape Research has been established as an interdisciplinary field dealing with complex environmental processes at multiple spatial and temporal scales. During the course of its history, various societal, technological and philosophical stimuli have shaped Landscape Research, e.g. the declaration of Landscape Ecology in the 1930s and contemporary global technological and societal developments.

Modern landscape research presently uses mathematics, statistics and advanced simulation techniques to combine empirical observations with known theories from ecology, physics, geography, social science and so on. Knowledge is thus updated and quantified via models that are used for estimation, hypothesis testing, prediction and assessment of scenarios. Advances in the computational sciences (e.g. fast computers and vast array of software), space science (e.g. remote sensing) and biological sciences (e.g. genetics) as well as new perspectives in the social sciences play important roles. Research findings are implemented in conservation management, urban planning and global change mitigation strategies.

This book identifies emerging fields and new challenges that are discussed within the framework of the driving forces of Landscape Development. Rather than offering a comprehensive overview of all fields of Landscape Research, the book addresses hot topics emphasizing major contemporary trends in these fields."

Long-memory processes are known to play an important part in many areas of science and technology, including physics, geophysics, hydrology, telecommunications, economics, finance, climatology, and network engineering. In the last 20 years enormous progress has been made in understanding the probabilistic foundations and statistical principles of such processes. This book provides a timely and comprehensive review, including a thorough discussion of mathematical and probabilistic foundations and statistical methods, emphasizing their practical motivation and mathematical justification. Proofs of the main theorems are provided and data examples illustrate practical aspects. This book will be a valuable resource for researchers and graduate students in statistics, mathematics, econometrics and other quantitative areas, as well as for practitioners and applied researchers who need to analyze data in which long memory, power laws, self-similar scaling or fractal properties are relevant.