Modern landscape research uses a panoply of techniques to further our understanding of our changing world, including mathematics, statistics and advanced simulation techniques to combine empirical observations with known theories. This book identifies emerging fields and new challenges that are discussed within the framework of the ‘driving forces’ of Landscape Development. the book addresses all of the ‘hot topics’ in this important area of study and emphasizes major contemporary trends in these fields.
|Series:||Landscape Series , #8|
|Product dimensions:||6.10(w) x 9.20(h) x 0.80(d)|
Table of Contents
Foreword.- Preface.- 1. Change and transformation: a synthesis; F. Kienast et al.- Part 1: Value systems - Major drivers of landscape dynamics. 2. Value systems: drivers of human-landscape interactions; M. Buchecker et al.- 3. The role of value systems in biodiversity research; P. Duelli et al.- 4. The meaning of 'Landscape' – an exegesis of Swiss government texts; P. Longatti, T. Dalang.- 5. Two aspects of the human-landscape relationship; M. Hunziker et al.- Part 2: Ecological observations and processes. 6. Modern remote sensing for environmental monitoring of landscape states and trajectories; N.E. Zimmermann et al.- 7. A large-scale, long-term view on collecting and sharing of landscape data; A. Lanz et al.- 8. On selected issues and challenges in dendroclimatology; J. Esper et al.- 9. Using the past to understand the present land use and land cover; M. Bürgi et al.- 10. Integrating population genetics with landscape ecology to infer spatio-temporal processes; R. Holderegger et al.- 11. Landscape permeability: from individual dispersal to population persistence; W. Suter et al.- Part 3: Spatial pattern recognition, time series analysis and dynamic modeling. 12. Identifying and quantifying landscape patterns in space and time; J. Bolliger et al.- 13. Essay on the study of the vegetation process; O. Wildi, L. Orlóci.- 14. Statistical analysis of landscape data: space-for-time, probability surfaces and discovering species; S. Ghosh, O. Wildi.- 15. Memory, non-stationarity and trend: analysis of environmental time series;S. Ghosh et al.- 16. Model up-scaling in landscape research; H. Lischke et al.- 17. Dynamic spatio-temporal landscape models; H. Lischke et al.-