Mapping Forest Landscape Patterns

Ajith H. Perera

ISBN 10: 1493973290 / ISBN 13: 9781493973293

Editore: Springer New York, Springer New York, 2017

Riguardo questo articolo

Druck auf Anfrage Neuware - Printed after ordering - This book explores the concepts, premises, advancements, and challenges in quantifying natural forest landscape patterns through mapping techniques. After several decades of development and use, these tools can now be examined for their foundations, intentions, scope, advancements, and limitations. When applied to natural forest landscapes, mapping techniques must address concepts such as stochasticity, heterogeneity, scale dependence, non-Euclidean geometry, continuity, non-linearity, and parsimony, as well as be explicit about the intended degree of abstraction and assumptions. These studies focus on quantifying natural (i.e., non-human engineered) forest landscape patterns, because those patterns are not planned, are relatively complex, and pose the greatest challenges in cartography, and landscape representation for further interpretation and analysis.

Codice articolo 9781493973293

Dati bibliografici

• Titolo: Mapping Forest Landscape Patterns
• Editore: Springer New York, Springer New York
• Data di pubblicazione: 2017
• Lingua: Inglese
• ISBN 10: 1493973290
• ISBN 13: 9781493973293
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 241 L x 160 A x 24 P (millimetri) 241 millimetri di larghezza per 160 millimetri di altezza per 24 millimetri di profondità
• Peso: 676 grammi

Descrizione articolo

Riassunto

This book explores the concepts, premises, advancements, and challenges in quantifying natural forest landscape patterns through mapping techniques. After several decades of development and use, these tools can now be examined for their foundations, intentions, scope, advancements, and limitations. When applied to natural forest landscapes, mapping techniques must address concepts such as stochasticity, heterogeneity, scale dependence, non-Euclidean geometry, continuity, non-linearity, and parsimony, as well as be explicit about the intended degree of abstraction and assumptions. These studies focus on quantifying natural (i.e., non-human engineered) forest landscape patterns, because those patterns are not planned, are relatively complex, and pose the greatest challenges in cartography, and landscape representation for further interpretation and analysis.

Informazioni sull?autore

Tarmo K. Remmel, Ph.D. (University of Toronto), Associate Professor of Geography at York University: A GIScientist with over 10 years of experience teaching and conducting research involving remote sensing, GIS, and spatial statistics, Dr. Remmel focuses primarily on boreal forests, with a particular emphasis on wildfire disturbances and on the development of algorithms for measuring and assessing spatial patterns, planar shapes, and the quantification of spatial change and accuracy. A strong proponent of free and open source software tools, particularly within the R-project to facilitate implementation, his work integrates field-level data collection with remotely sensed imagery obtained from satellite, aircraft, and UAV platforms to characterize the effects of scale.

Ajith H. Perera, Ph.D. (Penn State University), Senior Research Scientist and leader of the forest landscape ecology program at Ontario Forest Research Institute, Ontario Ministry of Natural Resources, adjunct professor at University of Waterloo, York University and University of Guelph: With over 25 years research experience in landscape ecology, Dr. Perera’s major focus is on quantifying and modeling spatio-temporal patterns in boreal forest disturbances. He has authored over 150 science publications, and been senior editor, co-editor and author of eight books on Forest Landscape Ecology.