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Mapping Forest Landscape Patterns

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

09.09.2017

Abbildungen

XIV, 125 illus., 94 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen

Herausgeber

Tarmo K. Remmel + weitere

Verlag

Springer Us

Seitenzahl

326

Maße (L/B/H)

24,1/16/2,4 cm

Gewicht

686 g

Auflage

1st ed. 2017

Sprache

Englisch

ISBN

978-1-4939-7329-3

Beschreibung

Portrait

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.

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

09.09.2017

Abbildungen

XIV, 125 illus., 94 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen

Herausgeber

Verlag

Springer Us

Seitenzahl

326

Maße (L/B/H)

24,1/16/2,4 cm

Gewicht

686 g

Auflage

1st ed. 2017

Sprache

Englisch

ISBN

978-1-4939-7329-3

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Mapping Forest Landscape Patterns
  • Produktbild: Mapping Forest Landscape Patterns
  • Preface

    Chapter 1: Mapping forest landscapes: overview and a primer 1. Mapping forest landscapes: an introduction1.1 What is mapping? 1.2 What is a forest landscape?  2. Considerations in forest landscape mapping2.1 Describing spatial patterns2.2 Focus on boundaries2.3 Beyond 2D data 3. Utility of forest landscape maps3.1 Map representations3.2 Morphological interpretations3.3 Map scale3.4 Error assessment and validation 4. Summary

    Chapter 2: Fuzzy classification of vegetation for ecosystem mapping 1. Introduction 2. Overview of fuzzy systems 2.1 Fuzzy systems – key concepts for mapping2.2 Mapping with fuzzy classifiers 3. Fuzzy approaches for identifying and utilizing uncertainty 3.1 Thematic uncertainty3.2 Spatial uncertainty3.3 Simultaneous considerations of thematic and spatial uncertainty3.4 Multiple outputs – fuzzy geodatabase 4. Vertical structure mapping 5. A look to the future 6. Summary

    Chapter 3: Portraying wildfires in forest landscapes as discrete complex objects 1. Introduction 2. Wildfire initiation and anatomy 2.1 Initiation2.2 Descriptors of footprints 3. Wildfires as discrete and complex objects 3.1 The outer edge of a wildfire is scale-dependent 3.2 Width of the ecotone3.3 Internal heterogeneity 4. Standardized depiction of wildfires as discrete complex objects  5. The future of mapping wildfires 5.1 Accuracy assessment in remote regions5.2 Landscape persistence5.3 Hierarchical data formats for capturing scale effects



    Chapter 4: Airborne LiDAR applications in forest landscapes 1. Introduction 1.1 Defining ALS LiDAR  1.2 Introduction to the three common LiDAR platforms1.3 Intensity, point density, and multi-spectral LiDAR 2. Primary measurements 2.1 Surface models (DEM, DSM, DTM, CHM)2.2 Canopy height models and detection and delineation of individual trees 3. Secondary measurements 3.1 Regression models and allometric equations3.2 Vertical profile for a single tree3.3 Classification of vegetation types3.4 Tree genus and species classification3.5 Case study: identifying potentially hazardous trees 4. The future of LiDAR

    Chapter 5: Regression Tree modeling of spatial pattern and process interactions 1. Spatial Pattern and Processes 1.1 Describing spatial patterns1.2 Process complexity1.3 Data mining 2. Methods 2.1 CART models2.2 BRT2.3 RF models 3. Case Study Context – Influence of beetle infestation spatial patterns on fire spatial processes 3.1 Study area3.2 Spatial data 4. Model evaluation 4.1 CART4.2 BRTs4.3 RF models4.4 Comparing modeling approaches 5. Interpreting regression tree results within the context of spatial pattern and process 

    Chapter 6: Mapping the abstractions of forest landscape patterns 1. Introduction 2. Tools for evaluating landscape patterns 3. Data preparation and uncertainties within metrics 3.1 Scale and classification issues 4. Mapping different aspects of a landscape pattern 4.1 Composition4.2 Configuration4.3 Criteria for selecting metrics 5. Applications of forest pattern mapping 5.1 Improving forest management5.2 Assessment of forest habitats5.3 Mapping landscape metrics by using GIS5.4 Using landscape metrics in modeling 6. Future perspectives on mapping patterns 6.1 3D landscape metrics6.2 4D landscape metrics 7. Conclusions Chapter 7: Towards automated forest mapping 1. Introduction 1.1 Definitions1.1.1 Forest 1.1.2 Remote sensing for automated mapping of woodland and forest 2. Data and Pre-processing 2.1 Reference data 2.2 Remote sensing systems2.3 Processing of input data sets 3. Mapping woodland  3.1 A hierarchical segmentation approach for mapping woodland 3.2 Individual tree and tree crown detection 3.3 Fractional tree cover approach 4. Forest mapping 4.1 Moving window approach4.2 Distance criterion approach 5. Lessons learned 6. Future perspectives

    Epilogue: Toward more efficient and effective applications of forest landscape maps 1. Background 2. Goals of this chapter 3. Considerations in forest landscape mapping 3.1. The community of map developers and users is broad3.2. Maps are model outputs 3.3. Maps are probabilistic3.4. Maps contain errors3.5. Map contents are scale-related3.6. Map applications are scale-related3.7. Mapping methods are advancing rapidly 4. A brief list of best practices for using forest landscape maps 5. Conclusions