Forest Mensuration

Author:   John A. Kershaw (University of New Brunswick, New Brunswick, Canada) ,  Mark J. Ducey (University of New Hampshire, USA) ,  Thomas W. Beers (Purdue University, West Lafayette, IN, USA) ,  Bertram Husch (Food and Agriculture Organization of the United Nations)
Publisher:   John Wiley and Sons Ltd
Edition:   5th edition
ISBN:  

9781118902035


Pages:   640
Publication Date:   30 December 2016
Replaced By:   9781394282104
Format:   Hardback
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

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Forest Mensuration


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Overview

Forest mensuration – the science of measurement applied to forest vegetation and forest products – holds value for basic ecology as well as sustainable forest management.  As demands on the world’s forests have grown, scientists and professionals are increasingly called on to quantify forest composition, structure, and the goods and services forests provide.  Grounded in geometry, sampling theory, and ecology as well as practical field experience, forest mensuration offers opportunities for creative problem solving and critical thinking.  This fifth edition of the classic volume, Forest Mensuration, includes coverage of traditional and emerging topics, with attention to SI and Imperial units throughout. The book has been reorganised from the fourth edition to better integrate non-timber and ecological aspects of forest mensuration at the tree, stand, forest, and landscape scales throughout.  The new edition includes new chapters that specifically address the integration of remotely sensed data in the forest inventory process, and inventory methods for dead and downed wood. One unifying theme, not only for traditional forestry but for the non-timber inventory and for remote sensing, is the use of covariates to make sampling more efficient and spatially explicit.  This is introduced in the introductory chapter on statistics and the chapter on sampling designs has been restructured to highlight this approach and lay the foundation for further learning. New examples will be developed throughout the textbook with an emphasis on current issues and international practice. Students in applied forestry programs will find ample coverage of forest products and timber inventory, while expanded material on biodiversity, biomass and carbon inventory, downed dead wood, and the growing role of remote sensing in forest assessment will be valuable to a broader audience in applied ecology.

Full Product Details

Author:   John A. Kershaw (University of New Brunswick, New Brunswick, Canada) ,  Mark J. Ducey (University of New Hampshire, USA) ,  Thomas W. Beers (Purdue University, West Lafayette, IN, USA) ,  Bertram Husch (Food and Agriculture Organization of the United Nations)
Publisher:   John Wiley and Sons Ltd
Imprint:   Wiley-Blackwell
Edition:   5th edition
Dimensions:   Width: 17.30cm , Height: 3.60cm , Length: 24.40cm
Weight:   1.066kg
ISBN:  

9781118902035


ISBN 10:   1118902033
Pages:   640
Publication Date:   30 December 2016
Audience:   Professional and scholarly ,  Professional & Vocational
Replaced By:   9781394282104
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

Table of Contents

Preface xiv 1 Introduction 1 1.1. Role of Forest Mensuration in Forest Management 2 1.2. Forest Mensuration as a Tool for Monitoring Forests 3 1.3. Relevance of Forest Mensuration for Ecology and Nontimber Resources 4 1.4. Design and Planning of Inventories 5 2 Principles of Measurement 13 2.1. Scales of Measurement 14 2.2. Units of Measurement 16 2.3. Systems of Measurement 16 2.4. Variables 21 2.5. Precision, Accuracy, and Bias 21 2.6. Significant Digits and Rounding Off 23 2.7. Data Summary and Presentation 27 2.8. Fundamental Measurements 30 3 Basic Statistical Concepts 34 3.1. Descriptive Statistics 34 3.2. Frequency Distributions 38 3.3. Measures of Central Tendency 40 3.4. Measures of Dispersion 42 3.5. Sampling Error 45 3.6. Sample Size Determination 50 3.7. Influence of Scalar Transformations and the Estimation of Totals 52 3.8. Correlation and Regression Estimation 53 3.9. Use of Covariates to Improve Estimation 63 4 Land Area Determination in Forest Mensuration 67 4.1. Land Distance and Area Units 68 4.2. Measuring Distances 68 4.3. Measuring Area in the Field 73 4.4. Measuring Area Using Maps and Photos 73 4.5. Determination of Photo Scale 76 4.6. Determination of Direction Using a Compass 80 4.7. The U.S. Public Land Surveys 82 4.8. Global Positioning Systems 86 4.9. Geographic Information Systems 89 5 Individual Tree Parameters 92 5.1. Age 92 5.2. Tree Diameters and Cross‐Sectional Areas 95 5.3. Height 108 5.4. Form 121 5.5. Crown Parameters 125 5.6. Regression and Allometric Approaches 130 6 Determination of Tree Volume Weight and Biomass 135 6.1. Measurement of Individual Trees 137 6.2. Allometric Equations for Volume, Weight, and Biomass 156 6.3. Tabular Estimation 160 6.4. Volume and Biomass Distribution in Trees 167 6.5. Other Methods of Estimating Tree Content 173 6.6. Applications to Seedlings and Understory Vegetation 179 6.7. Applications to Snags and Down Woody Material 179 7 Measurement of Primary Forest Products 184 7.1. Units of Measurement of Forest Products 184 7.2. Log Rules 186 7.3. Board Foot Log Rules 186 7.4. Log Scaling 195 7.5. Scaling Stacked Volume 199 7.6. Volume Unit Conversion 200 7.7. Scaling By Weight 204 8 Stand Parameters 210 8.1. Age 211 8.2. Species Composition 212 8.3. Diameter 219 8.4. Height 228 8.5. Volume, Weight, and Biomass 232 8.6. Crown and Canopy Measurements 236 8.7. Understory and Regeneration 239 8.8. Site Quality 250 8.9. Density and Stocking 259 9 Sampling Units for Estimating Parameters 273 9.1. The Factor Concept 274 9.2. Fixed‐Area Plots 276 9.3. Sampling Trees with Variable Probability 287 9.4. Other Examples of Variable Probability Sampling 298 9.5. Distance‐Based Sampling Units 299 9.6. Selecting Appropriate Sampling Units 303 10 Sampling Designs in Forest Inventories 305 10.1. Basic Considerations 305 10.2. Simple Random Sampling (SRS) 311 10.3. Systematic Sampling (SYS) 318 10.4. Selective or Opportunistic Sampling 326 10.5. Stratified Sampling (STS) 327 10.6. Cluster Sampling 334 10.7. Multistage Sampling 338 10.8. Sampling with Covariates 343 10.9. List Sampling 353 10.10. 3P Sampling 357 11 Inventory of Standing Trees Using Sampling with Varying Probability 361 11.1. Horizontal Point Sampling (HPS) 362 11.2. Subsampling in HPS 377 11.3. Other Variable Probability Sampling Techniques 386 12 Inventory of Downed Dead Material Using Sampling with Varying Probability 393 12.1. Fixed‐Area Plots 394 12.2. Line Intersect Sampling 398 12.3. Angle Gauge Methods 406 12.4. Perpendicular Distance Sampling (PDS) 414 12.5. Other Methods 425 12.6. Design Considerations and Selection of Methods 427 13 Integrating Remote Sensing in Forest Inventory 429 13.1. Types of Remotely Sensed Data 429 13.2. Remote Sensing for Stratification 442 13.3. Individual Tree Measurements 446 13.4. Remote Sensing for Covariates 449 14 Measurement of Tree and Stand Growth 455 14.1. Individual Tree Growth 456 14.2. Direct Measurement of Tree Growth 460 14.3. Reconstructing Tree Growth 465 14.4. Stand and Forest Growth 474 14.5. Measurement of Stand and Forest Growth and Yield 479 14.6. Considerations for the Design and Maintenance of Permanent Sample Plot Systems 494 14.7. Growth and Yield Models 503 Appendix 519 References 550 Index 592

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Author Information

John A. Kershaw, Jr. Faculty of Forestry and Environmental Management, University of New Brunswick, New Brunswick, Canada. Mark J. Ducey, Department of Natural Resources and the Environment, University of New Hampshire, USA. Thomas W. Beers, Emeritus Professor of Forestry, Purdue University, USA. Bertram Husch, former Forestry Consultant at INFORA Estudios Ltda. in Santiago, Chile, and former Forest Mensurationist, FAO.

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