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E-raamat: Forest Mensuration

(Purdue University, West Lafayette, IN, USA), (Food and Agriculture Organization of the United Nations), (University of New Hampshire, USA), (University of New Brunswick, New Brunswick, Canada)
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  • Ilmumisaeg: 04-Nov-2016
  • Kirjastus: Wiley-Blackwell
  • Keel: eng
  • ISBN-13: 9781118902011
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  • Ilmumisaeg: 04-Nov-2016
  • Kirjastus: Wiley-Blackwell
  • Keel: eng
  • ISBN-13: 9781118902011
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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 worlds 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.
Preface xiv
1 Introduction 1(12)
1.1 Role of Forest Mensuration in Forest Management
2(1)
1.2 Forest Mensuration as a Tool for Monitoring Forests
3(1)
1.3 Relevance of Forest Mensuration for Ecology and Nontimber Resources
4(1)
1.4 Design and Planning of Inventories
5(8)
1.4.1 Timber Estimation
5(2)
1.4.2 Nontimber Estimation
7(1)
1.4.3 Inventory Planning
7(3)
1.4.4 Forest Inventory Design
10(1)
1.4.5 Inventory Fieldwork
11(2)
2 Principles of Measurement 13(21)
2.1 Scales of Measurement
14(2)
2.2 Units of Measurement
16(1)
2.3 Systems of Measurement
16(5)
2.3.1 International System of Units (Metric System)
16(2)
2.3.2 Imperial System
18(2)
2.3.3 Conversions Between Systems
20(1)
2.4 Variables
21(1)
2.5 Precision, Accuracy, and Bias
21(2)
2.6 Significant Digits and Rounding Off
23(4)
2.6.1 Significant Digits in Measurements
23(1)
2.6.2 Rounding Off
24(1)
2.6.3 Significant Digits in Arithmetic Operations
25(2)
2.7 Data Summary and Presentation
27(3)
2.7.1 Tables
28(1)
2.7.2 Graphic Presentation
28(1)
2.7.3 Class Limits
29(1)
2.8 Fundamental Measurements
30(4)
2.8.1 Linear Measurements
30(1)
2.8.2 Time Measurements
31(1)
2.8.3 Weight Measurements
31(1)
2.8.4 Area Measurements
32(1)
2.8.5 Volume Measurements
33(1)
3 Basic Statistical Concepts 34(33)
3.1 Descriptive Statistics
34(4)
3.1.1 Population
35(1)
3.1.2 Sample
35(3)
3.1.3 Statistics
38(1)
3.2 Frequency Distributions
38(2)
3.3 Measures of Central Tendency
40(2)
3.3.1 Arithmetic Mean
40(1)
3.3.2 Quadratic Mean
41(1)
3.3.3 Harmonic and Geometric Means
42(1)
3.3.4 Median and Mode
42(1)
3.4 Measures of Dispersion
42(3)
3.4.1 Variance and Standard Deviation
43(2)
3.4.2 Coefficient of Variation
45(1)
3.5 Sampling Error
45(5)
3.5.1 Standard Error of the Mean
46(2)
3.5.2 Confidence Interval
48(2)
3.6 Sample Size Determination
50(2)
3.7 Influence of Scalar Transformations and the Estimation of Totals
52(1)
3.8 Correlation and Regression Estimation
53(10)
3.8.1 Covariance and Correlation
53(3)
3.8.2 Simple Linear Regression
56(2)
3.8.3 Goodness-of-Fit and Regression Diagnostics
58(3)
3.8.4 Multiple Regression and Transformations
61(2)
3.8.5 Advanced Topics in Regression Analysis
63(1)
3.9 Use of Covariates to Improve Estimation
63(4)
3.9.1 Ratio Estimation
64(1)
3.9.2 Regression Estimation
65(2)
4 Land Area Determination in Forest Mensuration 67(25)
4.1 Land Distance and Area Units
68(1)
4.2 Measuring Distances
68(5)
4.2.1 Pacing
69(1)
4.2.2 Distances with Chains and Tapes
69(2)
4.2.3 Optical Rangefinders
71(1)
4.2.4 Electronic Distance Measurement Devices
71(1)
4.2.5 Maps and Photos
72(1)
4.3 Measuring Area in the Field
73(1)
4.4 Measuring Area Using Maps and Photos
73(3)
4.4.1 Area by Coordinates
73(2)
4.4.2 Area by Dot Grids and Line Transects
75(1)
4.4.3 Area by Planimeters
76(1)
4.5 Determination of Photo Scale
76(4)
4.6 Determination of Direction Using a Compass
80(2)
4.6.1 Magnetic Declination
80(2)
4.7 The U.S. Public Land Surveys
82(4)
4.8 Global Positioning Systems
86(3)
4.8.1 Components of GPS
86(1)
4.8.2 How GPS Works
86(1)
4.8.3 Accuracy of GPS
87(1)
4.8.4 GPS Receivers
88(1)
4.8.5 Using GPS Data in Forest Mensuration
89(1)
4.9 Geographic Information Systems
89(3)
4.9.1 Applications of GIS to Forest Mensuration
90(2)
5 Individual Tree Parameters 92(43)
5.1 Age
92(3)
5.2 Tree Diameters and Cross-Sectional Areas
95(13)
5.2.1 Instruments for Measuring Diameter
98(5)
5.2.2 Measurement of Upper-Stem Diameters
103(1)
5.2.3 Cross-Sectional Area
104(2)
5.2.4 Surface Areas
106(1)
5.2.5 Applications to Understory Plants
107(1)
5.3 Height
108(13)
5.3.1 Hypsometers Based on Similar Triangles
110(2)
5.3.2 Hypsometers Based on Trigonometry
112(5)
5.3.3 Special Considerations in Measuring Tree Heights
117(3)
5.3.4 Use of LiDAR
120(1)
5.4 Form
121(4)
5.4.1 Form Factors
121(1)
5.4.2 Form Quotients
122(1)
5.4.3 Taper Tables, Curves, and Formulas
123(1)
5.4.4 Slenderness
124(1)
5.5 Crown Parameters
125(5)
5.5.1 Crown Length
125(1)
5.5.2 Crown Diameter and Area
126(1)
5.5.3 Crown Surface Area and Volume
127(1)
5.5.4 Foliage Area and Biomass
128(1)
5.5.5 Other Crown Characteristics
129(1)
5.6 Regression and Allometric Approaches
130(5)
5.6.1 Allometry of Standing Trees
130(2)
5.6.2 Applications to Seedlings, Saplings, and Understory Plants
132(3)
6 Determination of Tree Volume, Weight, and Biomass 135(49)
6.1 Measurement of Individual Trees
137(19)
6.1.1 Stem Dissection
137(1)
6.1.2 Volume Determination by Displacement
138(1)
6.1.3 Volume Determination by Formulas
139(5)
6.1.4 Determination of Cubic Volume by Graphical Methods and Integration
144(3)
6.1.5 Determination of Crown and Root Volumes
147(1)
6.1.6 Determination of Bark Volume
148(3)
6.1.7 Weight Determination
151(2)
6.1.8 Biomass Determination
153(1)
6.1.9 Carbon and Nutrient Content Determination
154(2)
6.2 Allometric Equations for Volume, Weight, and Biomass
156(4)
6.2.1 Standard and Form Class Functions
157(1)
6.2.2 Local Functions
158(1)
6.2.3 Volume Functions to Upper-Stem Diameter Limits
159(1)
6.3 Tabular Estimation
160(7)
6.3.1 Descriptive Information to Accompany Tables
165(1)
6.3.2 Checking Applicability of Tables
166(1)
6.3.3 Conversion of Volume Tables to Weight, Biomass, or Carbon and Nutrient Tables
166(1)
6.4 Volume and Biomass Distribution in Trees
167(6)
6.4.1 Methods for Estimating Stem Volume Distribution
167(3)
6.4.2 Distribution of Weight and Biomass in Trees
170(3)
6.5 Other Methods of Estimating Tree Content
173(6)
6.5.1 Determination of Volume by Height Accumulation
173(3)
6.5.2 Importance Sampling and Centroid Methods
176(3)
6.6 Applications to Seedlings and Understory Vegetation
179(1)
6.7 Applications to Snags and Down Woody Material
179(5)
6.7.1 Standing Dead Trees
179(2)
6.7.2 Downed Woody Material
181(3)
7 Measurement of Primary Forest Products 184(26)
7.1 Units of Measurement of Forest Products
184(2)
7.1.1 Board Foot
184(1)
7.1.2 Volume Units for Stacked Wood
185(1)
7.2 Log Rules
186(1)
7.3 Board Foot Log Rules
186(9)
7.3.1 Mill-Study Log Rules
187(1)
7.3.2 Diagram Log Rules
187(2)
7.3.3 Mathematical Log Rules
189(2)
7.3.4 Combination Log Rules
191(1)
7.3.5 Comparison of Log Rules
191(1)
7.3.6 Tabular Presentation of Log Rules
192(3)
7.4 Log Scaling
195(4)
7.4.1 Board Foot Scaling
195(3)
7.4.2 Cubic Volume Scaling
198(1)
7.4.3 Unmerchantable Logs
198(1)
7.4.4 Sample scaling
198(1)
7.5 Scaling Stacked Volume
199(1)
7.6 Volume Unit Conversion
200(4)
7.6.1 Determination of Solid Cubic Contents of Stacked Wood
202(2)
7.7 Scaling By Weight
204(6)
7.7.1 Weight Measurement of Pulpwood
204(3)
7.7.2 Weight Measurement of Sawlogs
207(1)
7.7.3 Weight Measurement of Pulp
208(1)
7.7.4 Weight Measurement of Other Forest Products
209(1)
8 Stand Parameters 210(63)
8.1 Age
211(1)
8.1.1 Even-Aged and Single-Cohort Stands
211(1)
8.1.2 Uneven-Aged and Multicohort Stands
211(1)
8.2 Species Composition
212(7)
8.2.1 Describing Species Composition
213(1)
8.2.2 Number and Diversity of Species
214(4)
8.2.3 Assigning Stand Types
218(1)
8.3 Diameter
219(9)
8.3.1 Expressions of Mean Diameter
220(1)
8.3.2 Basal Area
221(1)
8.3.3 Diameter Distributions
221(7)
8.4 Height
228(4)
8.4.1 Expressions of Mean Height
229(1)
8.4.2 Height-Diameter Curves
230(1)
8.4.3 Height-Diameter Ratio
231(1)
8.5 Volume, Weight, and Biomass
232(4)
8.5.1 Volume
232(2)
8.5.2 Weight, Biomass, and Carbon Content
234(1)
8.5.3 Volume, Weight, and Biomass of Dead Wood
235(1)
8.6 Crown and Canopy Measurements
236(3)
8.6.1 Crown Closure and Canopy Cover
236(1)
8.6.2 Leaf Area Index
237(2)
8.7 Understory and Regeneration
239(11)
8.7.1 Density and Frequency
240(1)
8.7.2 Cover and Competition
241(5)
8.7.3 Biomass and Forage
246(1)
8.7.4 Regeneration Surveys
247(3)
8.8 Site Quality
250(9)
8.8.1 Geocentric Approaches
251(2)
8.8.2 Phytocentric Approaches Using Vegetation Composition
253(1)
8.8.3 Dendrocentric Approaches
254(3)
8.8.4 Preparation of Site Index Curves
257(2)
8.9 Density and Stocking
259(14)
8.9.1 Relative Density Based on Volume
260(1)
8.9.2 Stand Density Index
261(2)
8.9.3 Tree-Area Ratio
263(1)
8.9.4 Crown Competition Factor
264(2)
8.9.5 Relative Spacing
266(1)
8.9.6 Density of Mixed-Species and Complex-Structure Stands
266(1)
8.9.7 Point Density and Competition Indices
266(3)
8.9.8 Forest Stocking and Density Management Diagrams
269(4)
9 Sampling Units for Estimating Parameters 273(32)
9.1 The Factor Concept
274(2)
9.2 Fixed-Area Plots
276(11)
9.2.1 Circular Plots
276(1)
9.2.2 Square and Rectangular Plots
277(1)
9.2.3 Subplots
278(1)
9.2.4 Selection of Plots and Trees
279(1)
9.2.5 Stand and Stock Tables
280(4)
9.2.6 Boundary Slopover
284(3)
9.3 Sampling Trees with Variable Probability
287(11)
9.3.1 Horizontal Point Samples
287(6)
9.3.2 Stand and Stock Tables
293(3)
9.3.3 Boundary Slopover Bias
296(1)
9.3.4 Other Forms of Sampling Proportional to Size
296(2)
9.4 Other Examples of Variable Probability Sampling
298(1)
9.4.1 Point Intercept Sampling
298(1)
9.4.2 Line Intercept Sampling
299(1)
9.5 Distance-Based Sampling Units
299(4)
9.5.1 Nearest-Neighbor Methods
299(3)
9.5.2 Distance Sampling
302(1)
9.6 Selecting Appropriate Sampling Units
303(2)
10 Sampling Designs in Forest Inventories 305(56)
10.1 Basic Considerations
305(6)
10.1.1 Errors in Forest Inventories
306(2)
10.1.2 Confidence Limits
308(2)
10.1.3 Precision Level and Intensity
310(1)
10.2 Simple Random Sampling (SRS)
311(7)
10.2.1 Influence of Plot Size on Simple Random Sample Designs
315(3)
10.3 Systematic Sampling (SYS)
318(8)
10.3.1 Systematic Plot Sampling
318(4)
10.3.2 Sampling Error for a SYS Inventory
322(2)
10.3.3 Systematic Strip Sampling
324(2)
10.4 Selective or Opportunistic Sampling
326(1)
10.5 Stratified Sampling (STS)
327(7)
10.5.1 Estimation of Number of Sampling Units
330(2)
10.5.2 Sample Efficiency
332(2)
10.6 Cluster Sampling
334(4)
10.7 Multistage Sampling
338(5)
10.8 Sampling with Covariates
343(10)
10.8.1 Regression Sampling
344(5)
10.8.2 Double Sampling
349(4)
10.9 List Sampling
353(4)
10.10 3P Sampling
357(4)
11 Inventory of Standing Trees Using Sampling with Varying Probability 361(32)
11.1 Horizontal Point Sampling (HPS)
362(15)
11.1.1 Angle Gauges for HPS
362(5)
11.1.2 Photographic Methods
367(1)
11.1.3 Sample Size
368(1)
11.1.4 Choosing a Suitable Gauge Constant
369(2)
11.1.5 Proper Use of Gauges
371(1)
11.1.6 Checking Questionable Trees
372(2)
11.1.7 Slope Correction
374(1)
11.1.8 Leaning and Hidden Trees
374(1)
11.1.9 Volume Estimation
375(1)
11.1.10 Special-Purpose Modifications of HPS
376(1)
11.2 Subsampling in HPS
377(9)
11.2.1 Big BAF Sampling
377(5)
11.2.2 Point 3P Sampling
382(4)
11.3 Other Variable Probability Sampling Techniques
386(7)
11.3.1 Horizontal Line Sampling (HLS)
386(3)
11.3.2 Vertical Point and Line Sampling
389(2)
11.3.3 Critical Height Sampling
391(2)
12 Inventory of Downed Dead Material Using Sampling with Varying Probability 393(36)
12.1 Fixed-Area Plots
394(4)
12.2 Line Intersect Sampling
398(8)
12.2.1 Assumptions of Line Intersect Sampling
399(2)
12.2.2 Estimating Downed Wood Parameters
401(3)
12.2.3 Choosing a Line Length and Design
404(2)
12.2.4 Adaptation for Fine Fuels
406(1)
12.3 Angle Gauge Methods
406(8)
12.3.1 Transect Relascope Sampling
406(4)
12.3.2 Point Relascope Sampling
410(1)
12.3.3 Gauge Construction and Choice of Angle
411(2)
12.3.4 Estimating Downed Wood Parameters
413(1)
12.3.5 Practical Aspects
413(1)
12.4 Perpendicular Distance Sampling (PDS)
414(11)
12.4.1 PDS for Volume
415(4)
12.4.2 Distance-Limited PDS
419(1)
12.4.3 PDS for Other Attributes
420(2)
12.4.4 Estimating Multiple Downed Wood Attributes
422(2)
12.4.5 Choosing a Design and Factor
424(1)
12.5 Other Methods
425(2)
12.5.1 Diameter Relascope Sampling
425(1)
12.5.2 Critical Length Sampling
426(1)
12.5.3 Line Intersect Distance Sampling
426(1)
12.6 Design Considerations and Selection of Methods
427(2)
13 Integrating Remote Sensing in Forest Inventory 429(26)
13.1 Types of Remotely Sensed Data
429(13)
13.1.1 Aerial Analog Photography
431(2)
13.1.2 Moderate-Resolution Optical Data
433(2)
13.1.3 High-Resolution Optical Data
435(1)
13.1.4 LiDAR
436(4)
13.1.5 Synthetic Aperture Radar
440(1)
13.1.6 Hyperspectral Data
441(1)
13.2 Remote Sensing for Stratification
442(4)
13.2.1 Photo Interpretation and Stand Mapping
442(2)
13.2.2 Pixel-Based Classification
444(1)
13.2.3 Object-Oriented Classification
444(1)
13.2.4 Effects of Misclassification on Estimation
445(1)
13.3 Individual Tree Measurements
446(3)
13.3.1 Crown Widths
447(1)
13.3.2 Tree Heights
448(1)
13.3.3 Estimating Stand Characteristics
448(1)
13.4 Remote Sensing for Covariates
449(6)
13.4.1 Tree and Stand Attributes and Sampling Covariates
449(2)
13.4.2 Applications to Ratio and Regression Sampling
451(2)
13.4.3 Imputation and Mapping
453(1)
13.4.4 Areal Importance Sampling
454(1)
14 Measurement of Tree and Stand Growth 455(64)
14.1 Individual Tree Growth
456(4)
14.1.1 Tree Growth Curves
456(2)
14.1.2 Growth Percent
458(2)
14.2 Direct Measurement of Tree Growth
460(5)
14.2.1 Diameter Growth Measurement
461(1)
14.2.2 Height Growth Measurement
462(1)
14.2.3 Crown Growth Measurements
463(1)
14.2.4 Belowground Growth Measurements
463(2)
14.3 Reconstructing Tree Growth
465(9)
14.3.1 Stem Analysis
465(1)
14.3.2 Estimating Diameter Growth from Increment Cores
466(6)
14.3.3 Allometric Relationships
472(2)
14.4 Stand and Forest Growth
474(5)
14.4.1 Components of Stand Growth
474(1)
14.4.2 Types of Stand Growth
475(4)
14.5 Measurement of Stand and Forest Growth and Yield
479(15)
14.5.1 Stand Reconstruction
479(2)
14.5.2 Estimation of Stand Growth and Yield from Temporary Sample Plots
481(1)
14.5.3 Estimation of Stand Growth and Yield from Fixed-Area Permanent Sample Plots
481(3)
14.5.4 Estimation of Stand Growth and Yield from Permanent Variable Probability Sample Points
484(10)
14.6 Considerations for the Design and Maintenance of Permanent Sample Plot Systems
494(9)
14.6.1 Sampling Unit Type
497(1)
14.6.2 Sampling Unit Size and Shape
498(1)
14.6.3 Sampling Unit Layout
498(1)
14.6.4 Measurement Protocols
499(4)
14.7 Growth and Yield Models
503(16)
14.7.1 Stand Table Projection
504(5)
14.7.2 Yield Tables and Equations
509(7)
14.7.3 Diameter Distribution Models
516(1)
14.7.4 Individual Tree Growth and Yield Models
516(1)
14.7.5 Other Types of Models
517(1)
14.7.6 Feedbacks between Growth and Yield Models and Forest Mensuration
518(1)
Appendix 519(31)
References 550(42)
Index 592
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.