Tree and Forest MeasurementSpringer Science & Business Media, 2004 - Всего страниц: 167 Trees and forests are large and complex, but even something as difficult as the amount of wood they contain can be measured with quite unsophisticated equipment. Everyone, from professional foresters to the layperson, who works with forests and needs to measure them no matter where in the world, will appreciate this book. It summarises modern forest measurement techniques and describes why forests are measured, how to measure them, and the basis of the science behind these techniques. Professor Phil West has been a forest scientist for over 30 years. His research speciality is the mathematical modelling of forest growth behaviour. He is presently a forestry consultant and teaches forest measurement in the forestry school of Southern Cross University in northern New South Wales, Australia. |
Содержание
11 Scope of this Book | 1 |
Scale of Measurement | 3 |
21 Measuring Things | 5 |
Accuracy Bias and Precision | 6 |
221 Accuracy | 7 |
222 Bias | 8 |
223 Precision | 9 |
Bias Precision and the Value of Measurements | 10 |
Basal Area | 71 |
Plot Measurement | 72 |
Practicalities of Point Sampling | 75 |
Stocking Density | 78 |
Quadratic Mean Diameter | 79 |
Measuring Dominant Height | 80 |
Site Productive Capacity | 81 |
89 Volume | 85 |
31 Basis of Stem Diameter Measurement | 13 |
Stem Crosssectional Shape | 14 |
Measuring Stem Diameter | 15 |
Tree Irregularities and Stem Diameter | 17 |
Bark Thickness | 18 |
41 Basis of Height Measurement | 19 |
Height by Direct Methods | 20 |
Height by Geometric Methods | 23 |
Height of Leaning Trees | 24 |
51 Reasons for Volume Measurement | 27 |
Volume by Xylometry | 28 |
Sectional Volume Formulae | 29 |
Tree Stem Shape | 30 |
Sectional Measurement of Felled Trees | 32 |
Sectional Measurement of Standing Trees | 33 |
Volume by Importance or Centroid Sampling | 34 |
61 Principles | 39 |
Stem Volume Functions | 40 |
Volume Estimated from Diameter Height and Taper | 44 |
Merchantable Stem Volume | 45 |
Taper Functions | 46 |
Examples of Taper Functions | 47 |
Using Taper Functions | 50 |
Developing Stem Volume and Taper Functions | 54 |
71 Reasons for Biomass Measurement | 57 |
Biomass by Direct Measurement | 58 |
Branches and Foliage | 59 |
722 Stems | 60 |
Carbon Content of Biomass | 61 |
Biomass Estimation Functions | 62 |
Allometric Functions | 63 |
Root Biomass Functions | 64 |
Leaf Biomass Functions | 65 |
Fineroot Biomass Functions | 67 |
81 Stands and Why they are Measured | 69 |
Measurements in Stands | 70 |
Point Sampling | 87 |
810 Biomass | 88 |
91 Forest Inventory and Sampling | 93 |
Subjective Versus Objective Sample Selection | 94 |
Population Statistics | 95 |
Variance and Confidence Limits | 96 |
101 Sampling Techniques and their Efficiency | 103 |
Sampling with Varying Probability of Selection | 104 |
Probability Proportional to Size | 105 |
Probability Proportional to Prediction | 109 |
Stratified Random Sampling | 112 |
Modelbased Sampling | 114 |
Choosing the Sampling Technique | 118 |
111 Objectives | 121 |
Stratification | 122 |
Forest Area | 123 |
Conduct of the Inventory | 124 |
Fixedarea Plot and Point Sampling | 126 |
117 Measuring Plots | 127 |
1171 Shape | 128 |
1173 Size | 129 |
1174 Edge Plots | 130 |
118 Conclusion | 131 |
121 Mapping | 133 |
Survey Example | 134 |
Calculating the Survey Results | 136 |
Plotting the Surveyed Area as Part of a Map | 141 |
Area of a Surveyed Region | 142 |
Global Positioning System | 144 |
References | 147 |
Appendix 1 Glossary | 153 |
Appendix 2 Conversion Factors | 159 |
Appendix 3 The Greek Alphabet | 161 |
Appendix 4 Basic Trigonometry | 163 |
| 165 | |
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allometric functions angle Australia bias branches breast height over-bark calculated clinometer confidence interval confidence limit covariate defined determine developed diameter at breast diameter over-bark discussed distance dominant height Ecology and Management estry Eucalyptus Eucalyptus regnans example forest area Forest Ecology forest inventory forest measurement forest types forestry global positioning system grid growth hypsometer individual trees leaf area index logs mean annual increment method model-based sampling number of trees Pinus Pinus patula plantation plot point sampling position PPS sampling precision predict productive capacity pulplogs regression analysis result sampling technique sampling units Sect selected simple random sampling slope stand basal area stand volume stem volume functions stem wood volume stocking density Suppose survey point Table taper functions theodolite top height total height tree biomass tree diameter tree height tree species tree stem volume trigonometric under-bark usually variable of interest woodland
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