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Produktbild: Forest Inventory
Band 10

Forest Inventory Methodology and Applications

Aus der Reihe Managing Forest Ecosystems

Fr. 162.00

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

10.07.2009

Herausgeber

Annika Kangas + weitere

Verlag

Springer Netherland

Seitenzahl

362

Maße (L/B/H)

23.5/15.5/2.4 cm

Gewicht

651 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-90-481-3164-8

Beschreibung

Rezension

From the reviews:“This book achieving its aim to serve as an academic textbook and as a practical manual … . the mix of useful information and impediments in the book recommends it as textbook and brain-trainer to students at EU universities. It gives an interesting overview over the complexities, problems and impressive achievements of forest inventory in Finland and is a welcome mental fitness trainer for inquisitive, integrating, coordinating and logical thinking, which I rather enjoyed.” (Eberhard F. Bruenig, International Forestry Review, Vol. 11 (4), 2009)

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

10.07.2009

Herausgeber

Verlag

Springer Netherland

Seitenzahl

362

Maße (L/B/H)

23.5/15.5/2.4 cm

Gewicht

651 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-90-481-3164-8

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Forest Inventory
  • Preface. Acknowledgements. List of contributing authors. Part I: Theory. 1. Introduction; A. Kangas et al. 1.1 General. 1.2 Historical background of sampling theory. 1.3 History of forest inventories. References.- 2. Design-based sampling and inference; A. Kangas. 2.1 Basis for probability sampling. 2.2 Simple random sampling. 2.3 Determining the sample size. 2.4 Systematic sampling. 2.5 Stratified sampling. 2.6 Cluster sampling. 2.7 Ratio and regression estimators. 2.8 Sampling with probability proportional to size. 2.9 Non-linear estimators. 2.10 Resampling. 2.11 Selecting the sampling method. References.- 3. Model-based inference; A. Kangas. 3.1 Foundations of model-based inference. 3.2 Models. 3.3 Applications of model-based methods to forest inventory. 3.4 Model-based versus design-based inference. References.- 4. Mensurational aspects; A. Kangas. 4.1 Sample plots. 4.1.1 Plot size. 4.1.2 Plot shape. 4.2 Point sampling. 4.3 Comparison of fixed-sized plots and points. 4.4 Plots located on an edge or slope. 4.4.1 Edge corrections. 4.4.2 Slope corrections. References.- 5. Change monitoring with permanent sample plots; S. Poso. 5.1 Concepts and notations. 5.2 Choice of sample plot type and tree measurement. 5.3 Estimating components of growth at the plot level. 5.4 Monitoring volume and volume increment over two or more measuring periods at the plot level. 5.5 Estimating population parameters. 5.6 Concluding remarks. References.- 6. Generalizing sample tree information; J. Lappi et al. 6.1 Estimation of tally tree regression. 6.2 Generalizing sample tree information in a small subpopulation. 6.2.1 Mixed estimation. 6.2.2 Applying mixed models. 6.3 A closer look at the three-level model structure. References.- 7. Use of additional information; J. Lappi, A. Kangas. 7.1 Calibration estimation. 7.2 Small area estimates. References.- 8. Sampling rare populations; A. Kangas. 8.1 Methods for sampling rare populations. 8.1.1 Principles. 8.1.2 Strip sampling. 8.1.3 Line intersect sampling. 8.1.4 Adaptive cluster sampling. 8.1.5 Transect and point relascope sampling. 8.1.6 Guided transect sampling. 8.2 Wildlife populations. 8.2.1 Line transect sampling. 8.2.2 Capture-recapture methods. 8.2.3 The wildlife triangle scheme. References.- 9. Inventories of vegetation, wild berries and mushrooms; M. Maltamo. 9.1 Basic principles. 9.2 Vegetation inventories. 9.2.1 Approaches to the description of vegetation. 9.2.2 Recording of abundance. 9.2.3 Sampling methods for vegetation analysis. 9.3 Examples of vegetation surveys. 9.4 Inventories of mushrooms and wild berries. References.- 10. Assessment of uncertainty in spatially systematic sampling; J. Heikkinen. 10.1 Introduction. 10.2 Notation, definitions and assumptions. 10.3 Variance estimators based on local differences. 10.3.1 Restrictions of SRS-estimator. 10.3.2 Development of estimators based on local differences. 10.4 Variance estimation in the national forest inventory in Finland. 10.5 Model-based approaches. 10.5.1 Modelling spatial variation. 10.5.2 Model-based variance and its estimation. 10.5.3 Descriptive versus analytic inference. 10.5.4 Kriging in inventories. 10.6 Other sources of uncertainty. References.- Part II: Applications. 11. The Finnish national forest inventory; E. Tomppo. 11.1 Introduction. 11.2 Field sampling system used in NFI9. 11.3 Estimation based on field data. 11.3.1 Area estimation. 11.3.2 Volume estimation. 11.3.2.1 Predicting sample tree volumes and volumes by timber assortment classes. 11.3.2.2 Predicting volumes for tally trees. 11.3.3.3 Computing volumes for computation units. 11.4 Increment estimation. 11.5 Conclusions. References.-