Preface. 1. Introduction. 2. Statistical Prerequisites. 2.1 Introduction. 2.2 Scales and units of measurement. 2.3 Graphical presentation of data. 2.4 Descriptive statistics. 2.5 Probability distributions. 2.6 Estimation. 2.7 Regression and correlation analysis. 2.8 Moving average. 2.9 Smoothening by fitting equations. 2.10 Freehand fitting. 3. Instruments. 3.1 Diameter measuring instruments. 3.2 Relascopes and prisms. 3.3 Tree height. 3.4 Blume-Leiss range-traces drum. 3.5 Tree crown and foliage. 3.6 Short-term radial growth responses. 3.7 Increment cores. 3.8 Bark thickness. 3.9 Recent developments in instrumentation. 4. Single Tree Measurements. 4.1 Measurements on standing trees. 4.2 Volume, log classes and weight of felled trees. 5. Measurement of Stands. 5.1 Introduction. 5.2 Age. 5.3 Mean diameter. 5.4 Diameter distributions. 5.5 Stand tables. 5.6 Stand height. 5.7 Stand volume. 5.8 Spatial distribution of trees. 5.9 Stand density. 6. Taper Tables and Functions. 6.1 Taper tables. 6.2 Stem profile models. 7. Tree Volume Tables and Equations. 7.1 Introduction. 7.2 Volume equations with one predictor variable. 7.3 Equations with two predictor variables. 7.4 Equations with more than two predictor variables. 7.5 Merchantable volume. 8. Tree and Stand Biomass. 8.1 Introduction. 8.2 Biomass components. 8.3 Tree level regression models. 8.4 Additivity of biomass components. 8.5 Dummy-variables for tree species. 8.6 Ratio estimators and cluster sampling. 9. Growth and Yield. 9.1 Definitions. 9.2 The growth of single trees. 9.3 Site class and site index. 9.4 The growth of stands. 10. Sampling for Forest Inventories. 10.1 Introduction. 10.2 Plot sampling. 10.3 Point sampling. 10.4 Simple random sampling. 10.5 Error propagation. 10.6 Stratified random sampling. 10.7 Regression and ratio estimators. 10.8 Double sampling (Two-phase sampling). 10.9 Cluster sampling. 10.10 Multistage sampling. 10.11 Strip sampling. 10.12 Sampling with unequal selection probabilities. 10.13 Systematic sampling. 10.14 Sampling proportions. 10.15 Estimating changes. 10.16 Line intersect sampling. 11. Remote Sensing in Forest Mensuration. 11.1 Introduction. 11.2 Fundamentals of aerial photography. 11.3 Dendrometric data. 11.4 Estimation of stand volume. 11.5 The estimation of volume increment. Appendix. A. Symbols, Greek letter. B. Diameter data of sampling trees. C. Sample tree data for fitting stand height curves. D. Conversion factors for linear, square, cubic and weight measures. Bibliography. Index.

Forest mensuration is one of the most fundamental disciplines within forest and related sciences. It deals with the measurement of trees and stands and the analysis of the resultant information. During the early days of sustained forest management simple measurement and estimation methods and with the analysis of inventory and research data were available. The middle of last c- tury, however, witnessed a worldwide increase in the need for more quan- tative information about trees and stands. This generated the need for more sophisticated methods to obtain and analyze forest data. This development was followed by a phenomenal explosion of information. During the past decades there has been fruitful cooperation between the Institute of Forest Inventory and Forest Growth, formerly ¿Institute of Forest Management and Forest Yield Sciences¿ of the University of Gottingen, ¿ Germany and the Faculty of Forestry of the University of Stellenbosch, South Africa. This book is one of the results of this fruitful cooperation between these institutions.

ANTHONIE VAN LAAR was born in the Netherlands in 1923 and studied forest science at the University and Research Centre Wageningen between 1941 and 1949. In 1958 he emigrated to South Africa and obtained the D.Sc.degree in Forest Science at the University of Stellenbosch (1961) and thereafter Dr.oec.pub (1973) and Dr.hab. (1979) at the University of Münich. The theses dealt with forest biometry and growth modeling. Since his retirement in 1988 the author continued his involvement in these subjects, more particularly in growth models for
Eucalyptus grandis
.

ALPARSLAN AKCA (born 1936) studied forestry at the University of Istanbul an Freiburg i. Br. He received his doctorate in Forestry at the University of Freiburg on identification of land use classes and forest types by means of microdensitometer and discriminant analyses in 1970 and his habilitations in photogrammetry and geodesy at the University of Istanbul in 1976 and in forest inventory and forest management at the University of Göttingen in 1981. He is Professor for Forest Management, Forest Inventory and Remote sensing at the University of Göttingen and retired 2001. His main research interest are forest mensuration. Forest inventory and remote sensing in forestry.