1 / 39

Forest Sampling Simulation

Forest Sampling Simulation . Loukas G. Arvanitis University of Florida Robin M . Reich Colorado State University Valentina S. Boycheva Post-doctoral Associate, Univ. of Florida.

teryl
Download Presentation

Forest Sampling Simulation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Forest SamplingSimulation Loukas G. Arvanitis University of Florida Robin M. Reich Colorado State University Valentina S. Boycheva Post-doctoral Associate, Univ. of Florida

  2. “It is the mark of an educated mind to rest satisfied with the degree of precision, which the nature of the subject admits, and not to seek exactness where only an approximation is possible.” Aristotle (384-322 B.C.)

  3. Main Objective Assist students of all ages in: • Designing • Implementing • Interpreting COST-EFFECTIVE forest inventories (Maximize information per unit cost)

  4. Prerequisites a) An introductory course in statistics. b) Basic knowledge of computer simulation c) Critical thinking d) Perseverance

  5. Basic Components of FOSS • Spatial distribution of trees • Cost and precision constraints • Sampling units • Allocation of samples (sampling designs).

  6. FOSS • Spatial pattern of trees • Random • Aggregated • Uniform (plantation type) • Distribution of tree DBH • Normal • Weibull

  7. Random Pattern

  8. Aggregated Pattern

  9. Uniform Pattern

  10. Tree Gradients • East - West • North - South • Combination of E-W and N-S

  11. Sequence of Tasks • Assess spatial pattern of the population • Decide on cost and precision constraints • Determine number, size, and shape of the elementary sampling unit • Select sampling method • Decide on single or repeated sampling • Implement selected sampling method • Evaluate results

  12. Elementary Sampling Units • Square • Rectangle • Circle • Strip • Line • Point

  13. Available Sampling Designs • Simple random • Systematic • Stratified (Proportional, Neyman, Optimal) • 3-P • Vertical Point • Vertical Line • Horizontal Line • Multi-phase • Multi-stage • ListSampling • Double sampling with regression

  14. Vertical Point Sampling

  15. Vertical Line Sampling

  16. Horizontal Line Sampling (Hush, Beers, & Kershaw, Jr. 2003)

  17. Density Estimation • Quadrat sampling is used in forestry, range, wildlife, and ecology to sample frequency, density, abundance, and presence. • Distance sampling was developed primarily to study the spatial relationships that exist in biological populations.

  18. Forest Variables of Interest in FOSS • Mean/total basal area • Mean/total volume • Mean DBH • Total tree height

  19. 1

  20. Selection of Sampling Units • Most efficient: one that samples proportional to the variance of the stand parameter of interest. • Density: fixed area plots • Basal Area and Volume: horizontal point sample • Unbiased estimates of forest parameters can be obtained from any plot type and size. • The precision and cost may vary significantly.

  21. Selection of Sampling Units • For a given sampling intensity, the smaller the sampling unit, the greater will be the precision because there will be more samples. • However, large (n) will increase the cost of sampling. • In general, the cost of sampling will be greater for a large number of sample units than for fewer samples of larger size.

  22. Cost $ Sample Size (n) Selection of Sampling Units

  23. Selection of Sampling Units • If sampling units are too small, the probability that they may be representative of the population decreases. • Ultimately, the size of the sampling unit should be large enough to include a representative number of trees but small enough that the time required for measurements is not excessive.

  24. Concluding Remarks • FOSS: interactive program to enhance students’ comprehension of basic concepts on sampling forests in a cost effective manner. • Main idea: assist students in advancing from dependent memorization to independent thinking and problem solving ability.

  25. Concluding Remarks • Allows students to explore a wide variety of alternative solutions through computer simulation, linking theory and practice. • Gradients of different densities: East-West, N-S, and E-W /N-S, valuable for foresters, ecologies, range specialists, and wildlife professionals.

  26. Concluding Remarks • Aims at student’s awareness of fundamental concepts related to sampling efficiency and the thinking process of maximizing the amount of information per unit effort or cost.

  27. Concluding Remarks • Assists students in becoming actively involved in the decision-making process (rewards and penalties) attributed to their actions. • Although FOSS does not process field data, it is a powerful scientific tool for understanding, implementing, and properly interpreting forest sampling.

  28. Concluding Remarks FOSS works in the following operating systems: • MS Windows NT • MS Windows 2000 • MS Windows XP

  29. Words of Wisdom Jonathan Swift, an Irish-born satirist of the 17th century said that: “A man should never be ashamed to own he had been in the wrong, which is but saying, in other words, that he is wiser today than he was yesterday”. THANK YOU FOR YOUR ATTENTION

More Related