Sampling the Landscape

• Scenario: You have been told from people who fish cypress creek regularly that the species density and composition of both fish and shellfish change dramatically below the golf course (the old Florence landfill)... You are a curious scientist.

• How do you find the answer?

• Scenario: You are working on creating a land cover/land use image for central Asia in the Tien Shen mountains. You have spent many hours creating what you believe is the BEST landcover/landuse classification possible...

• How do you know your classification is correct?

• Scenario: You are traveling in a place you have never been before. You want to make sure you have a good basis to evaluate this new place... You want to avoid being influenced by ‘wow’ factors nor do you want to only remember the first and last place you visited.

• How can you insure an objective assessment?

Options to characterize apopulation

• Census: observe every element in a population

• Sample: observe selected elements in

population and extrapolate properties to

population characteristics

Statistical Sampling….

http://yosemite.epa.gov/R10/OEA.NSF/34090D07B77D50BD88256B79006529E8/F3974A8B1ED416A188256CA800759EFA?OpenDocument

• BY A SMALL SAMPLE, WE MAY JUDGE THE WHOLE PIECE

---- Miguel de Cervantes

Typical objectives of a sampling design for

environmental data collection are:• To determine whether certain characteristics of

two populations differ by some amount,• To estimate the mean characteristics of a

population or the proportion of a population that has certain characteristics of interest,

• To identify the location of “hot spots” (areas having high levels or concentration) or plume delineation,

• To monitor trends in environmental conditions or indicators of health.

Guidance on Choosing aSampling Design for Environmental

Data Collectionfor Use in Developing a Quality

Assurance Project PlanEPA QA/G-5S

http://yosemite.epa.gov/R10/OEA.NSF/34090D07B77D50BD88256B79006529E8/F3974A8B1ED416A188256CA800759EFA?OpenDocument

“...A well-planned sampling design is intended to ensure that resulting data are representative of the target population and defensible for their intended use....”

SAMPLING DESIGN CONCEPTS AND TERMS

• Target population is the set of all units that comprise the items of interest in a scientific study

• Sampled population is that part of the target population that is accessible and available for sampling.

• sampling unit is a member of the population that may be selected for sampling, such as individual trees, or a specific volume of air or water.

• measurement protocol is a specific procedure for making observations or performing analyses to determine the characteristics of interest for each sampling unit.

Two main categories of sampling designs:

• Probability-based sampling designs apply sampling theory and involve random selection of sampling units.

(quantitative conclusions about the sampled population are produced)

• Judgmental sampling designs involve the selection of sampling units on the basis of expert knowledge or professional judgment.

(statistical analysis tools cannot be used, conclusions can only be drawn on the basis of professional judgment)

Simple Random Sampling

• Selected using random numbers, and all possible selections of a given number of units are equally likely.

• ‘Traditional’ statistical technique, familiar to all statistics courses

• most useful when the population of interest is relatively homogeneous

• can be more costly due to difficulties in obtaining samples (inaccessible areas, transportation difficulties)

• Can be invalid in a heterogeneous environment• no bias in the sample selection (can occur if units are

selected subjectively.

Stratified Random Sampling

• target population is separated into strata, or subpopulations that are thought to be more homogeneous

• There is less variation among sampling units in the same stratum than among sampling units in different strata.

• potential for achieving greater precision in estimates of the mean and variance

• Water/land

Systematic or Grid Sampling

• samples are taken at regularly spaced intervals over space or time.

• useful for estimating spatial patterns over a large area or trends over time.

• ensures uniform coverage of a site.

How many points need to be sampled?

• Somebody is always going to argue that you need more points.

• Traditionally, 20 is the number of observations needed to be considered significant

• 2%-80% ‘rule’.... Unofficially, from Compton Tucker NASA-GSFC ... A 2% sample of the population will describe 80% of the variability within the sample

The transect or ‘windshield survey’

• A regular sampling scheme

• A linear transect allows the geographer to extrapolate a limited set of field observations into a description of a fairly large area.

• A well done transect avoids observational bias. (primacy, recency, “oh wow!”)

• Linear transects are usually laid out along paths of easy transport… while this can limit their statistical viability and leads to a biased sample… the short answer is that they are cheap, easy to lay out and often one of the best tools available for initial reconnaissance of a field area

“across the grain”

• it is desirable to construct the transect across as many features / factors of the landscape as possible. In many places the gradient on the landscape will be elevation and or climatic.

• In Oregon, a north/south transect has little utility as the topography and climatic variability are greatest in the E-W direction

• In North Alabama, the grain appears to be related to the Tennessee River

Stratified Linear Random Sampling

• A ‘defensible’ method• Assumes that true random sampling will

be expensive• Assumes that populations should be

divided into sub-populations with lower variability (land use classes for example)

• Assumes transport corridors will provide a reasonable sub-set of the target population.

There is something fascinating about science. Onegets such wholesale returns of conjecture out ofsuch a trifling investment of fact.---- Mark Twain

• Observation

In the space of one hundred and seventy six years, the Lower Mississippi has shortened itself by two hundred and forty two miles.

That is an average of a trifle over one mile and a third every year.

• Therefore: any calm person, who is not blind or idiotic, can see that in the Old Oolitic Silurian Period, just a million years ago next November, the Lower Mississippi was upwards of one million three hundred thousand miles long, and stuck out over the Gulf of Mexico like a fishing rod.