We live in a very complex world! In order to understand, manage and analyze our world, we try to simplify it using only the data and information required. For example, we may want to examine roads and traffic flows for transportation analysis, or examine remnant vegetation and national reserve areas in land use planning. Given the enormous range of objects and factors on the earth to be examined, this task can be quite often overwhelming.

When examining and exploring aspects of our earth, we will tend to focus on one or more groups of objects or features (ie.a population) such as roads, remnant vegetation, people and minerals.

Gathering data and information about our earth means obtaining data for a population. It is often not possible or feasible to gather data about every object in the population, hence we must narrow our data collection to a subset of the population. This process is referred to as data sampling.

A sample is a subset of entities or observations in a target population. It is intended to be representative of that population. The relationship between the samples and their parent populations underpins the theory and practice of inferential statistics. When a statistic is calculated and obtained for that sample, it is an estimate of the population. Sampling that is based on spatial properties (ie. geographic location) is referred to as spatial sampling.

What is sampling - Outline

1.1 Examples of sampling
1.2 Study area examples (for virtual field work)
1.3 Canning River 3D

Virtual sampling

You will be exposed to various spatial sampling methods and applications as you progress through this virtual field work web site.

This first module will introduce you to the data sampling concepts, its applications, and the specific study region for which you will be performing virtual sampling. Enjoy!!