Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Lecture

Sampling: Continuous Spatial Phenomena

Description

This lecture introduces different spatial sampling procedures, including random, systematic, transect, and uniform-grid based sampling. It covers the properties of sampling surfaces, survey theory, domain definition, and sample quality assessment in Geographic Information Systems.

In MOOC

Geographical Information Systems 2

Official source

Quiz

Related concepts (32)

Sampling (statistics)

In statistics, quality assurance, and survey methodology, sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within a statistical population to estimate characteristics of the whole population. Statisticians attempt to collect samples that are representative of the population. Sampling has lower costs and faster data collection compared to recording data from the entire population, and thus, it can provide insights in cases where it is infeasible to measure an entire population.

Survey sampling

In statistics, survey sampling describes the process of selecting a sample of elements from a target population to conduct a survey. The term "survey" may refer to many different types or techniques of observation. In survey sampling it most often involves a questionnaire used to measure the characteristics and/or attitudes of people. Different ways of contacting members of a sample once they have been selected is the subject of survey data collection.

Stratified sampling

In statistics, stratified sampling is a method of sampling from a population which can be partitioned into subpopulations. In statistical surveys, when subpopulations within an overall population vary, it could be advantageous to sample each subpopulation (stratum) independently. Stratification is the process of dividing members of the population into homogeneous subgroups before sampling. The strata should define a partition of the population.

Cluster sampling

In statistics, cluster sampling is a sampling plan used when mutually homogeneous yet internally heterogeneous groupings are evident in a statistical population. It is often used in marketing research. In this sampling plan, the total population is divided into these groups (known as clusters) and a simple random sample of the groups is selected. The elements in each cluster are then sampled. If all elements in each sampled cluster are sampled, then this is referred to as a "one-stage" cluster sampling plan.

Nonprobability sampling

Sampling is the use of a subset of the population to represent the whole population or to inform about (social) processes that are meaningful beyond the particular cases, individuals or sites studied. Probability sampling, or random sampling, is a sampling technique in which the probability of getting any particular sample may be calculated. In cases where external validity is not of critical importance to the study's goals or purpose, researchers might prefer to use nonprobability sampling.

Related lectures (33)

Spatial Sampling: Concepts and Techniques

Covers spatial sampling in GIS, including autocorrelation, elevation models, and interpolation methods.

Altitude Models: Derivative Variables

Covers global relief indicators, altitude models, slope, orientation, curvature, and morphological indices for terrain description.

Spatial Continuous Phenomena, Sampling MOOC: Geographical Information Systems 2

Explores sampling procedures for analyzing continuous geographical phenomena and their importance in reducing prediction uncertainty.

Altitude Models and Derivative Variables MOOC: Geographical Information Systems 2

Covers geographic information systems, relief indicators, and digital elevation models.

Vector-Vector Interactions