Z-Value
The value representing elevation or another attribute at a specific (x, y) location. Z-values are fundamental for 3D spatial analysis, terrain modelling, and representing surfaces such as elevation or depth.

What is Z-Value?
The vertical position or elevation of a point in a three-dimensional coordinate system is known as its Z-value in GIS. The Z-value provides a third dimension by identifying the site's height or depth, usually expressed in meters or feet, while the X and Y coordinates represent the horizontal location (east-west and north-south). In order to represent terrain surfaces, create 3D models, and analyse elevation-related elements like mountains, valleys, and building heights, Z-values are essential. They are commonly used in applications that need an understanding of elevation fluctuations, such as environmental modelling, infrastructure development, flood risk assessment, and topographic mapping. By using Z-values, GIS users can see and study the Earth's surface in a more realistic and detailed manner, going beyond flat maps.
Related Keywords
A Z-score measures how many standard deviations a data point is from the mean of a dataset. It is calculated using the formula:
Z = \frac{X - \mu}{\sigma}
where X is the data value, \mu is the mean, and \sigma is the standard deviation. Z-scores standardize data, making it easy to compare values from different datasets.
A statistical significance test establishes whether research findings are likely the result of chance or actually represent an effect. Statistical significance is indicated by a low p-value (e.g., <0.05).
With a mean of 0 and a standard deviation of 1, the standard normal distribution is a unique kind of normal distribution. It is used to compute probabilities and z-scores, which show how many standard deviations a number deviates from the mean. It is symmetric around the mean, creating the traditional bell-shaped curve.
A statistical technique for determining if sample data supports a particular assertion about a population is hypothesis testing. It determines if a null hypothesis (H₀) may be rejected by comparing it with an alternative (H₁) using a test statistic and p-value.
