Ground Truth (data verification)

Ground truth, in data verification, refers to the accurate, real-world information used as a reference to validate or label data collected through sensors, images, or other methods. It serves as the benchmark to ensure that the data being processed or analyzed correctly reflects actual conditions. For example, physically checking a forest to confirm satellite images accurately identify tree types. Ground truth helps improve the accuracy of machine learning models and data analysis by providing a reliable standard against which digital data can be compared and corrected if necessary.