Kriging is an interpolation method that makes predictions at unsampled locations using a linear combination of observations at nearby sampled locations. The influence of each observation on the kriging prediction is based on several factors: 1) its geographical proximity to the unsampled location, 2) the spatial arrangement of all observations (i.e., data configuration, such as clustering of observations in oversampled areas), and 3) the pattern of spatial correlation of the data. The development of kriging models is meaningful only when data are spatially correlated.. Kriging has several advantages over traditional interpolation techniques, such as inverse distance weighting or nearest neighbor: 1) it provides a measure of uncertainty attached to the results (i.e., kriging variance); 2) it accounts for direction-dependent relationships (i.e., spatial anisotropy); 3) weights are assigned to observations based on the spatial correlation of data instead of assumptions made by the analyst for IDW; 4) kriging predictions are not constrained to the range of observations used for interpolation, and 5) data measured over different spatial supports can be combined and change of support, such as downscaling or upscaling, can be conducted.
Researchers and practitioners apply the concepts and tools of GIScience to answer questions about geographic phenomena and to inform policy and management decisions across a wide range of social and environmental domains. Verification and validation of applied GIS research is essential to the development and application of credible geographic knowledge. Attempting to verify and validate the claims researchers and practitioners make when they analyze phenomena using the concepts and tools of GIScience is essential to the development of geographic knowledge. Verification is the act of testing whether the concepts and methods used to make a research claim were implemented in a way that is appropriate for the question being investigated. Validation is the act of assessing whether the concepts, measurements, or conclusions of a study are logically sound and factually well-founded. Researchers can pursue the verification and validation of past studies by attempting to reproduce or replicate these earlier findings. During a reproduction, an independent researcher attempts to recreate the results of an initial study using the data and procedures of that study. During a replication, an independent researcher empirically tests the validity of the claims made in a study by selectively altering different aspects of the initial work when repeating the study. This entry outlines these processes and how they are used to verify and validate applied GIS research.