This topic includes interpolation, regression, and surface analysis.
Many features occur across large areas while
measurements of the values can only be taken at fixed locations.
Continuous surfaces can be predicted using the sampled
measurements.
What types of value can I predict?
Surface analysis includes terrain analysis, surface modeling, surface interpolation, suitability modeling, hydrological analysis, and image classification. Using an elevation surface you can derive information and identify features that were not readily apparent in the original surface, such as contours, angle of slope, steepest downslope direction (aspect), shaded relief (hillshade), and visible areas (viewsheds). Use derived data together to help solve spatial problems.
Interpolation is used to predict values at unsampled sites from measurements made at point locations within the same area. Geostatistical methods can provide interpolated values and, additionally, measures of uncertainty for those locations. The measurement of uncertainty is critical to informed decision making, providing information on the possible outcomes (values) at each location.
This topic includes a number of case studies that, in part, use surface analysis or interpolation. These are exploratory analyses, designed to demonstrate an approach to a specific problem using ArcGIS. For each case study, additional resources have been made available including workflows that describe how the analysis was done in ArcGIS and a GPK (geoprocessing package) in which all resources (models, scripts, data, layers, and files) needed to perform the described analysis are included in the package.
What questions can I answer?
Predicting values from your data could help you answer these types of questions:
- What are the values between known samples?
- What is the effect of a physical barrier?
- Can a feature be seen from that location?
- In which watershed is this location?
- Could it be elsewhere?