Surfacebased

Surfacebased, or surface-based, is an adjective used across disciplines to describe methods, analyses, or representations that operate on a surface rather than a volume. It emphasizes a two-dimensional manifold embedded in three-dimensional space and is often chosen when the geometry of a boundary, interface, or skin carries the essential information. This term is typically contrasted with volume-based, voxel-based, or grid-based approaches.

In neuroimaging and neuroscience, surface-based analysis maps data onto the cortical surface reconstructed from MRI data. This approach preserves the topology of the cortex, enables alignment across individuals by folding patterns, and supports surface-based smoothing and vertex-wise statistics. It is commonly associated with tools like FreeSurfer and CIVET, and is used to study cortical thickness, functional activity, and other measures in a manner that respects cortical geometry.

In computer graphics and geometric modeling, surface-based representations model object geometry with surfaces such as polygonal meshes or NURBS. Rendering, shading, texturing, and collision detection are often performed on surfaces, while volume-based representations (like voxel grids) serve different purposes, such as volumetric rendering or subsurface phenomena.

In geoscience and environmental science, surface-based terminology refers to observations and models defined at or near the Earth's surface. Examples include surface temperature, wind at 2 meters, and land-surface energy balance models. Such approaches focus on processes and measurements confined to the boundary layer or near-surface interface.

Overall, surfacebased methods leverage the geometry and topology of surfaces to capture relevant phenomena more accurately when the boundary plays a central role.