which devotes higher resolution mesh at regions of interests increasing the simulation precision while keeping the memory footage at manageable size. In
biodiversity science, geodesic grids are a global extension of local discrete grids that are staked out in field studies to ensure appropriate statistical sampling and larger multi-use grids deployed at regional and national levels to develop an aggregated understanding of biodiversity. These grids translate environmental and ecological monitoring data from multiple spatial and temporal scales into assessments of current ecological condition and forecasts of risks to our natural resources. A geodesic grid allows local to global assimilation of ecologically significant information at its own level of granularity. When modeling the
weather, ocean circulation, or the
climate,
partial differential equations are used to describe the evolution of these systems over time. Because computer programs are used to build and work with these complex models, approximations need to be formulated into easily computable forms. Some of these
numerical analysis techniques (such as
finite differences) require the area of interest to be subdivided into a grid — in this case, over the
shape of the Earth. Geodesic grids can be used in
video game development to model fictional worlds instead of the Earth. They are a natural analog of the
hex map to a spherical surface.
Pros and cons Pros: • Largely
isotropic. • Resolution can be easily increased by binary division. • Does not suffer from over sampling near the poles like more traditional rectangular longitude–latitude square grids. • Does not result in dense linear systems like
spectral methods do (see also
Gaussian grid). • No single points of contact between neighboring grid cells.
Square grids and isometric grids suffer from the ambiguous problem of how to handle neighbors that only touch at a single point. • Cells can be both minimally distorted and near-equal-area. In contrast, square grids are not equal area, while equal-area rectangular grids vary in shape from equator to poles. Cons: • More complicated to implement than rectangular longitude–latitude grids in computers. == See also ==