Raster data, also known as data grids, stores map data as matrices. Regular data grids require a referencing object, vector, or matrix that describes the sampling and location of the data points. Geolocated data grids explicitly identify the latitude and longitude coordinates of all rows and columns.
|Reference raster cells to geographic coordinates|
|Reference raster postings to geographic coordinates|
|Referencing matrix to geographic raster reference object|
|Referencing vector to geographic raster reference object|
|Convert geolocated data array to regular data grid|
|Resize geographic raster|
|Crop geographic raster|
|Geographic raster interpolation|
|Generate synthetic data set on sphere|
|Encode data points into regular data grid|
|Filter latitudes and longitudes based on underlying data grid|
|Latitudes and longitudes of nonzero data grid elements|
|Substitute values in data array|
|Fill in regular data grid from seed values and locations|
|Reference raster cells to map coordinates|
|Reference raster postings to map coordinates|
|Referencing matrix to map raster reference object|
Raster geodata represents map data in matrix format.
Each element of georeferenced raster data corresponds to a defined quadrangle of territory on a planet.
You can display regular and geolocated data grids in many ways, such as a 2-D indexed image where color represents the data value, or as a 3-D surface with light shading.
When you cannot import spatial referencing information using the
readgeoraster function, you can manually reference the
To analyze data spread across several raster tiles, first combine the tiles into a single raster.
This example shows how to store a matrix in a geographic referencing object. Display the matrix on a map, and specify display properties such as the projection, axes labels, and color map.
A geolocated data grid is defined by three matrices giving latitude and longitude coordinates and indices associated with the mapped region.
The dimensions of a map matrix and associated latitude and longitude matrices determines the interpretation of the geographic map data.
You can perform logic tests on data grid variables to create a binary logical grid.