This example shows how to compute the gradient, slope, and aspect for a regular data grid. The gradient components are the change in the grid variable per meter of distance in the north and east directions. Slope is defined as the change in elevation per unit distance along the path of steepest ascent or descent from a grid cell to one of its eight immediate neighbors, expressed as the arctangent. If the grid contains elevations in meters, the aspect and slope are the angles of the surface normal clockwise from north and up from the horizontal. The
gradientm function uses a finite-difference approach to compute gradients for either a regular or a georeferenced data grid. The function returns the components of the gradient in the north and east directions (i.e., north-to-south, east-to-west), as well as slope and aspect. The angles are in units of degrees by default.
Construct a 100-by-100 grid using the
peaks function and construct a referencing matrix for it.
datagrid = 500*peaks(100); gridrv = [1000 0 0];
Generate grids containing aspect, slope, gradients to north, and gradients to east.
[aspect,slope,gradN,gradE] = gradientm(datagrid,gridrv);
Map the surface data in a cylindrical equal area projection. Start with the original elevations.
axesm eqacyl meshm(datagrid,gridrv) colormap (jet(64)) colorbar('vert') title('Peaks: elevation') axis square
Clear the frame and display the slope grid.
clma meshm(slope,gridrv) colorbar('vert'); title('Peaks: slope')
Map the aspect grid.
clma meshm(aspect,gridrv) colorbar('vert'); title('Peaks: aspect')
Map the gradients to the north.
clma meshm(gradN,gridrv) colorbar('vert'); title('Peaks: North gradient')
Map the gradients to the east.
clma meshm(gradE,gridrv) colorbar('vert'); title('Peaks: East Gradient')