www.gusucode.com > map 案例源码 matlab代码程序 > map/ComputeGradientDataFromRegularDataGridExample.m

    %% Compute Gradient, Slope, and Aspect from Regular Data Grid
% 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
% <docid:map_ref.f13-860392> 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.

% Copyright 2015 The MathWorks, Inc.

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')