MATLAB Plots *.tif According to Light

Hi @ Barbaros Teoman Kosoglu,

Please let me address your query regarding, “I am trying to plot a lunar terrain from a *.stl file. You can see the real image and plot in photos. MATLAB is plotting the deepest place as dark blue, the highest as yellow, but the thing is MATLAB's dark blue is not actually the deepest place, it is just shadow, likewise MATLAB's yellow actually isn't the highest place, it just takes the most light so its brighter. This is my code snippet to plot it. My real aim is to create a simulation, therefore I need the surface model. [dem, ~] = readgeoraster('moon1m-a.tif'); gridSize = 3900; start = 1; [X, Y] = meshgrid(1:gridSize, 1:gridSize); Z = dem(start:start+gridSize-1, start+gridSize-1:-1:start); figure mesh(X, Y, Z); Images are aligned, you can see the shadow places at the bottom right. I can't put the file into the attachments, it is too big even after compressing. I can put the *.tif into a 3D drawing tool, this is the output.Any help would be appreciated.”

Please see my response to your comments below.

First, I saved your output image “*.tif into a 3D drawing tool, this is the output.” as shown in your comments to JPG image and converted to TIF format in matlab.

% Load the JPG image
img = imread('/MATLAB Drive/IMG_7597.PNG');

% Write the image to a TIF file
imwrite(img, '/MATLAB Drive/IMG_7597.tif');

Please see attached IMG_7597.tif

Then, to visualize a Digital Elevation Model (DEM), I loaded the DEM data from a TIFF file (Reference: '/MATLAB Drive/IMG_7597.tif') using the readgeoraster function. It then checks the dimensions of the loaded DEM array against a predefined grid size of 3900. If the DEM is smaller than this grid size, it adjusts the grid size to match the smaller dimension of the DEM. Next, it initializes a meshgrid for the specified grid size and extracts the elevation data (Z) from the DEM, flipping it for correct orientation. Afterwards, a figure is created to plot the mesh, with shading applied to interpolate colors between points, enhancing the visual representation of the terrain. The view is set to 3D, and a colormap (jet or parula) is applied to reflect elevation data effectively. A colorbar is added for interpretation, and axes are labeled for clarity. Finally, the plot is titled "Lunar Terrain Elevation Model," providing context for the visualization.

% Load the DEM data
[dem, ~] = readgeoraster('/MATLAB Drive/IMG_7597.tif');

For more information on readgeoraster, please refer to

https://www.mathworks.com/help/map/ref/readgeoraster.html

    % Define grid size
    gridSize = 3900;

    % Check the size of the dem array
    [rows, cols] = size(dem);
    if rows < gridSize || cols < gridSize
      warning('The dem array is smaller than the required grid size. Adjusting 
      grid size to match DEM dimensions.');
      gridSize = min(rows, cols); % Adjust grid size to the smaller dimension
    end

    % Initialize meshgrid for the specified grid size
    start = 1;
    [X, Y] = meshgrid(1:gridSize, 1:gridSize);

    % Extract and flip Z data for correct orientation
    Z = dem(start:start+gridSize-1, start+gridSize-1:-1:start);

    % Create figure for plotting
    figure;

    % Plot the mesh with appropriate shading and colormap
    mesh(X, Y, Z);

    % Set shading to interpolate colors between points
    shading interp;

For more information on shading, please refer to

https://www.mathworks.com/help/matlab/ref/shading.html?searchHighlight=shading%20interp&s_tid=srchtitle_support_results_1_shading%20interp

    % Adjust view angle for better visualization
    view(3); % Set view to 3D

    % Set colormap to better reflect elevation data
    colormap(jet); % or use parula for a different gradient

    % Add colorbar to interpret values
    colorbar;

    % Label axes for clarity
    xlabel('X Coordinate');
    ylabel('Y Coordinate');
    zlabel('Elevation (Z)');

    % Set title for context
    title('Lunar Terrain Elevation Model');

Please see attached.

Since you mentioned issues with file sizes, consider compressing your .tif files or breaking them into smaller sections if necessary. This can facilitate easier handling in MATLAB. In case, if you want to explore more advanced visualization techniques (like contour plots or 3D surface plots), MATLAB offers functions like surf or contour3, which might also help in conveying depth and features more effectively. Hopefully, by implementing these changes, you should achieve a more accurate representation of the lunar terrain based on your elevation data while mitigating issues related to shadowing and light intensity. Please let me know if you have any further questions.