Mean Composite of netcdf images

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Arnab Paul
Arnab Paul 2024-3-11
回答： Udit06 2024-3-18
I am stuck with a problem. I want to create a mean composite of multiple georeferenced .nc satelllite images. 1st problem is findling the study area. The images have my AOI in different position because of swath. Although I cropped the images based on desired lat and lon. Which cuased the 2nd problem. The cropped images have different dimensions. Someone suggested me to use meshgrid. Can someone give a clear vision how to create composite of multiple images
the code I have written so far is here.
fileDirectory = "input folder";
filename = dir(fullfile(fileDirectory, '*_reprojected_chl.nc'));
nFileDirectory = length(filename);
outputFolder = "output folder";
for i=1:nFileDirectory
nFileRrs = filename(i).name;
% Crop the data
min_lat = 26.5;
max_lat = 30.5;
min_lon = -95;
max_lon = -88.5;
data = ncread(fullfile(fileDirectory, nFileRrs), 'latitude'); % Replace with your actual variable name
latitude = double(data);
data = ncread(fullfile(fileDirectory, nFileRrs), 'longitude'); % Replace with your actual variable name
longitude = double(data);
data = ncread(fullfile(fileDirectory, nFileRrs), 'chl_image'); % Replace with your actual variable name
chl_image = double(data);
% Print lat/lon ranges
fprintf('File: %s, Latitude Range: %f to %f, Longitude Range: %f to %f\n', nFileRrs, min(latitude(:)), max(latitude(:)), min(longitude(:)), max(longitude(:)));
% Find row and column indices
[row_indices, col_indices] = find(latitude >= min_lat & latitude <= max_lat & ...
longitude >= min_lon & longitude <= max_lon);
clipped_chl_data = chl_image(min(row_indices):max(row_indices), min(col_indices):max(col_indices));
clipped_latitude = latitude(min(row_indices):max(row_indices), min(col_indices):max(col_indices));
clipped_longitude = longitude(min(row_indices):max(row_indices), min(col_indices):max(col_indices));
clipped_chl_data = clipped_chl_data';
clipped_latitude = clipped_latitude';
clipped_longitude = clipped_longitude';
% Get the dimensions of the clipped data
[r, c] = size(clipped_chl_data);
end

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回答（1 个）

Udit06
Udit06 2024-3-18
Hi Arnab,
Based on the code you have provided above, you've successfully looped through your .nc files, read the relevant data (latitude, longitude, and chl_image), and cropped the data to your Area of Interest (AOI). The next step would be to interpolate these cropped images to a common grid and then calculate the mean composite of these images.
You can follow the following steps for the same
1) Define a common grid
min_lat = 26.5;
max_lat = 30.5;
min_lon = -95;
max_lon = -88.5;
% Define the common grid's latitude and longitude boundaries and resolution
resolution_lat = 0.1; % adjust as per your requirement
resolution_lon = 0.1; % adjust as per your requirement
common_lat = min_lat:resolution_lat:max_lat;
common_lon = min_lon:resolution_lon:max_lon;
% Create the meshgrid for the common grid
[common_lon_grid, common_lat_grid] = meshgrid(common_lon, common_lat);
2) Interpolate each cropped image to the common grid
% Interpolate the current image to the common grid
interpolated_image = interp2(clipped_longitude, clipped_latitude, clipped_chl_data, common_lon_grid, common_lat_grid, 'linear'
You can refer to the following MathWorks documentation to understand more about meshgrid and interp2 functions.
https://www.mathworks.com/help/matlab/ref/meshgrid.html
https://www.mathworks.com/help/matlab/ref/interp2.html
I hope it helps.

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