readgeoraster

Read a GeoTIFF image of Boston as an array and a map cells reference object. The array is of size 2881-by-4481-by-3 and specifies the red, green, and blue components of the image. Display the image using the mapshow function.

[A,R] = readgeoraster("boston.tif");
mapshow(A,R)

The data used in this example includes material copyrighted by GeoEye, all rights reserved.

Read and display a land cover classification of Oahu, Hawaii.

First, read the land cover data as an array, a map cells reference object, and a colormap. The elements of A index into the colormap. Each row of the colormap specifies the red, green, and blue components of a single color. Then, display the land cover data.

[A,R,cmap] = readgeoraster('oahu_landcover.img');
mapshow(A,cmap,R)

The data used in this example is courtesy of the National Oceanic and Atmospheric Administration (NOAA).

Read and display elevation data for an area around South Boulder Peak in Colorado.

Read the elevation data as an array and a geographic postings reference object. To display the data as a surface, the geoshow function requires data of type double or single. In this case, preserve precision by specifying the output type as "double".

[A,R] = readgeoraster("n39_w106_3arc_v2.dt1","OutputType","double");

Create a map by specifying the latitude and longitude limits of the data. Then, display the data as a surface using the geoshow function. Apply a colormap appropriate for elevation data using the demcmap function.

latlim = R.LatitudeLimits;
lonlim = R.LongitudeLimits;
usamap(latlim,lonlim)
geoshow(A,R,"DisplayType","surface")
demcmap(A)

The elevation data used in this example is courtesy of the US Geological Survey.

Raster data sets sometimes indicate missing data values using a large negative number. Import raster data, find the missing data indicator, and then replace missing data with NaN values.

Import raster data and a reference object using the readgeoraster function. Find the missing data indicator using the georasterinfo function.

[A,R] = readgeoraster('MtWashington-ft.grd');
info = georasterinfo('MtWashington-ft.grd');
m = info.MissingDataIndicator

m = 
-32766

Verify the raster data contains missing data using the ismember function. The ismember function returns logical 1 (true) if the raster contains the missing data indicator.

ismember(m,A)

ans = logical
   1

Replace the missing data with NaN values using the standardizeMissing function.

A = standardizeMissing(A,m);

Since R2023b

GRIB files often store data using multiple bands. If you do not know which bands to read, you can query the metadata stored in the GRIB file.

Read and display a band of data from a GRIB file. The file contains sea ice concentrations for multiple years [1][2], and each band of the file corresponds to a different year.

Get information about the GRIB file by creating a RasterInfo object. Get the metadata by accessing the Metadata property of the RasterInfo object.

info = georasterinfo("seaice.grib");
metadata = info.Metadata;

RasterInfo objects store GRIB metadata using a table, where each row of the table corresponds to a band of data in the file. Find the band that contains data for the year 2016.

yrs = year(metadata.ReferenceTime);
band = find(yrs == 2016);

Read data from the band by using the readgeoraster function. Replace missing data with NaN values by using the standardizeMissing function. Then, convert the concentrations to percentages.

[A,R] = readgeoraster("seaice.grib",Bands=band);

m = info.MissingDataIndicator;
A = standardizeMissing(A,m);

A = A * 100;

Display the data as a surface on an axesm-based map. Change the colormap and add a labeled color bar.

figure
worldmap(A,R)
mlabel off
plabel off
geoshow(A,R,DisplayType="surface")


colormap abyss
c = colorbar;
c.Label.String = "Sea ice concentration (%)";

[1] Hersbach, H., B. Bell, P. Berrisford, G. Biavati, A. Horányi, J. Muñoz Sabater, J. Nicolas, et al. "ERA5 Hourly Data on Single Levels from 1940 to Present." Copernicus Climate Change Service (C3S) Climate Data Store (CDS), 2023. Accessed May 22, 2023. https://doi.org/10.24381/cds.adbb2d47.

[2] Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.