Convert Matrix to ArcGIS raster

조회 수: 46 (최근 30일)
Diego Fonseca
Diego Fonseca 2020년 5월 31일
답변: Robert Daly 2022년 11월 30일
Hello Everybody,
I am working in a project, where a team is generating simulations with a model and exporting results in .mat files (x, y, z). I need to plot the results with ArcGIS (only ploting without doing further interpolations or operations, just setting colors and legend).
The problem is I need to generate a raster in matlab so ArcGIS can read it. If I only import x,y,z points into ArcGIS I will need to create a shapefile with them and interpolate it to generate a raster, which is not the best option, as it can differ from Matlab results (interpolation method etc).
So, anyone could help me converting a mx3 matlab variable (containing x, y coordinates in WGS84) and a variable z into a raster so I can read it directly into ArcGIS as a raster file?
Thanks in advance.
Best regards,
Diego

채택된 답변

KSSV
KSSV 2020년 5월 31일
It depends whether your data is structured or unstructured. Based on the data, the folloiwng is the procedure. Let A be your (x,y,z) data.
x = A(:,1) ; y = A(:,2) ; z = A(:,3) ;
%%structured
xi = unique(x) ; yi = unique(y) ;
[X,Y] = meshgrid(xi,yi) ;
Z = reshape(z,size(X)) ;
figure
surf(X,Y,Z)
%%unstructured
Z = griddata(x,y,z,X,Y) ;
  댓글 수: 7
KSSV
KSSV 2020년 6월 8일
편집: KSSV 2020년 6월 8일
WGS84 means UTM coordinates?
Just use
ncwrite(file,'z',Z) ; % write 2D data
Diego Fonseca
Diego Fonseca 2020년 6월 8일
No, UTM is the projection, WGS 84 is the datum for geographic coordinates. However, this is not a major issue, as I can project the netcdf in arcgis (it was just to speed up the process).

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Robert Daly
Robert Daly 2022년 11월 30일
Following on from KSSV in the comments...
You can export the data to a netCDF file then import that in ArcGIS.
To define the coordinate system for ArcGIS you need to add a bunch of attributes to the variables.
To work out the important attributes I exported a source raster to netCDF using "Multidimension tools>Raster to NetCDF"
Then in matlab use
ncdisp('export.nc')
to read the attributes.
The "esri_pe_string" attribute value is important according to this article Stackexchange
I got the string from the exported example.
% nc filename to be written
file = 'test.nc' ;
% create test dataset
Z=rand(10,10);
x = [2.2493e+05:2.2493e+05+10]
y = [6.1817e+06:6.1817e+06+10]
[x,y]=meshgrid(x,y)
% Write X and Y variables
% Get data
X = x(1,:) ;
Y = y(:,1) ;
%% Define data dimensions and write data
nccreate(file,'x','Dimensions',{'x',1,length(X)},'DeflateLevel',5) ;
ncwrite(file,'x',X) ;
nccreate(file,'y','Dimensions',{'y',1,length(Y)},'DeflateLevel',5) ;
ncwrite(file,'y',Y) ;
nccreate(file,'z','Dimensions',{'x','y'},'DeflateLevel',5) ;
ncwrite(file,'z',Z',[1,1]) ; % write 2D data
nccreate(file,'transverse_mercator','Dimensions',{'transverse_mercator',1,Inf},'DeflateLevel',5) ;
% Add projection attributes for ArcGIS
ncid = netcdf.open(file,'WRITE')
netcdf.reDef(ncid);
netcdf.putAtt(ncid,0,'units','Meter')
netcdf.putAtt(ncid,0,'long_name', 'Easting')
netcdf.putAtt(ncid,0,'standard_name','projection_x_coordinate')
netcdf.putAtt(ncid,0,'axis','X')
netcdf.putAtt(ncid,1,'units','Meter')
netcdf.putAtt(ncid,1,'long_name', 'Northing')
netcdf.putAtt(ncid,1,'standard_name','projection_y_coordinate')
netcdf.putAtt(ncid,1,'axis','Y')
netcdf.putAtt(ncid,2,'long_name','Habitat Suitability Index')
netcdf.putAtt(ncid,2,'standard_name','HSI')
netcdf.putAtt(ncid,2,'esri_pe_string','PROJCS["GDA2020_MGA_Zone_54",GEOGCS["GDA2020",DATUM["GDA2020",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",10000000.0],PARAMETER["Central_Meridian",141.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]]')
netcdf.putAtt(ncid,2,'coordinates','x y')
netcdf.putAtt(ncid,2,'grid_mapping','transverse_mercator')
netcdf.putAtt(ncid,3,'grid_mapping_name','transverse_mercator')
netcdf.putAtt(ncid,3,'longitude_of_central_meridian',141)
netcdf.putAtt(ncid,3,'latitude_of_projection_origin',0)
netcdf.putAtt(ncid,3,'scale_factor_at_central_meridian',0.9996)
netcdf.putAtt(ncid,3,'false_easting',500000)
netcdf.putAtt(ncid,3,'false_northing',10000000)
netcdf.close(ncid)

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