New answers tagged gdal
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HOW to perform same thing in JAVA????
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Well whuber already gave you the short answer in his comment to your question, but I will elaborate a bit. Remember that latitude and longitude are angular measurements meant for graduating points on the earths ellipsoidal surface. A map projection takes these angular measurements(latitude and longitude) and transforms them into a 2D Cartesian coordinate ...
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gdal CPLString is a convenient class for std::string
class CPL_DLL CPLString : public gdal_std_string
{
...
};
and gdal_std_string is a typedef for std::string or MSVC string class
00213 # define gdal_std_string string
00214 #else
00215 # define gdal_std_string std::string
00216 #endif
Source:GDAL API docs
so basically CPLString can be checked for ...
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Here is how I got this working on my machine :
Hope that helps!
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"DLL load failed: The specified module could not be found."
it simply means that GDAL is improperly installed (line 17: missing dll file or rather, that the dll file is not installed at the requested location)
Look also at Importing GDAL from ArcGIS python window - is it possible? and Running GDAL and arcpy together (ArcGIS 10.1, GDAL 1.9.2, python 2.7.4)
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GDAL doesn't have a ready-made utility for this that I know of. You would probably have to script something.
However, for filling sinks, GRASS has the r.fill.dir and r.terraflow functions. SAGA and some other FOSS raster GIS packages also have sink filling functions too.
Spikes pose a different problem and you'll need to consider a median filter and/or ...
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Have a look here: http://trac.osgeo.org/gdal/wiki/DownloadingGdalBinaries. This gives you links to GDAL binaries for all sorts of operating systems and the first item is for ELGIS, supposedly including RHEL. Also see here.
I mostly use Windows and get my binaries from the excellent gisinternals link further down the page, so I can't vouch for the ...
2
You might try looking at OpenCV library. It is better suited for such tasks.
http://docs.opencv.org/doc/tutorials/imgproc/imgtrans/hough_circle/hough_circle.html
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Did you check that the "black" pixels are really black? They might have a low value and appear black on the screen, thus your conversion will not consider them black.
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See the OGR Projections tutorial and the OGRSpatialReference class. In particular, the GetAttrValue method.
Here's a worked example.
from osgeo import gdal,osr
ds=gdal.Open(r'SOMERASTER.TIF')
prj=ds.GetProjection()
print prj
srs=osr.SpatialReference(wkt=prj)
if srs.IsProjected:
print srs.GetAttrValue('projcs')
print srs.GetAttrValue('geogcs')
For my ...
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The problem was that I didn't use quotation marks when specifying output format: "ESRI Shapefile"
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I do not know of any automatic projection algorithm or software that could master so many challanges and unknown parameters in one picture (extremely high panorama-induced distortion in the NW direction, unknown look angle and flight height of the sensor, unequal pixel size, interrupting elements in the picture and many, many others). The only thing you ...
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Investigating this a bit further left me thinking it could be numerical errors. Using the zero-buffer trick worked, but ofcourse slowed my process down considerably.
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Have you tried the MicroDEM? It's free, and I have heard it works great at this, but have not used it myself.
http://www.usna.edu/Users/oceano/pguth/website/microdem/microdem.htm
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If the problem lies in the project file, you can edit that with any text editor, and delete manually the call of the CSV file.
At the moment, there is a lot of changing going on in QGIS and GDAL development. Assuming you are on Windows, I would advice to use the standalone QGIS Lisboa installer, not OSGeo4W. The standalone comes with GDAL 1.9.2, and is ...
2
I finally managed to make it work...Hope this is useful for others, too.
I re-installed the GDAL 1.9 bindings using the proper installer in this page http://www.gisinternals.com/sdk/PackageList.aspx?file=release-1600-gdal-1-9-mapserver-6-2.zip which lists the GDAL core binaries and bindings components that are compiled daily using the Microsoft Visual ...
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You mean something like Grass' r.cross?
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You could try only doing the Within() test against points that are within the polygon features envelopes, i.e.
def PointsInPolygons(pointsLayer, polysLayer):
nbInside = 0
polyFeat=polysLayer.GetNextFeature()
while polyFeat:
polyGeo = polyFeat.GetGeometryRef()
pointsLayer.SetSpatialFilter(polyGeo) #<----Only test points within ...
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You could add a field to your polygons and fill with some random but traceable value. Then do a Spatial join with the points, and all the points residing within a specific polygon will get the corresponding value.
Not sure if this will be any faster, but at least it's an alternative approach.
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What you need is a Point-In-Polygon test, which is a standard algorithm and has been covered extensively in other sources.
See here
or here
or even this post here on GIS-SE
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gdaladdo builds overviews internally by default. That is why you have seen the increased file size. You can build external overview by specifying:
gdaladdo -ro ...
This will build external overviews:
http://gdal.org/gdaladdo.html
As far as benefits, it depends on the application. If the application uses gdal, then it is built in (for some drivers) to ...
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This trick from another user on Stackoverflow solved the problem:
from scipy import ndimage
outVariance = ndimage.generic_filter(data, np.var, size=3)
See here for a detailed description of the answer:
http://stackoverflow.com/questions/16107671/variance-image-in-python-using-gdal-and-a-running-window-approach
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I think you almost have it. Be sure to add single quotes around the entire input name with double quotes around the hdf file name.
gdal_translate -of GTiff 'HDF4_EOS:EOS_GRID:"MOD13C2.A2001001.005.2007078152825.hdf":MOD_Grid_monthly_CMG_VI:CMG 0.05 Deg Monthly NDVI'
Hope that helps
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