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0

This is not exactly the answer to your question, but rather a suggestion. For RS, I would not use QGIS as a core software, because it is more oriented for GIS (even if it includes many tools). I suggest that you have a look at GRASS 7 (the new GUI is a true step forward). I don't have a look of experience because it is new, but I got some feedback and I've ...


1

In an email exchange with Radim Blazek in the grass-user mailing list he explained: QGis from OSGeo4Win is compiled with GRASS 6, you cannot get it working with GRASS 7. Reinstalling will not help. The provider and the plugin has first to be fixed to support build with both GRASS 6 and GRASS 7. This is in the first package of proposed upgrade: ...


1

From GRASS Raster Library, GRASS GIS 7 Programmer's Manual: Raster map data can be of type CELL, FCELL or DCELL, they are defined in "gis.h". CELL is a 32-bit signed integer, FCELL is an IEEE single-precision floating-point, and DCELL is an IEEE double-precision floating-point. 3D rasters (grid3d) is treated as DCELL (see related library).


2

The GRASS 7 meta-package made available last week had errors that cause this situation. The ubuntugis-unstable PPA maintainers have in consequence removed this meta-package. In a system where this rogue GRASS 7 meta-package was installed the fix is to remove all its packages and downgrade: sudo apt-get purge grass grass-core grass-doc grass-gui sudo ...


0

The original question could have been more complete, if the exact command instructed would have been posted. As well, the exact type of Landsat product, and the metadata file in question. Anyhow, from the screenshot, one can conclude that the original poster tried to work on Landsat7 bands. Taking into account the date when the question was posted, it is ...


1

When this question was submitted, there was no support for the recent sensor of the Landsat family. However, according to http://trac.osgeo.org/grass/changeset/61314, wihch is GRASS GIS' official project management system, the i.atcorr module in GRASS 7, supports for Landsat8 imagery since end of July 2014.


2

Majority Filter. You can apply multiple runs to smooth the image.


1

Note that GRASS GIS 7 comes with an updated vector format (esp. new spatial index). In order to use older vector data (from GRASS GIS 6) in GRASS GIS 7 the user has to rebuild the topology. Additionally it is recommended to switch the database backend from DBF files to SQLite. Both can be done in an automated way per MAPSET as described in this wiki page: ...


0

Large file support (not sure if it is already needed in your case being on Windows) has been added also for vector data to GRASS GIS 7.0. For details, see http://trac.osgeo.org/grass/wiki/Grass7/NewFeatures#Libvector


3

Jeffrey's answer works perfectly but the GRASS solution is also an option. I used r1, r2, r3 and r4 Jeffrey's raster for producing the 'mode' raster in QGIS-GRASS. The GRASS command was: r.mapcalc mode="mode(r1,r2,r3,r4)" At the Image below, I chose an arbitrary point to illustrate, with Value Tool Plugin, that the pixel value in the resultant map is the ...


1

On QGis 2.8 this problem is caused by a known, but yet unreported bug (access to the QGis bug tracker seems restricted). Before it is fixed it is not possible to create new mapsets in QGis. However, the user can create a new mapset directly with GRASS and then open it with the GRASS plug-in in QGis.


4

I am assuming that by mode you mean the most frequent class? You can use the R function "table" to calculate the frequencies of a vector. x <- c(1,1,2,3,4,4,4,4) table(x) Then use which.max to return the class associated with the most frequent class. To return the actual class name you need to wrap the statement in names. which.max( table(x) ) names( ...


1

You might take a look at the GRASS model r.param.scale. This module is designed to create a categorical raster of geo-morphology. You choose the threshold slope and it creates all "flat" areas with value 0. Then you could easily concoct an r.mapcalc expression to extract areas where the aspect is south and the terrain (output of r.param.scale) = '0'


-1

Free matrix heat-map software, for personal use and experimentation is here.


0

What are you trying to do exactly an what is your operating system (Windows, Linux, Mac OS X) ? 1) If you want to use the Grass shell (grass70), you don't need to create a conda environment if grass70 is in your path. 2) If you want to use the Python modules grass.script or grass.pygrass in Anaconda/Python, you have two solutions: call Anaconda from ...


1

You need to install the required frameworks first. The Numpy framework you can download where you (likely) also downloaded GRASS GIS 7.0.0 for Mac OSX, see: http://grassmac.wikidot.com/frameworks


0

Thanks! Solved it: I added a if-crierion. If below 0, then 1, else 0. In each step I have Octave (runs in the background via executable) calculate the sum of the raster values. Shell/GRASS reads the value: while [ $X -lt 1 ] do [...] as soon as sum >=1, the loop stops.


0

Don't know which shell language you are using but basically I'd use r.info -r inside an if block to get the value range for the raster. If you find that your raster has values 0 or less, you the use break or continue depending on your need, to exit the loop and carry on. Break and Continue manual page of bash. ...


0

I have changed the windows user account control setting to the lowest level and it solves the problem on my Win7 machine. Thanks for leading me in that direction @NeilBenny Unfortunately the same trick did not resolve the problem on my Win8 machine.


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For the record: The reporter opened a ticket http://trac.osgeo.org/grass/ticket/2610 - the answer is that the problem has already been solved in GRASS GIS 6.4.svn. It will be published with the upcoming 6.4.5 release or a nightly/weekly snapshot is used.


1

If your original pointcloud data is an ascii x,y,z formatted text file, then GRASS has the module r.in.xyz for this kind of data. The steps are simple: First run the module with the -s flag, which scans all the input data and give you the full extents of the data (min,max X and min,max Y). Now set the region using g.region with the extents from above. You ...


0

Sometimes, the statistics are calculated through sampling. This could cause the differences. Try to use gdalinfo with the -stat option to calculate image statistics and see if there are differences


1

Well this is confusing. Try to use short names because sometimes long names might cause you problems. eg. "dem_map-AlbSRTMdem" don't use "-" in names. Try "_" and make names shorter. Perhaps that is your problem (according to what I see).


2

You can use r.out.gdal. See the example on how to export group of image maps as multi-band file: g.list group i.group group=tm7 subgroup=tm7 input=tm7_10,tm7_20,tm7_30,tm7_40,tm7_50,tm7_60,tm7_70 i.group -l tm7 g.region rast=tm7_10 -p r.out.gdal tm7 output=lsat_multiband.tif gdalinfo lsat_multiband.tif


0

As commented by @gene: You need to fix the region on one of the RGB files, before applying r.composite. If not -> blank file. It looks like this worked for you because you commented: I set the region again after importing the individual bands to the defined bounds for all coverage. And now I succeeded in running r.composite and ...


1

Here is an approach in R. It is computationally expensive and very slow when applied to large rasters. Because of this, I added a point sub-sampling approach that seems tractable. I should note that, because the raster needs to be coerced into a vector, this function is not memory safe. This function returns the percent volume data and not a contour, but ...


7

In spatial hydrology, DEM-based flow accumulation operations are typically static. That is, they represent a steady-state condition of the discharge of surface and near surface water passing through a point. Flow accumulation grids are actually accumulating contributing area downslope, i.e. areas not volumes. The accumulated cells that you described is ...


0

Thanks to some discussion in the comments I was able to get solve this problem. I had previously installed Python 3.4 Using Anaconda. During the anaconda installation process it asked to add export PATH=$HOME/anaconda/bin:$PATH to .bashrc. By removing this line in the .bashrc file I can get Grass 7 to start up. EDIT: Although I get it to start it still ...


0

Using r.watershed -s with cells of interest provided as flow on a distance to network raster map (from r.grow.distance), i obtained the accumulation map answering our issues.


0

I downloaded OSM vector data from Geofabrik website. For the time being, i downloaded OSM vector data. I filled usefull field (speed_profile) for driving isochrones. On my windows 7 32 bits, Grass 7.0 and postgres/postgis have been installed. I loaded my OSM roads network into my Grass db. And i made a test with v.isochrones plugin. up to now, i did not load ...


0

What about using r.watershed with the flow input parameter? r.watershed elevation="elevation" flow="runoff" accumulation="flow_accumulation" ... For the flow input you need to provide a raster map representing amount of overland flow per cell. For a simplified approach assuming no groundwater flow etc. you can use your generated runoff map ...


0

The module to calculate insolation estimates is r.sun. There is a related Wiki page available at: http://grasswiki.osgeo.org/wiki/R.sun In order to simplify accumulated calculations, see these two addons: r.sun.daily: Runs r.sun for multiple days in loop (mode 2) r.sun.hourly: Runs r.sun in loop for given time range (mode 1) Be sure to include the cast ...



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