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1

I would use SAGA or python. SAGA: -import raster to grid -reclassify all points greater than your min-depth to NODATA -reclassify all points less than max-depth to NODATA at this point you can visualize your band of habitat. then you can do several different things but I would: -create constant grid with value min-depth (not, max-depth is the deeper ...


1

There's another GRASS module that you might find applicable to your case: v.rast.stats. This module creates a table of univariate statistics for each polygon in a vector layer, from the values in a raster. You will get: sum=the total of all cell values with each polygon, which is your habitat volume. And for free you also will have max, min, mean, std, etc. ...


1

Since GRASS GIS 6.4.3 should ideally start, maybe there is junk in the session configuration file (%APPDATA%\GRASS6\grassrc6 for GRASS 6 or %APPDATA%\GRASS7\rc for GRASS 7) where %APPDATA% is usually C:\Users\\AppData. To test, rename it and a new one will be created next time you run GRASS GIS. Note that %APPDATA% is a hidden folder. (cited from ...


1

I don't have an elegant answer but have a couple ideas that may send you in the right direction. Skyline in conjunction with Skyline Graph could get you close (requires 3D Analyst extension). Skyline uses the same line of sight principle. Search radius can be set (max_horizon_radius) and azimuth values should work to enforce the 8-tuple, but the tricky part ...


1

The LOCATION_NAME variable is not set. To start a project with GRASS, you need to set a "fully qualified initial mapset directory" which is defined by a "GISDBASE/LOCATION_NAME/MAPSET" path. Have you tried to launch GRASS from the start menu instead of the cmd window? After this first launch, you will be asked to set the variables.


1

Consider to try GRASS GIS 7 for that which comes with a more efficient memory management for vector data. I have generalized the Austrian OpenStreetMap roads in one step, a reasonably big dataset, no problem on a normal desktop.


1

As Andre mentioned in GRASS your LOCATION coordinate system must match the coordinate system of the data being input. You can create a new LOCATION when you input the original tiff file by using the location= parameter. For example: r.in.gdal input=E:\cdnh43e_v1.1r1.tif output=cdnh43e_v1 location=LCC Now run: g.region raster=cdnh43e_v1 to set your ...


0

This is an older one, but since it does not have an accepted answer: GRASS GIS is divided into modules. Each module is a command line program which can by invoked in many ways. Inside GRASS itself, it is through the system command line or GUI (with our without auto-generated GUI dialog). Most of the GRASS functionality is exposed through modules. There is ...


4

I believe you can use some map algebra (raster > raster calculator) before you can preform your volume measurements in grass. Assuming that your bathymetric data use positive values to represent the sea depth, and using your example for the range as 50 the min_depth and 200 the max_depth. For each of the raster cells you need to "remove" anything below the ...


2

In GRASS, location and dataset should share the same projection. On-the-fly-reprojection is only available in advanced GIS packages like QGIS or Arcgis. To change the projection, use gdalwarp to a different filename outside of GRASS.


4

The ASTER L1B files contain several subdatasets with different resolutions. That's why you can not easily add them to QGIS. You have to run gdalinfo and gdalwarp on it to get a tif file that QGIS can import: gdalinfo AST_L1B.hdf >>info.txt gives you a long list of metadata. Look out for the subdatasets: Subdatasets: ...


0

The GRASS command v.out.ogr, which you would use to export a vector to a shape, takes a layer= parameter. This way you can export separate layers from a GRASS vector. The values would be 0,1 etc. But when you say "vector map has multiple layers" I assume you mean that the vector contains both points and lines. In this case use the type= parameter to get ...


0

One of GRASS's unique properties is that it allocates cache memory with the g_malloc() pointer prior to computing. Because of this memory allocation the function will run faster and it surely won't result in an "out of memory" error after half of the function has run. For this property of GRASS, you only have three options: Select a smaller region extent ...


0

The GRASS v.distance function does currently not work from QGIS Processing. See GRASS in QGIS not working (windows XP). You will have to run it through the GRASS plugin. Update: You could also try the NNJoin plugin. It provides an option to use the centroids of the geometries of polygon (or line) input layers. It may be slow for large datasets.


2

I'm not sure exactly what kind of TIF format a LISS3 image is, but I will assume that it is a geoTIFF as this is the case for most satellite data. Whitebox GAT can import uncompressed, single band GeoTIFF images simply by selecting them from the list of available files when you press 'Add Layer'. You can open multiple images at a time as well: Whitebox ...


1

You have about three options: (Best) In the GRASS plugin, open the GRASS shell - it's at the top of the Module tree. Type into the command line the r.in.gdal command, and include the location=... parameter. This will create a new LOCATION based on your custom CRS, and import the raster there. You'll then need r.proj to reproject your other layers into this ...


0

Depending on your needs, the resolution usually should be such that a few thousand cells in both the X direction and the Y direction are sufficient. If you have map layers of the whole world then a resolution of 5 kilometers would give you about 8000 X 8000 cells in your raster. That's "comfortable". But, again, you have to clearly define your needs, and ...


0

Here is a suggestion using GridTopology from R. library(sp) library(rgeos) # coordinates of some points x <- c(44, 66, 88, 22, 44, 66, 44, 66) y <- c(64, 64, 64, 48, 48, 48, 32, 32) sp <- SpatialPoints(cbind (x,y)) # dimensions of grid topleftCorner <- bbox(sp)[,1] columns <- length(unique(x)) rows <- length(unique(y)) cellWidth <- 22 ...


0

Back to this topic: you really wanted to apply "smoothing" here, see http://grass.osgeo.org/grass70/manuals/v.generalize.html#smoothing and not what you have tried (douglas). Use instead e.g. "chaiken": http://grass.osgeo.org/grass70/manuals/v.generalize.html#smoothing-example BTW: we added the possibility to generate an "error" map which contains those ...


3

I develop a free and open-source GIS called Whitebox Geospatial Analysis Tools (can be downloaded here) that has extensive analysis functionality for processing LiDAR data. Whitebox contains a tool specifically for calculating the point-density of LiDAR LAS files called Point Density LiDAR. The tool is highly specific to LiDAR, taking one or more LAS ...


1

You need to assign a grey color table (r.colors). To get an RGB composite run d.rgb (composite on the fly) or r.composite (saved as new map) or via graphical user interface (on the fly). And with i.landsat.rgb (called now i.colors.enhance in GRASS GIS 7) you can color-balance the natural colors.


0

You could generate a polygon grid layer using the MMGIS plugin in QGIS (install it from the the plugin manager within QGIS) MMGIS > Create > Create grid layer. You can specify a rectangular grid with whatever grid spacing and origin point you require. If you need to transfer attributes from the points to the grid use Vector > Data Management Tools ...


0

Would it be just as easy to: Create the grid layer with the dimensions that you want using the MMQGIS plugin and the Create | Create Grid option. Create the grid as a polygon. Select the grids that don't match your points and delete them. Use the Vector | Geometry Tools | Polygon Centroids tool to 'regain' the centroids I realise that my method ...


1

Here's one solution. The green, yellow, and red lines in the first picture above represent costs for travel to the firestations, stored in a column named cat. The green have cat = 1, yellow cat = 2, red cat = 3. So we know from this layer (output of v.net.iso) which street segments are within which costs. However, we also need to associate these segments ...


0

I would do it with Spatialite-gui. The steps are: Create an empty Spatialite DB with Spatialite-gui Import Excel file with "Import Excel" tool (Excel 2003 format or older) Create geometry column (POINT) with desired SRID Populate geometry column with dummy points "geomfromtext('POINT 1 1')" Open the Spatialite table with QGIS. Move dummy points to their ...


-1

Please see http://support.esri.com/en/knowledgebase/techarticles/detail/27589 Although I don't know ArcGIS at all well, I've done the exact same thing with other tools. However since you have the big guns, why not use them...


4

What I'd probably do in ArcMap: Create a new feature class and start adding new features. As you place each point on the map, and note in your Excel file what the OBJECTID for the point is. Then, once you are done creating points, Join the Excel file to the feature class and the property owners can be copied over to the feature class. Another way in ArcMap: ...


1

I am no expert in rasters (nor in QGIS for that matter) but have you tried manually setting the colours for the bands in QGIS? Layer Properties > Style > Select "Multiband color" and configure the settings to your requirements. Apologies for not providing a definitive answer.


2

Convert lines to raster (this step depends slightly on exactly what form the original data is in, but the assumption is that you will start with a raster representing streets with each pixel containing the cumulative distance to the nearest point) Reclass distance raster corresponding to the desired isoline values (GRASS r.reclass) Create a regular point ...


0

Welcome to the site Janos. Ideally answers such as yours should have a description as to why they are good methods. .. For pansharpening of Landsat 8 pictures the easier method the http://www.geosage.com/highview/download.html. My advise, try it. Only one click....


1

The answer will depend on the requirements of your specific workflow and application but I can offer you advise on how a drainage network is generally extracted from a digital elevation model (DEM). The key to extracting a drainage network from a DEM is creating a flow accumulation raster, i.e. a raster for which each grid cell contains a value that is ...


-1

For pansharpenig I used GUI spectral transformer for Landsat 8 pictures http://www.geosage.com/highview/download.html Very good. BR Janos


0

"CELL" type means integer type (see also http://grasswiki.osgeo.org/wiki/GRASS_raster_semantics#Raster_map_precision_types). Since SRTM is delivered as integer map but i.topo.corr expects a floating point map, you need to convert/resample that map beforehand. For resampling methods available in GRASS GIS, see the manual or Wiki, especially: ...


0

You can run GRASS GIS in a complete batch mode which includes the temporary creation of the workspace (just need to know the EPSG code of the actual projection or simply use the metadata provided by your SHAPE file, i.e. the .prj file). See for examples: http://grasswiki.osgeo.org/wiki/Working_with_GRASS_without_starting_it_explicitly See therein "Python: ...


1

You may want to look at mb-system, which is specically made for mapping sea floors (I have no experience, I just know it exists): http://live.osgeo.org/en/overview/mb-system_overview.html Anyway, you could consider converting you shoreline line to points before interpolating.


0

Toni (and knives): I would not recommend manually editing the cellhd files. That will surely lead to trouble down the line. When using GRASS (unlike some other, less strict GIS software) you must set the correct coordinate system and region before creating or importing any data. That's probably why knives had trouble displaying his rasters. If you have data ...


1

I think I found the answer here. You have to click View output which adds the GRASS layers to the QGIS map. Then the select boxes populate with the GRASS layers.


0

Answered here: http://lists.osgeo.org/pipermail/grass-dev/2014-September/070622.html http://lists.osgeo.org/pipermail/grass-dev/2014-September/070624.html Essentially, for GUI customization, see http://trac.osgeo.org/grass/wiki/wxGUIDevelopment/Toolboxes


1

You need to iterate through the files, so your loop should be as follows: for file in $NPPFILES do r.out.gdal input=$file output=$file.tif format=GTiff done You should add the semi-colons if you write the loop on one line.


0

I get the same type of result when there is no file produced at the end of a process. In some cases it is because there is no data because I have input the wrong layers or the layers in the wrong order. In other cases it is because I don't have read / write for all the necessary directories. My installation of QGIS 2.2 has different permissions to my ...


3

I just found the answer fo myself, reading the manual carefully and focused. The r.sun mode 2 computes just the clear-sky irridiation. To get the "real-sky" irridiation you have to multiply the result with a clearsky Factor (Kc). Kc is defined as the ratio of messured Irridation on Ground under overcast situation and the clearsky amount messured via ...


2

Why don't you crop again with your clipper after vectorizing? That way any combined polygons derived from your raster layer will match your original clipping layer. If you don't want to add an extra step you can vectorize the entire raster layer then clip to vector layer (though this could take more computation time). Any other option I can think of would ...



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