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6

Your fire hydrants will have a very unique spectral signature, therefore I would use supervised maximum likelihood classification to classify your raster. An alternative is to run an ISODATA algorithm for an unsupervised approach. Try the following (partial) workflow: Open Iso Cluster Unsupervised Classification in ArcGIS Enter ALL 3 bands (i.e. R, G, B) ...


4

Vegetation extraction is a bit more complex than running the spatial analysis tools that you named. For better results I would suggest the following: run analysis on a 4 band image (e.g. R,G,B,NIR) change image to be symbolized as 432 for RGB not 321 create training samples that represent vegetation and run a supervised classification These steps will ...


3

Herein lies a misunderstanding: "...that is done separately for each band and not for a specific colour." "Each band" and "specific colour" are in fact the same thing. That is, it is the values in each band that, when combined together, make a specific colour. For example the RGB triplet 255,0,0 is the specific colour of pure red, comprised of band-red at ...


3

As a geologist, I make geological cross section using the elevations values from a DEM and the colors from a geological map, look at the pure Python solution with osgeo.gdal in Python Script for getting elevation difference between two points But now, since PyQGIS 2.x, it is easier with PyQGIS and the QgsRaster.IdentifyFormatValuefunction example with a ...


2

The feature you want is implemented as "Data defined properties". See Data-defined Styles in QGIS for a first announcement. It works for me this way: Load the data as delimited text, and save it as a shapefile with CRS EPSG:4326 WGS84 Right-click on the layer -> Properties -> Style Leave the topmost dropdown field at Single Symbol Click on Simple ...


2

Seems the bugs you mention with GRASS are a known issue with the standalone version. Nothing to do with mapcalc... this was a packaging issue that has been solved on osgeo4w and now is just needed to wait for updated standalone installers. Réf : https://hub.qgis.org/issues/8529


1

This does not probably work generally but it should give a correct result in your case. I captured your image above and saved it as "pngtest.png". I checked that it is a RGB png file with alpha channel. However, because it looks like a classified image I decided to try what happens if I convert it into a paletted tiff with GDAL tool rgb2pct.py ...


1

I would just add all of the rasters to a mosaic dataset (requires at least an ArcGIS Standard license), without any conversion. If you want to add info about the date, you can add a field to the attribute table of the mosaic's footprints (not even necessary if the name of the raster file is enough: it is added to the attribute table of the footprints when ...


1

ArcScan is meant to digitize drawings (typically scanned cadastral maps or the likes). In your case you want to classify an RGB image. With a true color image, you can use the image classification toolbar . You'll need to draw some sample polygons and use them for training a classifier. You need spatial analyst licence for that, and I would rather use an ...


1

I am guessing those mysterious spaces after G:\ are your attempt to make your file path anonymous? Your output file name is invalid. "cml.tif&_nred" is not a valid file geodatabase name. You cannot have symbols like "." or "&" in the raster name. A valid name would by something like "cml_tif_nred". Have a look at the model only Parse Path tool.


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If the output file format is not geotiff, rgb2pct.py creates an intermediate geotiff to write the results into before converting that to the final output format. The comments in the code state: # Create the working file. We have to use TIFF since there are few formats # that allow setting the color table after creation. From lines 127-129 of ...



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