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11

Have you looked at using FWTools? There is a python script called gdal_merge that is available within FWTools. You can use a list as input. The command with usage would be: gdal_merge -o c:\temp\output_image.tif -q -v --optfile c:\temp\rasterlist.txt


10

You can get Sentinel-1 data from scihub.esa. Requires only registration (And most likely, non-commercial use). As Sentinel-1 has just become operational the archive is not very extensive but should grow quite quickly. You can set request data-access propospal on Alaska Satellite Facility. Some data open access. For ALOS-PALSAR you must be a resident of the ...


8

GDAL supports .img format, both the basic Imagine and the extended Imagine (greater than 2GB), thus any software that utilizes GDAL drivers would support ERDAS Imagine. The most workable and well documented that I have seen is QGIS. It is also open source and therefore free.


6

If you're using Python I'd recommend using the GDAL library, which has it's own Python bindings. Assuming you've got both GDAl (see this GIS StackExchange question for details on how to install on windows) and numpy installed, your code could look something like: from osgeo import gdal import numpy as np #Open our original data as read only dataset = ...


6

Panchromatic images are created when the imaging sensor is sensitive to a wide range of wavelengths of light, typically spanning a large part of the visible part of the spectrum. Here is the thing, all imaging sensors need a certain minimum amount of light energy before they can detect a difference in brightness. If the sensor is only sensitive (or is only ...


5

Under'Options', choose the 'CRS' tab, and see the choices for new layers. Choose either "Use project CRS", or 'Use default CRS displayed below'.


5

Posterizing was a great start: it eliminated most of the compression artifacts and simplified the cartography enough to enable additional cleaning. Much of the cleaning of a categorical raster involves so-called "morphological" operations. These include expanding one category into its neighbors, shrinking it back again, and region grouping contiguous ...


5

If you want to show your geometries as vectors instead of images there are a couple of tricks that you can apply to reduce the load of your page: Use TopoJSON instead of GeoJSON Remove all the attributes that you are not going to use in the applicaation and also the whitspaces. Taking into account your visualization scale, simplify your geometries and ...


5

you can either check "update georeferencing" or create a new rectified image using "rectify". These tools are in the drop down menu of th georeferencing toolbar.


5

Only managed to find a couple of sources for SAR images and data: You can download SAR images from here which are mostly focused on ecological sites such as forests: You can download SAR samples from here which contain fairly large datasets (note: the last 4 links at the bottom of the SAR section are dead) Hope this helps.


5

Yes, there is a way to do that. In the symbology palette for the overlay raster, you can select the Display Background Value (R, G, B) _ _ _ as ___ option (see screenshot for a raster I have doing the same thing with a white background. Assuming your background image is truly all white, your values will also be 255, 255, 255 in the boxes. Make sure to select ...


5

I hacked together a solution for this and wrote a blog article a while back on a very similar topic, which I will summarize here. The script is intended to extract a river from a 4-band NAIP image using an image segmentation and classification approach. Convert image to a numpy array Perform a quick shift segmentation (Image 2) Convert segments to raster ...


4

Though I am not able to understand the difference between the standard deviation output and the percentage output and what is the significance of using one over the other? Those refer to the threshold used to decide whether there has been any change between two images. For percentage change, it uses a symmetric relative difference formula to ...


4

From the USGS FAQ: the blue band is useful for "Bathymetric mapping, distinguishing soil from vegetation and deciduous from coniferous vegetation". It's my experience that you get better results by using band combination, however.


4

GIS file formats contain georeferencing information. This ties image pixel coordinates to grid references in a projection system, in this case British National Grid. There are lots of ways this information can be stored depending on image format. A basic tool to get you started is gdalinfo which will query the extents of the image in British National ...


4

Achieved it by adding a pictureMarker of protractor PNG image. protactorLayer = new esri.layers.GraphicsLayer(); map.addLayer(this.protractorLayer); protractorGraphic = protactorLayer.add(new esri.Graphic(geometry, new esri.symbol.PictureMarkerSymbol('images/protractor.png', 250, 250)));


4

Of course you can change the OpenLayers default z-index. Just overwrite the z-index default range before anything. OpenLayers.Map.prototype.Z_INDEX_BASE.Feature = 2000; OpenLayers.Map.prototype.Z_INDEX_BASE.Popup = 4000; OpenLayers.Map.prototype.Z_INDEX_BASE.Control = 5000; var map = new OpenLayers.Map(); ...


4

It looks like GDAL is describing the outer edge of the 'origin pixel' and Arcmap is refering to the center of the origin pixel. If you add half the resolution of a pixel they'll match fine. This definition is often different with different software, it doesnt really matter, though you should know what you're looking at so you can take it into account. One ...


4

It's normal that azimuth and range resolution of SAR sensors differ, because they depend on different variables: The azimuth resolution (AR) of a SAR system is: AR=Length_of_antenna/2 The slant range resolution (SRR) of a SAR system is: SRR=(Speed_of_light*pulse_length)/2 The ground range resolution (GRR) of a SAR system is: ...


3

In theory, it should be possible to create one layer, add images as features with externalGraphic, and set their size (graphicWidth, graphicHeight) dynamically by context function. This will "emulate" georeferenced images. In practice, first problem is - after changing zoom, when feature's origin is not on screen, it's not displayed. Zoom in in example, and ...


3

Combined pan-sharpening, contrast stretching, and gamma stretching functions If you have access to ArcGIS (and the Spatial Analyst Extension) you can use the technique described in this blog to "blend" DEM (or imagery) with shaded relief. The main disadvantage of this solution is that it is static; you need to produce an RGB raster from your DEM so if you ...


3

I would use style's context object which calculates graphicWidth and graphicHeight depending on current map resolution. It applies to you first option (Vector layer).


3

You have tagged your question with OpenStreetMap, so I am assuming you are interested in the data in OSM's zoom levels. Please have a look at: Zoom Levels Usually you would not look at the whole world, at the same zoom level, as you would a small city. Your example is at zoom level 17, which has a scale of 1:4000. You would look at the world either at ...


3

Yes, your example seems logical, however I think you mean georeference not geocode. To start this setup you can do the following: Create a new polygon feature class defined with a spatial reference (in meters) that matches your geographic area of interest. Load in your polygon layer into ArcMap and start an edit session on it. Zoom in on the map to the ...


3

Try File -> Import -> Desktop Publishing Formats -> JPGIDRIS. You can then mosaic the individual imported jpegs now in Idrisi format.


3

In answer to your first question I found confirmation of the default compression quality (number) on the help page entitled Compression (Environment setting) where it says (with my bolding): If JPEG, JPEG_YCbCr, or JPEG 2000 is selected, you can also set the compression quality to control how much loss the image will be subjected to by the ...


3

Try converting your file to another/the same format (Raster/conversion/translate(convert format).There you can define a value for "no data", which you can set to a number different than 0. Hope it helps


3

The software to choose depends on your objectives. For GIS purpose, QGIS is great. It includes many toolboxes for spatial analysis. It is an open source alternative to ArcGIS. For image processing, you can use Monteverdi. Monteverdi is particularly usefull if you have very large images. It is an open source alternative to Erdas.


3

JAXA have made global L-band SAR mosaics at 50 m spatial resolution available from the PALSAR sensor: http://www.eorc.jaxa.jp/ALOS/en/palsar_fnf/fnf_index.htm Registration is required to download the data.


3

Try converting your color list from RGB format to HSV format and then sort the HSV list. What program did you get the RGB values out of? You might be able to tell it to simply report out HSV values. If you can't get HSV directly from that program, you could convert RGB to HSV here http://www.rapidtables.com/convert/color/rgb-to-hsv.htm Background: RGB ...



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