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9

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.


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

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.


4

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 ...


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 ...


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 ...


3

You can block out the "white" using a Mask function, through the image analysis window. Change NoData Interpretation to "All", and add values 0 (minimum) and 250 (maximum) to all bands in your raster. As your image may contain "near white" values, you may want to lower the masking threshold to, say, 245. The "white" values will also depend on the pixel depth ...


3

I guess you have gdal and the bindings installed, and some coding ability, so I'll just provide an outline: import org.gdal.gdal.gdal; import org.gdal.gdal.Band; import org.gdal.gdal.Dataset; ... Dataset dataset = gdal.Open(filename); Band band = dataset.GetRasterBand(1); ... // Do some band operation, like band.ReadRaster() to get the data, whatever you ...


2

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.


2

Using OpenStreetMap you can compute the building height through some tags on buidings. As you can see there is an extrusion in Bucharest (and whole world) in this 3D simulation: http://demo.f4map.com/#lat=44.4379244&lon=26.1004697&zoom=18. Note that the accuracy of the height of buildings is random and some buildings does not have height relative ...


2

For getting DSM or a DTM some countrys have thier own DSM for free, for example in Spain is this page www.cnig.es, and you can download for free the DSM and DTM but only for Spain. Search if your country have similar system.


2

Here's a fully reproducible example with output: set.seed(310366) # so we get the same random numbers library(raster) uk = getData("GADM",country="GBR", level=0) bbox(uk) # tells us the bounds (I think it goes as far west as Rockall) # make 200 points over that area: pts = cbind(runif(200,-13,1), runif(200,50,60)) That code has done the basic setup. Now ...


2

Using QGIS, the simpliest way is to load the data as delimited text, select EPSG:4326 WGS84 as CRS and save the result with Project -> Save as image. The Raster -> Conversion -> Rasterize function is a bit more sophisticated, but since your points are close to each other, it needs reprojecting to a projected CRS like UTM zone 10 first to get a ...


2

Since the points don't form a regular grid you could use gdal_rasterize. Set up a VRT header like so: <OGRVRTDataSource> <OGRVRTLayer name="test"> <SrcDataSource>test.csv</SrcDataSource> <GeometryType>wkbPoint</GeometryType> <GeometryField encoding="PointFromColumns" x="longitude" y="latitude" ...


2

From the esri help pages... When you are in the edit report layout page. Select picture under element on the left hand side and add it to whatever location you want on your report. When you click on the box, on the right hand side there is a place to add your source which you have 3 choices: Source 1: choose a field You can choose any Raster or ...


2

I believe you need a minimum of 3 points to translate, scale, and rotate. The procedure and open source code for doing this is explained here: http://docs.opencv.org/doc/tutorials/imgproc/imgtrans/warp_affine/warp_affine.html I'm assuming your images are not georeferenced, so it should not matter what your map projection is since the user only has to ...


2

rasterImage draws a raster image at a given location and size. Below is a very rough example, which you can hopefully adjust to your needs. (I made up some location points, you would obviously have to use yours.) library(rgdal) library(png) # load icons in PNG format iconfile1 <- ...


2

I do this a lot with historic maps, and began by using @nicksan's method, but had the same issues the OP mentioned. I haven't used the mask method (will try soon) but here's what I do now, if you can deal with not having the red and blue in your overlay: Make sure you have Updated Georeferencing in the georeferencing toolbar and then remove the layer from ...


2

Two of the best commercial high resolution multispectral products available are Worldview-2 and Worldview-3. These sensors are commonly used for natural resources and biodiversity applications. You can learn more about these products here. Another more cost efficient option is to use RapidEye medium resolution imagery (details). Of course, if your budget ...


1

Export the image from Data View. Check the Write World file in the general tab. There you can also control the image output resolution and size. Image quality of the output will be compromised either way because you have georeferenced the image and thus altered/warped or stretched the original pixels. Work out the outptut size and resolution that closely ...


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

you can add the image as a Leaflet control, then Leaflet takes care of the z-indexing and positioning. var MyControl = L.Control.extend({ options: { position: 'bottomleft' }, onAdd: function (map) { // create the control container with a particular class name // ** you can add the image to the div as a background image using ...


1

Here's a fuller answer about the synthetic aperture radar (SAR) data available from the Alaska Satellite Facility at no cost to users. The datasets include Seasat (1978 data newly processed in 2013), InSAR, PALSAR (including radiometrically terrain-corrected products), RADARSAT-1, ERS-1, ERS-2, JERS-1, UAVSAR, AirMOSS, AirSAR, and more. SMAP data will ...


1

It looks like you are trying to directly apply the radiometric calibration equations from the Landsat handbook to SPOT. The equations are slightly different because the DN calibration method is different. Take a look at the SPOT 5/6 handbook for the correct equations. You also want to use the solar zenith (not elevation) as the theta parameter. Here is a ...


1

SimpleFeatures are used for Vector data, for images you will need a coverage reader. See the image tutorial for a good introduction.


1

In the ArcGIS Help 10.2 there is a page called Managing the performance of ArcGIS map services which discusses options for addressing any display performance issues and includes the approach that you mention in your question: Precompute information results when you can do so. For example, you can precompute the maps that are delivered with ArcGIS for ...


1

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.


1

As others have mentioned, the best practical way to determine which bands are which is to look at the source metadata, which is widely available for common products like ASTER and Rapideye. You can also derive much information about the bands doing a little legwork in Erdas. This is a useful skill to have if you are given, for example, a Rapideye image ...



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