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17

Well, I found the answer. Esri did in fact answer this with an in depth presentation at the 2010 San Diego User Conference called "Managing Imagery and Raster Data in ArcGIS". Here is the link for anyone else who is interested: http://gis.idaho.gov/portal/pdf/Framework/Imagery/ManagingImageryRaster.pdf My short summary of this is: Raster Catalog is on ...


7

Sure, gdal_translate: gdal_translate in_file.tif out_file.tif -co "PROFILE=GeoTIFF" -co "TFW=YES" the above command should do the trick.


7

As whuber mentioned, often statistics found in the raster properties are sometimes approximate or are out-of-date. They are predetermined properties that can be misleading to the actual raster values. Calculated your own min / max values from 100% of the actual data using NumPy arrays. See Working with NumPy in ArcGIS, and RasterToNumPyArray (arcpy). E.g.: ...


6

Another option is to build a Virtual Raster. You can perform this using GDAL, FWTools, or QGIS. Essentially, a virtual raster will make the mosaic, but as a pointer file, that brings in all the imagery. The file size stays relatively small, and the performance is good. I am using it to mosaic 5cm imagery, and I like the results.


6

The issue here is that mosaic and do.call are expecting a raster object in the list and not just character names of the raster that is contained in the "rasters1" vector. You are, in effect, asking to mosaic a name in a vector and not a raster object. # Create some example data require(raster) r <- raster(ncol=100, nrow=100) r1 <- crop(r, ...


5

You need to create a raster that has spatial extents that contain both of your previous rasters (see Create Raster Dataset). I suggest setting the value for this new raster to be 0. Then, you can add the existing rasters to the new blank raster. To fill in the gap, you can use Spatial Analyst, choosing the option Neighborhood Statistics to interpolate or ...


5

I ran across this mosaicing the True Marble imagery as well, though I used gdalbuildvrt and then gdal_translate. From memory, the recalcitrant tiffs are stored as a single band with a color table. Just convert them to 3 band RGB with gdal_translate: gdal_translate -expand rgb TrueMarble.250m.21600x21600.B4.tif TrueMarble.250m.21600x21600.B4.RGB.tif


5

I noticed the Mosaic To New Raster tool has a Mosaic Operator setting. The default is LAST, which states the output cell value of the overlapping areas will be the value from the last raster dataset mosaicked into that location. Settings are FIRST, LAST, BLEND, MEAN, MINIMUM, and MAXIMUM. I would try other settings or reorder your rasters in the Input ...


5

Agree to the comment of @FelixIP, one possible solution is to first create a whole raster using RasterMosaicker transformer, then reproject and re-tile the Raster with RasterTiler transformer. This can be a ressource consuming approach, if you have many input tiles. Another approach is to apply nodata values with the RasterBandNodataSetter (Value = 0) or ...


4

First, you are using R. R Studio is just an IDE for R so in the future please make this an R question. I will warn you that working with HDF files in R is a pain. In theory GDAL supports HDF5 so one could use readGDAL in the rgdal package. Depending on the source of the data readGDAL has a high fail rate making it less than reliable. Historically, there ...


4

I recommend creating a mosaic dataset within a file geodatabase. There are many advantages of working with this type of data model. For one, you can modify properties of the dataset once it is created to enhance rendering. You also have much finer control of how these data are served compared to a stand-alone raster dataset created using mosaic to new ...


4

Your best bet would be to mosaic the raw red band and near infrared band images from which the NDVI images are derived. There are techniques for creating seamless mosaics for images, e.g. through the use of histogram matching and feathering techniques. For areas of overlap, the feathering method will calculate the output value as a weighted combination of ...


3

In addition to @Ryan Garnett answer, you can convert the VRT file to BIGTIFF using gdal_translate if you absolutely need a unique file (this is often not necessary as most software can read vrt's). Just make sure that you use gdal_translate -co BIGTIFF=YES -co TILED=YES source.vrt result.tif if your tif exceed 4 Go


3

There seems to be two camps about this one. Some prefer to mosaic before classification, others prefer to classify the images before mossaicking. Personally, I would classify the images first, then mosaic them. Have a look at the discussions on this page and you'll find arguments for and against both methods. Generally, they state that you should ...


3

FME RasterMosaicker can accomplish this: You will have to modify these setting to suit your sampling and Interpolation. You should be be able to achieve something like this if your aerial photo have been ortho-rectified: It might take a few goes- best advice is to try a sample of 3-5 adjoining images and test. source of image (safe.com) and more ...


3

There is some good description of NoData in raster datasets in general here. Otherwise, I'd suggest using the Define Mosaic Dataset NoData GP tool.


3

There is a GRASS GIS 7 Addon, i.histo.match which performs histogram matching on the given input images. The histogram matching method is based on the method Cumulative Distribution Function (CDF) of two or more histograms. For RGB images you will mosaic them color by color. If needed, a post-mosaic color optimization can be achieved with i.landsat.rgb (it ...


3

Merging is combining several (usually vastly overlapping) rasters into one either single-banded or multy-banded raster wich area isn't much bigger then the area of any original raster. Its purpose, well, is to get one raster out of many. Mosaicing is assembling of several adjusted (or slightly overlapped) rasters into the set of non-overlapping rasters or ...


3

Merge is usually used to refer to the combining vector data whereas mosaicking is used when combining raster data. At least that's how the terms are used with ArcGIS and QGIS.


3

There is some generic information on patching the gaps at http://www.quantdec.com/SYSEN597/ which can be translated into any gis environment


3

Try gdal_merge. You can grab the GDAL framework from William Kyngesburye's website. Instructions for utilizing gdal_merge can be found here.


3

The simplest way I can think of is to take the merged raster you have just made and save out the red band (perhaps using gdal_translate and the -b switch). Alternatively you could use QGIS' raster calculator to save only the red band as a new raster.


3

You have to enter the parameters in the correct order when using Python. From the ArcGIS 10.2 help page, the following is the correct format: MosaicToNewRaster_management (input_rasters, output_location, raster_dataset_name_with_extension, {coordinate_system_for_the_raster}, {pixel_type}, {cellsize}, number_of_bands, {mosaic_method}, ...


3

A successful workaround was to create a new file geodatabase, and write the mosaic image to this - the gap is now gone, with no other changes to the code. This may be a bug, or perhaps there's a problem with using PNG files as the output?


3

Yes, make the data 8 bit. I would use GDAL_Translate -ot byte, it's less messy than trying to do it in ESRI. Mosaic to new raster will also resample your data if there isn't an exact (or near exact) cell alignment. In the mosaic tool, which is called by mosaic to new raster there is a cell alignment parameter which determines if a raster is resampled or ...


3

I support the answer by radouxju, but would like to add: As you have chosen to do this in chunks (good idea! you can process multiple chunks simultaneously) I recommend using an overlap of ~1k with your tiles. You have not elaborated on how you create the DEM from LiDAR data but lets assume that you are using LiDAR->MultiPoint->Terrain->Raster DEM ...


3

Have you tried looking at a software package like pix4dmapper? There is a free trial available with a fair amount of functionality called pix4dmapper discovery: https://pix4d.com/download/ I use this software a lot for mosaicing UAV acquired imagery and it may be worth your while to give it a shot. For images without georeferencing, you could look at ...


3

Try QGIS' Saga Plugin > Grid Tools > Mosaick raster layers. You can combine a number of rasters and classify overlapping areas with blending, feathering, min and max values.


3

It seems that there are two things going on here. First, your tiles are not seamless, in that in the areas of overlap at the edges of the tiles, the elevations are not identical. I can confirm this as I digitized several points along the overlapping area and extracted the elevations in both raster DEMs and found this: In the case of the two tiles that you ...



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