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12

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 ...


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

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 ...


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 ...


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

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

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

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


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

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

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


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

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

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 ...


3

as for the first part of the question - there might be some guidance here since it is suggested on the mosaicToNewRaster page that "When working with a large number of raster datasets, the Raster Catalog To Raster Dataset tool performs more efficiently". However, to look at the scripting option - you may be close (i can't test this at the moment, so you'll ...


3

Depending on your image type you can use Esri Raster Mosaic dataset - have your tiles and mosaic too without any (much) extra storage. The mosaic dataset works like a VRT file where the rasters are referenced but not imported so the table in the database stores the path and location of the tiles; overviews are a good idea but they don't take up much space. ...


2

I would advise against image processing with R. Rather, I would revisit mosaicing your imagery with ArcGIS. I used the following model recently to mosaic approximately 40 1m CIR raster images into a 25 GB mosaic (shown below). ArcGIS is definitely capable of large scale processing if you do it correctly. A few ideas: Make sure to set the raster storage ...


2

You can specify the parallel processing factor in the Mosaic environment settings (See attached image), which is new to ArcGIS 10.1 SP1. However, be cautious with this method since ESRI's documentation is very minimal and bordering on cryptic. I would do some timed runs (and share your findings here) before implementing these environment settings on very ...


2

I have a solution! It IS because of the old and infuriating GDAL upside-down export to GeoTiff (see my comments above)! Before anybody tells me that this has been fixed - I agree it does appear to be fixed but I was using a mixture of data converted with a older version of GDAL about 4 years ago and data I converted with the latest version of GDAL about 3 ...


2

I am now using an python+arcpy script for adding the raster to the Mosaic DataSet and then updating the value in the time field. For this, I am using some Python time/date time Manuipulation to get the correct expressions. My code is as follows: import arceditor import arcpy import datetime import time #time manipulations n=datetime.datetime.now() ...


2

Sadly, no. Not in 2.0. 2.1 should provide significant performance improvement over 2.0. No matter what you attempt in the database with 2.0, you are limited by the number of times the raster objects are serialized/deserialized. PostGIS 2.1 should be going beta in the next week or two (hopefully sooner than later).


2

Another illustrative documentation may be found here



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