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27

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 ...


17

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, ...


13

You may consider GRASS GIS which offers a rather complete processing chain for Landsat including radiance correction for Landsat 8. For details, see http://grasswiki.osgeo.org/wiki/LANDSAT Examples: Landsat 1-5,7,8 data import Auto-enhance colors, natural color composites Calculate Top-of-Atmosphere Reflectance and band-6 Temperature Haze removal ...


13

You could create a virtual mosaic from all Tiff files: gdalbuildvrt mosaic.vrt c:\data\....\*.tif and convert it afterwards: gdal_translate -of GTiff -co "COMPRESS=JPEG" -co "PHOTOMETRIC=YCBCR" -co "TILED=YES" mosaic.vrt mosaic.tif Keep an eye on all the GDAL creation parameters to compress your mosaic and use gdaladdo to add overviews. More info here: ...


9

As whuber mentioned, often statistics found in the raster properties are sometimes approximate or are out-of-date.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.: ...


7

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 ...


7

If you have not recalculated the statistics, you can do this by right clicking on the raster and selecting "Calculate Statistics"


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

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 ...


6

The differences between Raster Datasets, Mosaic Datasets, and Raster Catalogs are explained well on the Esri help page. At the bottom has a chart that breaks everything down and list pros and cons of all three types. http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#/Raster_data_organization/009t0000000n000000/


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

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 ...


6

You can use r.patch for that (see help file) You probably want to set the region first to encompass all raster layers, after which you can use r.patch to 'mosaic' the layers. The following example is from the helpfile: export MAPS=`g.mlist type=rast sep=, pat="map_*"` g.region rast=$MAPS -p r.patch in=$MAPS out=mosaic Use the keyword export when you are ...


6

As the other replies say the statistics are likely out of date. If you prefer using ArcGIS try the Calculate Statistics tool in the Data Management toolbox. This should update the statistics for you.


6

Found a quick solution - replacing "-hidenodata" with "-srcnodata 0" in the .vrt build: gdalbuildvrt -srcnodata 0 mosaic.vrt geo_pict20140910_131*


6

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 ...


6

You may see considerable benefit if you load them into a single virtual raster (vrt). You can do that through the processing toolbox, by searching for "build vrt"


5

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 ...


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

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.


5

Chris, Maksim is right, you should be able to solve this problem by mosaicing each of your individual tiles into a single DEM. The problem that you have currently is that each of the individual DEMs has it's own display minimum and maximum values over which the same greyscale palette is being stretched. Consider, for one tile the 256 (perhaps more) grey ...


5

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 ...


5

The best solution to this is making a list of the rasters, then passing this to a function based on the apply family The following code was pulled from a similar question wrapped into a function and should work for you mosaicList <- function(rasList){ #Internal function to make a list of raster objects from list of files. ListRasters <- function(...


5

1st: The exact code you posted (https://code.earthengine.google.com/ce1a151ce06497b20cf1793715cb0120) did export the image correctly. So the error cannot be reproduced. May be, you changed the 'ROI' to a place where the filtered collection had no images. 2nd: There are no images because you filtered by cloud percentage, and so, it found images that suited ...


4

if you are using arcmap you can use the stretched values along a colormap setting. (similar in qgis) this also allows you to change the stretch type and so doesn't require building statistics.


4

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 ...


4

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 ...


4

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.


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 ...


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