Latest Contributions by PeterBecker

I would also suggest using the Raster Products capability and then edit the function chain. Following in ArcGIS Pro which I would recommend using instead of ArcMap, but similar is available in ArcMap. In Catalog navigate to the Pleiades scene. The Dim file will appear as a 'product' if you open you can see options such as Multispectral and PanSharpen Drag into your map. Right click on layer and select 'Edit function chain'. If the scene has an RPC then you will see a geometric function (but so far does not have a DEM) Use Add Raster icon or drag a DTM from content into function editor and connect to the Geometric function. (Note if you are pansharpening there are two geometeric functions) In the Geometric properties set the method to 'Use DEM' and if your DEM is orthometric height (eg SRTM) then tick the 'Geoid' option. If you are working with collections of such imagery then look to use Mosaic Datasets. There are workflows to automate the creation and maintenance of such mosaic datasets see 'Managing High-Resolution Satellite Imagery' ... View more

There are many different method to achieve this and the optimum choice is dependent on factors such as whether the source is pixel aligned, the total size of the data and type of storage (Local or cloud). The method you are using works well and is similar to what is used in the Hycom sample. . In this case the source is similar to what you mention, a MRF referenced by a mosaic dataset. What you are doing is not incorrect, but we know there are limitations to this as the datasets get larger. This use of a Mosaic dataset and individual rasters per slice is not optimized for the fact that in this case all the pixels are aligned in a single coordinate system. (Remember mosaic datasets can many different coordinate systems simultaneously). Also the data is stored as pixel blocks. To get a temporal profile requires reading many pixel blocks from storage. If the storage is fast and you don't have too many layers then this is not an issue. In your case you are referring to over 1000 layers, so such as solution would need to read over a thousand pixel blocks for any profile location. (Not optimum). The solution as you have seen is to use a CRF with Transpose option. The CRF is optimized for the storage of such pixel aligned datasets and the transpose re-arranges the storage of the pixels such that a query for a profile need only make minimal disk access. You would still manage your data by creating a Mosaic dataset. With ArcGIS Image Server 10.8 you can directly publish a Transposed CRF and the Sample function will then near instantaneously return you the pixel for a point or small area of interest. You can you this for a profile or extract to a table of choice. One drawback with Pro 2.5/10.8 with CRFs is that you can not append to a CRF so that when you get a new dataset  you need to recreate the CRF. (But such an append is available in upcoming 2.5/10.8.1).  What I need to check on is how WABIS provides access to this profile capability. I'll check and get back. ... View more

Easiest way to do that is following this steps:  Use Enterprise Builder to install ArcGIS Portal/Server/Data Store https://enterprise.arcgis.com/en/enterprise/10.5/install/linux/eb-sys-req-link.htm Add your image server license to authorize your server. Now configure the server  as raster analytics server following this guide https://enterprise.arcgis.com/en/image/latest/raster-analytics/configure-and-deploy-arcgis-enterprise-for-raster-analytics.htm ... View more

Note that once you have the data as a raster you could determine the sift by splitting the problem into two: X and Y direction. For X direction you create a raster that define the slope (Rise/Run) in X direction. Set to NoData all values where abs(value) is below a threshold (eg 1 for 45deg). ShiftX = HeightDifference / X direction slope. Repeat similar for Y direction. I don't know of a function pre-written that does this. Once created you could just select any area and the average of the resulting pixels should be the shift to be applied. ... View more

Suggest you us the concept of Source and Derived Mosaic datasets. Create a 'Source' mosaic dataset as you would any mosaic dataset. Perform the QC. To create a derived mosaic you use the 'Table Raster Type' and select as input the source mosaic dataset. All (or selected) records from the source will be copied to the derived. This is used in quite a number of the workflows. Also see Source/Derived Mosaic datasets. The syncronize can be used to re-create a mosaic dataset from a source. Say you create a mosaic dataset by adding all imagery from a specific directory and then at a later time more images are added to the directory, then you can used syncronize and it will re-add them to include the additions. It should also be possible to use Synchronize with a derived mosaic dataset. IE if you change the source you can update the derived using synchronize. ... View more

Brian I had a quick look at the files. I downloaded the color image (TIF) and georeferenced it based on the layer that you provided earlier. Looking at the extent  it is apparent that these are two separate scans. (See white border from BW around the extent of the color). As a result there will not be a constant offset or scale between the two. The image coordinates in the color image will be approx a scale and offset different to the bw but will change from scan to scan (Note the AUX.XML file you have above appears to be for a sheet below this one) I believe you are going to have to manually georeference them. Simplest way is to load the BW image, zoom to its extent. Add the Color image. Go to georeferencing, Fit To Display, and then measure 4 manual control point close to teh corners of each sheet. Then Save and this will will write the new Aux.xml.  I'm not sure what color mages you are downloading, but for more compact storage I would recommend you use OptimizeRasters and convert to TIF with JPEG compression first. ... View more

A) If the color maps where the same scans as the original, but just a color version then if you originally georeferenced the bw using the Save (vs Save as) option then there will be an .Aux.xml for each image. This will contain the georeferencing information (control points) and transforms selected. You should be able to just copy the files so they have the appropriate extension for the color images. If you get an error about stats or strange colors, then open the xml file in a text editor and remove the stats section. B) When you did the original georeferencing did you record the control point files? If so you can use these again for each of the new images. If the new images have a different scale or offset from the originals, consider just editing the values (in excel). This might not be accurate enough but would be an alternative to the TFW defined in C.  C) If the images are new scans but similar resolution and clipping then instead of using the Aux.xml copy the .tfw or .tfwx (but rename to .tfw) to the new images. If you open then up in Pro the images should fall in approx the same location (do ensure you use the same projection). Now when you use the georeferencing tool with the bw images as the background then the process should be a lot faster as you can just pick points between the images. There is also a auto-georeference feature. Before using it make sure the base map is off and the only layer other layer on is the bw scans.  The system might be able to match between the images and auto-georefernence. This tool is primarily for optical imagery so it might not work with these scanned paper maps, but it is worth the try. D) If none of the above work, then you will probably need to resort to manually georeferencing, but use the BW images as a base to measure control points of which should be a lot faster. Once georeferenced you should be able to create a new mosaic dataset and "Import footprints" from the original mosaic dataset, if you used these to clip the images.  ... View more

Not sure on the Sleuth model. Suggest you look to using raster functions to define the transforms you are looking to apply. Also look to use ArcGIS Pro vs ArcMap. The greyscale function simply converts a multiband image/raster into a single band image/raster by multiplying each band by the defined weight (which is normalized by the sum of weights). If you don't see a result it may be that no stats are available or the bit depth of the output is not what you expect.  ... View more

Are you attempting this in ArcMap, Pro or through a web client?. The Image Service REST API is extensive. See link. You can pass a raster function request as part of Export Image. This can be a predefined function as defined in the service or a raster function chain. Similar in ArcMap and Pro you can pass parameters for the functions or function chains. ... View more

MetaData for the rasters should be stored as auxiliary files to the individual rasters. There a multiple standards that can be used to store such image metadata. One method is to use store the data in the .AUX.XML stored next to the raster. This is sometimes referred to as GDAL PAM). When the mosaic dataset is created the metadata will be extracted as attributes if fields with the same name exist in the mosaic dataset. These metadata attributes are then available for search, sorting etc in the mosaic dataset. If published and downloaded the Aux.xml (and some other associated metadata files) for the image will also be downloaded and so available. Note this does not work for Export which clips and returns the pixels for a specific AOI and can be the results of mosaicking of multiple images. ... View more

If you are referring to the imagery being captured by the sensor then I would recommend 16bit 3band. Ensure you use the OptimizeRaster tools to structure them appropriately. I would recommend you use MRF with LERC compression for best lossless compression, but you may prefer to use Tiled TIF Deflate. You can use these in ArcGIS for example using Ortho Mapping to generate the ortho images. If you are using the dynamic mosaicking capabilities of ArcGIS to gain the maximum detail, then leave the images as 16bit. If you are looking for a single seamless image then use the color correction (dodging) and seamline generation then export (as TileCache, CRF or TIF files) but set the output to 8bit and use a JPEG quality of 95%. This will significantly reduce the data volume and provide the visual product that you are most likely looking for. ... View more

If the imagery has been correctly processed then 8bit imagery will provide the vast majority of the details. If you are capturing imagery directly from a sensor I would use 16bit. There will be no visual difference until you start further enhancing the imagery. ArcGIS provides features such as DRA (Dynamic Range Adjustment) that enable the full details such as shadows and highlights to be seen and for this 16bit can provide more information. Assuming no compression 16bit takes 2x data volume of 8bit. With compression these factors change. JPEG can be used to compress 8bit imagery very well and can achieve about 8x compression with nearly no visual loss. Esri support also 12bit JPEG compression can can be efficiently used to compress imagery where the data range has been set to 0 -4096. This is often a good way to get additional dynamic range while enable compression of about 6x. For 16bit imagery one can use JP2 which can get about 30% additional compression, but I would not recommend due to the significant conversion required. Esri also support LERC which can typically get about 2.5x compression of 16bit imagery losslessly and by allowing some loss in precision the compression can be greater, but for optical imagery I would use JPEG if size is a significant concern. For more details on this see Imagery Formats and Performance ... View more