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  5. January 10, 2020 – MRO HiRISE Updates - MRO HiRISE EDR, RDR, DTM and Anaglyph data products released through December 3, 2019 (Orbit 62,599) See https://wufs.wustl.edu/ode/odeholdings/Mars_holdings.html
  6. Did you try to use ENVI mask or band calculation to filter out the black pixels? If you like, you can upload the CRISM output together with the ENVI header online. I can have a try of your data. Thanks, June
  7. I mean the black pixels which ENVI don't process for certain band selections custom stretched: I want to "substract" only the painted shapes to put that over a CTX image, so the black part of this image would be the CTX image detailed surface or a DTM. Thank you, Wladimir
  8. Do you mean the black pixels along the edge of the image, which represent no data? If that is the "black pixels" you want to clean, in ArcGIS, when you overlain the CRISM output onto a DTM, right click the image, and choose properties. Below is the instruction to remove the background area of a raster layer using the Unique Values renderer in ArcMap. Arcscene has similar function to set the background color as transparent. Or you can google an example. I cannot use ArcGIS desktop these days due to a university license issue. People are still working on that. If you still have problem, I can send you a pic example as soon as I can access my ArcGIS desktop again. Thanks, https://desktop.arcgis.com/en/arcmap/10.3/manage-data/raster-and-images/removing-the-background-using-the-unique-values-renderer.htm June
  9. Thank you so much for your support June, now I can picture more clearly the general panorama. A remaining question would be about the process of create a "layer" from the CRISM image (using a browse product?) with only the "painted" pixels which represents the main mineralogy from a particular scene, as the maps who I've attached on the previous answer. Is there an automatized method to do is or maybe I should use a photo edition software to clean the images from the "black pixels" and create a layer with only the "colorized pixels"? Thanks, Wladimir
  10. I am not quite understand your question. Do you like to know how to give a 3D view? I saw your overlain of the CRISM onto a CTX. If you overlain all the images onto a DTM, and change the terrain exaggeration factors, you will see something like above figures from different points of views. HiRiSE DTM has much higher resolution than the DTMs from HRSC and MOLA. Map resolution for a HiRISE image is about 25cm/pixel, and the HiRISE DTM is about 1m/pixel. HRSC DTMs have various resolution from 50m/pixel to 400m/pixel. Most of the products are at the resolution of ~50m/pixel, 75m/pixel, and 100m/pixel. MOLA DTM is about 500m/pixel. CTX image is about 6m/pixel. And FRT CRISM data are about 18m/pixel. Depending on your needs, the higher resolution of a DTM, the more detailed features the terrain can represent.
  11. January 6th, 2019 - Mars Odyssey Release 70 Data Updates Loaded NS and HEND raw and derived data (EDR, DHD, DND, AHD, and AND) into ODE through June 30th, 2019 Updated THEMIS standard data products (IREDR, IRRDR, IRBTR, VISEDR, VISRDR and VISABR data) from February 19th, 2002 to June 4th, 2019 Updated THEMIS geometry data products (IRGEO2, IRPBT2, VGEO2, and VISALB data) from September 28th, 2013 to June 4th, 2019 See https://wufs.wustl.edu/ode/odeholdings/Mars_holdings.html.
  12. Hi June, I followed the steps that you indicated to me, and I've got this: Is the frt00003bfb_07_if166j_ter3 product charged with the PHY browse product (I've created frt00003bfb_07_if166j_ter3_2014params archive with CAT) over the D17_033826_2027_XN_22N018W CTX image. Looks very raw, but finally I'm moving forward, thank you. Nevertheless, what I'm looking to produce is something like this (images from Carter, 2015) : What procedures do I need to follow to obtain similar results? Also, I've notice that the HiRiSE DTM are very limited in quantity and spatially. If I need a 3D model of the surface where a DTM isn't available should I use a HRSC or MOLA product?. Do they work similar to a DTM? Thank you so much, Wladimir
  13. Hi Wladimir , ENVI 5.3 would also work for you. Please have a try. You can search for CTX EDR and Non-PDS Compliant RDRs through Mars ODE (https://ode.rsl.wustl.edu/mars/indexProductSearch.aspx) as shown in the attached fig1. In the data search results page (fig2), you can download the 'Pyramidized GeoTIFF' under 'Processed CTX' panel on the right. The Pyramidized GeoTIFF image has spatial reference information included in the image header. You can export a map projected CRISM image using the CAT menu function as shown in the fig3. The CRISM output can be overlain with the CTX RDR in ArcGIS. Please let me know if this doesn't work for you. Thanks, June Fig1 Fig2 Fig3
  14. Thank you June. Do you refer to the EDR CTX products?. I'm using ArcScene trying to overlain the CTX images on a HiRISE DTM model but I don't know how to do this with a CRISM image. Also, do yow know how to create a mineralogical map from the CRISM cubes?. I'm trying to export the summary parameters custom stretched images, but sincerely, I don't have idea how to this in a right way. Any help will be very greatful, thanks. Wladimir
  15. Thank you for your response Mr. Arvidson. Unfortunately, I only have access to the 5.3 version of ENVI software, so I would need a method using that version or Arcmap. Nevertheless, the flatten function seem to work well with the striping problem. Another question that I have is how much is necessary apply the "empirical corrections" for a TRDR product?. I mean, It is enough a standard corrected (atmospherical, photometric) TRDR product to analyze or I have to try to convert this on a "TER type product" through geom. normalization and spectral smile correction to analyze properly a scene?. Any help will be very appreciated. Thanks, Wladimir
  16. Hi Wladimir , You can download non-PDS Compliant CTX RDR data from Mars ODE(https://ode.rsl.wustl.edu/mars/indexProductSearch.aspx) or from ASU Mars Space Flight Facility's Mars Image Explorer (http://viewer.mars.asu.edu/planetview/inst/ctx/#T=0) directly. Those CTX RDR data are map projected and could be overlain with the HiRISE DTM. ArcGIS can project the data on the fly if they have different projections. I can also help if you need more assists on data registration. Thanks, June
  17. Wladimir: I suggest you use ENVI 5.5.2 interface and upgrade to CAT 7.4. You can use the flatten function in CAT to suppress column dependent striping. And with ENVI 5.5.2 it is easy to co-register CRISM images with CTX or HiRISE images. Let me know if you have these versions of ENVI and CAT. The CAT 7.4 is available from our PDS web site. https://pds-geosciences.wustl.edu/missions/mro/crism.htm Ray Arvidson PDS Geosciences Node Manager CRISM Team Member
  18. Hi all, as the title says, how can I remove in a simple way (I wish) this artifact from CRISM cubes?. I'm working with ENVI and CAT, but I'm not an IDL user, so if there exist a simple way to did it, would be really great. Also, how can I project a CRISM mineralogical map into a CTX image and into a DTM (HiRISE) terrain model?. I'm trying with ArcScene but it seems that it is possible with ENVI too. Thanks, Wladimir
  19. December 30th, 2019 Updated Diviner RDR query tool database from July 5th, 2009 to September 15th, 2019.
  20. Mars Odyssey Release 70 includes new GRS data. The new Raw data (EDR), Derived Neutron Data (DND), and Derived HEND Data (DHD) products cover the period April 1 through June 30, 2019. The new Averaged Neutron Data (AND) and Averaged HEND Data (AHD) products cover the period March 24, 2019 to June 28, 2019 , which is Ls=0 to 45 in Odyssey mapping year 10. Please note that Ls=0 to 15 (March 24, 2019 to April 23, 2019) are not included for AHD because it did not have enough valid data points to create averaged data. The data are online at the PDS Geosciences Node at http://pds-geosciences.wustl.edu/missions/odyssey/grs.html.
  21. December 20th, 2019 - LRO Release 40 has been loaded into ODE. Updated LAMP EDR and RDR products from July 6th, 2009 to September 15th, 2019 Updated LEND EDR_SCI, EDR_HK, RDR_RSCI, and RDR_CHK products from June 18th, 2009 to September 14th, 2019 Updated LEND RDR_DLD and RDR_DLX products from June 27th, 2009 to June 14th, 2019 Updated Diviner EDR and RDR products from July 5th, 2009 to September 16th, 2019 Updated LROC EDR, CDR and RDR products from June 30th, 2009 to September 15th, 2019 Loaded Mini-RF new Version 3 Bistatic radar data products (EDR, RDR, and DDR) from January 28th, 2019 to February 4th, 2019 Updated LOLA EDR products from June 18th, 2009 to November 7th, 2019 Updated LOLA RDR products from July 13th, 2009 to November 7th, 2019 Updated LOLA RDR query tool database from July 13th, 2009 to November 7th, 2019 In Progress Diviner RDR query tool database from July 5th, 2009 to September 15th, 2019 Please see ODE Lunar Holdings - https://wufs.wustl.edu/ode/odeholdings/Moon_holdings.html
  22. Hi Vidyesh, A data ignore value is a designated pixel value that ENVI should ignore when processing an image or computing statistics. When CAT processing these image, it sets the noData as 65535. If the data ignore value is not set as 65535, when ENVI display these images, it displays the whole data range (i.e. from 0 to 65535). So the input histogram for each color (RGB) is from 0 to 65535, the output display will arrange them from 0 to 255. Since most values data are close to zero end not the 65535 end, it returns 0 (for each color i.e. RGB) on the output display instead of a value between 0 and 255. So ENVI now displayes a image which has R=0, G=0, B=0. which is actual a black image. Hope this helps. Thanks, Feng
  23. Thank you very much for your reply, as you mentioned above the data_ignore_value in header was none in my case. I replaced the value with your data_ignore_value and the image was generated. Again I am really grateful for your quick response and for helping me out. Can you please explain to me what actually happened when I replaced the data_ignore_value in the header, that will be really helpful. Thank you.
  24. The ODE map search has been updated to have product coverage map layers grouped by mission/instrument/processing level. This map layer organization matches the product search page. Mars Orbital Data Explorer Map Search Lunar Orbital Data Explorer Map Search Mercury Orbital Data Explorer Map Search Venus Orbital Data Explorer Map Search Mars ODE Map Search Example:
  25. Hi Vidyesh, I download these two data and processed the exact same way as you described but didn't find any problem. Your processing looks fine. One thing you may look at is the header file of the stacking image. The blank in your image could be the data_ignore_value in your header. Would you please compare the header file with mines: ENVI description = { Create Layer File Result [Tue Dec 17 09:47:59 2019]} samples = 751 lines = 634 bands = 518 header offset = 0 file type = ENVI Standard data type = 4 interleave = bsq sensor type = Unknown byte order = 0 map info = {MRO Mars Equirectangular [IAU 2000] [-35.00N; -39.88E], 1.0000, 1.0000, -6787.3851, -2187402.8323, 1.8000000000e+001, 1.8000000000e+001, D_Mars_2000_IAU_IAG_custom_sphere_lat35, units=Meters} projection info = {17, 3389570.0, -35.000000, -39.880000, 0.0, 0.0, D_Mars_2000_IAU_IAG_custom_sphere_lat35, MRO Mars Equirectangular [IAU 2000] [-35.00N; -39.88E], units=Meters} coordinate system string = {PROJCS["MRO Mars Equirectangular [IAU 2000] [-35.00N; -39.88E]",GEOGCS["GCS_Mars_2000_IAU_IAG_custom_sphere_lat35",DATUM["D_Mars_2000_IAU_IAG_custom_sphere_lat35",SPHEROID["Mars_2000_IAU_IAG_custom_sphere_lat35",3389570.0,0.0]],PRIMEM["Reference_Meridian",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Equidistant_Cylindrical"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-39.88],PARAMETER["Standard_Parallel_1",-35.0],UNIT["Meter",1.0]]} wavelength units = Nanometers data ignore value = 6.55350000e+004 band names = { Layer (Band 1:frt0001176e_07_if164s_trr3_corr_p.img), Layer (Band 2:frt0001176e_07_if164s_trr3_corr_p.img), ..... Also I am using CAT 7.4 in ENVI 5.5 standard (not classic version) to process data. This may be another difference between us. Please let me know if the problem is still there after you check the header or reprocessed in ENVI 5.5 standard. Thanks, Feng
  26. Hello My name is Vidyesh Sathe, I am actually working on my Dissertation in Planetary Geology, I am pretty new to Crism Data Set and Analysis of Crism Data. I am using Data set which is frt0001176e_07_if164ds_trr3.img and frt0001176e_07_if164l_trr3.img, i am using both VNIR And IR data. sir I followed the process given in CRISM Demonstration: Data Access, Processing, and Analysis - 3rd Planetary Data Workshop 2012, After pre-processing given in presentation, I wanted to Combine both VNIR and IR data. so i followed standard Envi process which is, Envi-Basic Tool-Layer stacking I imported both map-projected images of VNIR(S) and IR(L). But as the result the image was completely Black but the information was present(Spectra information from 0.5-3.9) I will be really grateful if you can explain to me what i am doing wrong, and what should I do to correctly project the image. Thank You.
  27. Release 40 of Lunar Reconnaissance Orbiter data is now online at the Geosciences Node. This release includes new data acquired between June 15 and September 14, 2019, for most data sets. Data can be reached from the Geosciences Node LRO page. The Lunar Orbital Data Explorer allows searching and downloading of LRO data.
  28. Many publishers of scientific research, including AGU, are now requiring authors to make their data available in a public repository as a condition of publication. (See AGU's policy here.) The Geosciences Node has been contacted by a few such authors asking whether the PDS will receive their data so that their articles can be published. In some cases the data set in question is a suitable candidate for a PDS archive, but usually it is not. If you are the author of an article for a journal that requires you to archive your data in a public repository, you may not wish to undertake the steps involved in submitting the data to the PDS, steps that include labeling, documenting, and possibly reformatting the data products. The effort involved may not be justified for a small, simple data set. In this case we recommend that you submit the data to one of the many available online data repositories, such as figshare (figshare.com) or Dataverse (dataverse.org). On the other hand, if you believe your data would be a useful addition to the PDS, and you are willing to put in the work and submit the data to a peer review, please send your request to geosci@wunder.wustl.edu.
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