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data set:
MRO CONTEXT CAMERA EXPERIMENT DATA RECORD
LEVEL 0 V1.0
MRO CONTEXT CAMERA UNCOMPRESSED IMAGES
MARS RECONNAISSANCE ORBITER - MRO-M-CTX-2-EDR-L0-V1.0 - starting 2005-08-30T00:00:00Z -
instrument:
CONTEXT CAMERA for MRO
Information about the CONTEXT CAMERA for MRO instrument -
instrument:
CONTEXT CAMERA for MRO
Information about the CONTEXT CAMERA for MRO instrument -
bundle:
Mars Global Cave Candidate Catalog Archive Bundle
The Mars Cave Database -
bundle:
Mars Global Cave Candidate Catalog Archive Bundle
Mars Global Cave Candidate Catalog Archive Bundle -
instrument host:
MARS RECONNAISSANCE ORBITER
Information about the MARS RECONNAISSANCE ORBITER instrument host -
instrument:
CONTEXT CAMERA for MRO
Information about the CONTEXT CAMERA for MRO instrument -
collection:
Mars Global Cave Candidate Catalog
Mars Global Cave Candidate Catalog -
collection:
Mars Global Cave Candidate Catalog
Mars Global Cave Candidate Catalog -
bundle:
Mars MRO CTX Global Mosaic Murray Lab v1
The V01 release of the Global CTX Mosaic, by Caltech's Murray Lab, is comprised of 86,571 separate images acquired between 2006 and 2020. Overlapping images were registered to each other (semi-controlled) before blending. The final CTX mosaic covers > 99.5% of the surface of Mars between 88°S and 88°N. We emphasize transparency both in how the mosaic was generated and for users to understand where data in the mosaic come from. We have developed a Python-based pipeline that incorporates non-destructive image processing techniques that preserve all information about the original data that comprise the mosaic and map all seams. This connects the mosaic directly with its original data, ensures that blending artifacts are not mistaken for landforms and geologic contacts, and provides instant access to the raw data that comprise the mosaic. Unzipped and uncompressed, the entire mosaic is about 10TB. -
collection:
Mars Global Cave Candidate Catalog
Mars Global Cave Candidate Catalog -
collection:
Mars Global Cave Candidate Catalog
Mars Global Cave Candidate Catalog
Data Sets and Information