Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
2,007
datasets available to search
ShareScore release 0.9.0
Dataset results
2,007 results for “Image Studies”
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1993-02-25
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1993-02-25 (15:08:25.1360250Z) by Landsat 5, row 33, path 15. Cloud cover was 10 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331993056XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T16:14:10Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1993-04-14
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1993-04-14 (15:08:47.4810060Z) by Landsat 5, row 33, path 15. Cloud cover was 20 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331993104XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T17:38:37Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1993-05-16
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1993-05-16 (15:08:55.9210130Z) by Landsat 5, row 33, path 15. Cloud cover was 10 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331993136XXX04, LPGS_11.6.0, USGS, Sioux Falls, 2012-03-09T19:50:38Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1993-06-01
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1993-06-01 (15:08:59.4010130Z) by Landsat 5, row 33, path 15. Cloud cover was 10 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331993152XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T16:16:36Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1993-06-17
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1993-06-17 (15:08:57.1690190Z) by Landsat 5, row 33, path 15. Cloud cover was 0 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331993168AAA02, LPGS_11.6.0, USGS, Sioux Falls, 2012-03-09T19:43:29Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1993-07-03
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1993-07-03 (15:08:50.7250690Z) by Landsat 5, row 33, path 15. Cloud cover was 30 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331993184XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-05-05T01:40:48Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1993-08-04
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1993-08-04 (15:08:51.1270060Z) by Landsat 5, row 33, path 15. Cloud cover was 20 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331993216XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T16:15:34Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1993-08-20
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1993-08-20 (15:08:50.5580000Z) by Landsat 5, row 33, path 15. Cloud cover was 10 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331993232XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T16:16:39Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1993-09-05
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1993-09-05 (15:08:48.5890940Z) by Landsat 5, row 33, path 15. Cloud cover was 0 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331993248XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-05-30T17:40:55Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1993-10-07
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1993-10-07 (15:08:41.0700130Z) by Landsat 5, row 33, path 15. Cloud cover was 0 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331993280AAA02, LPGS_11.6.0, USGS, Sioux Falls, 2012-03-09T19:54:07Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1993-10-23
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1993-10-23 (15:08:35.1660810Z) by Landsat 5, row 33, path 15. Cloud cover was 0 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331993296XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-05-30T17:40:03Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1993-11-08
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1993-11-08 (15:08:28.5240940Z) by Landsat 5, row 33, path 15. Cloud cover was 0 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331993312XXX02, LPGS_11.6.0, USGS, Sioux Falls, 2012-03-09T19:49:23Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1993-12-26
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1993-12-26 (15:08:07.9380190Z) by Landsat 5, row 33, path 15. Cloud cover was 10 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331993360XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T16:13:56Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1994-02-28
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1994-02-28 (15:07:17.2660000Z) by Landsat 5, row 33, path 15. Cloud cover was 0 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331994059XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T16:16:02Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1994-03-16
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1994-03-16 (15:07:03.3900190Z) by Landsat 5, row 33, path 15. Cloud cover was 40 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331994075XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T16:16:26Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1994-04-01
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1994-04-01 (15:06:47.6120250Z) by Landsat 5, row 33, path 15. Cloud cover was 0 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331994091AAA02, LPGS_12.0.0, USGS, Sioux Falls, 2012-03-28T10:53:33Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1994-04-17
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1994-04-17 (15:06:28.6450940Z) by Landsat 5, row 33, path 15. Cloud cover was 30 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331994107XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T16:18:22Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1994-05-03
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1994-05-03 (15:06:10.9170380Z) by Landsat 5, row 33, path 15. Cloud cover was 40 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331994123XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-07-12T16:13:13Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1994-06-04
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1994-06-04 (15:05:35.9450750Z) by Landsat 5, row 33, path 15. Cloud cover was 0 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331994155XXX02, LPGS_12.0.2, USGS, Sioux Falls, 2012-05-30T18:40:15Z.
LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study collected on 1994-06-20
This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Baltimore Ecosystem Study, originally collected on 1994-06-20 (15:05:15.3350690Z) by Landsat 5, row 33, path 15. Cloud cover was 0 percent. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) software was originally developed by the National Aeronautics and Space Administration–Goddard Space Flight Center and the University of Maryland to produce top-of-atmosphere reflectance from Landsat Thematic Mapper and Enhanced Thematic Mapper Plus Level 1 digital numbers and to apply atmospheric corrections to generate a surface-reflectance product. The U.S. Geological Survey (USGS) has adopted the LEDAPS algorithm for producing the Landsat Surface Reflectance Climate Data Record. NASA Landsat Program, 2009, Landsat TM LT50150331994171XXX03, LPGS_12.0.2, USGS, Sioux Falls, 2012-05-30T18:38:58Z.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.