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1,605 results for “1995”

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edi36/100

Stream Gauge Measurements During 1995 Tracer Experiment

As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a 1995 tracer This dataset shows the stream discharges, conductivity, and water temperatures that occurred during this experiment.

openOpenJan 2020View details →
edi36/100

Small Mammal Exclosure Study (SMES) Rabbit Feces Data from Chihuahuan Desert Grassland and Shrubland at the Sevilleta National Wildlife Refuge, New Mexico (1995-2005)

The purpose of this study is to determine whether or not the activities of small mammals regulate plant community structure, plant species diversity, and spatial vegetation patterns in Chihuahuan Desert shrublands and grasslands. What role if any do indigenous small mammal consumers have in maintaining desertified landscapes in the Chihuahuan Desert? Additionally, how do the effects of small mammals interact with changing climate to affect vegetation patterns over time? This is data for numbers rabbit fecal pellets counted on each of the Small Mammal Exclosure Study (SMES) plots. Rabbit fecal pellets were counted from each of the 36 one-meter2 quadrats twice each year when vegetation was measured.

openOpenMar 2016View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe collected on 1995-04-18

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe, originally collected on 1995-04-18 (16:46:05.7110690Z) by Landsat 5, row 032, path 033. 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 LT50330321995108AAA01, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T08:08:12Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe collected on 1995-05-04

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe, originally collected on 1995-05-04 (16:45:23.0900190Z) by Landsat 5, row 032, path 033. 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 LT50330321995124XXX01, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T08:08:30Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe collected on 1995-06-05

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe, originally collected on 1995-06-05 (16:43:54.8330560Z) by Landsat 5, row 032, path 033. 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 LT50330321995156XXX02, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T08:14:56Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe collected on 1995-06-21

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe, originally collected on 1995-06-21 (16:43:12.6130750Z) by Landsat 5, row 032, path 033. 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 LT50330321995172XXX03, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T08:07:52Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe collected on 1995-07-07

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe, originally collected on 1995-07-07 (16:42:28.8000630Z) by Landsat 5, row 032, path 033. 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 LT50330321995188AAA01, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T08:07:22Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe collected on 1995-07-23

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe, originally collected on 1995-07-23 (16:41:45.1910190Z) by Landsat 5, row 032, path 033. 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 LT50330321995204XXX00, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T08:10:00Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe collected on 1995-08-08

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe, originally collected on 1995-08-08 (16:41:01.4620310Z) by Landsat 5, row 032, path 033. 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 LT50330321995220XXX02, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T08:09:41Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe collected on 1995-08-24

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe, originally collected on 1995-08-24 (16:40:16.9560060Z) by Landsat 5, row 032, path 033. 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 LT50330321995236XXX02, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T08:09:10Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe collected on 1995-09-25

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe, originally collected on 1995-09-25 (16:38:43.3260060Z) by Landsat 5, row 032, path 033. 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 LT50330321995268AAA01, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T08:19:54Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe collected on 1995-10-11

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe, originally collected on 1995-10-11 (16:37:52.7230130Z) by Landsat 5, row 032, path 033. 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 LT50330321995284XXX02, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T08:17:03Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe collected on 1995-12-14

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Shortgrass Steppe, originally collected on 1995-12-14 (16:38:18.8190630Z) by Landsat 5, row 032, path 033. 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 LT50330321995348XXX01, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T08:13:22Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Virginia Coast Reserve LTER collected on 1995-01-23

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Virginia Coast Reserve LTER, originally collected on 1995-01-23 (14:52:55.5450880Z) by Landsat 5, row 034, path 014. 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 LT50140341995023XXX01, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T06:02:51Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Virginia Coast Reserve LTER collected on 1995-02-08

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Virginia Coast Reserve LTER, originally collected on 1995-02-08 (14:52:17.4420060Z) by Landsat 5, row 034, path 014. Cloud cover was 50 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 LT50140341995039XXX01, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T05:51:00Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Virginia Coast Reserve LTER collected on 1995-02-24

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Virginia Coast Reserve LTER, originally collected on 1995-02-24 (14:51:39.5870560Z) by Landsat 5, row 034, path 014. 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 LT50140341995055XXX01, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T05:56:26Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Virginia Coast Reserve LTER collected on 1995-03-12

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Virginia Coast Reserve LTER, originally collected on 1995-03-12 (14:51:00.7950500Z) by Landsat 5, row 034, path 014. 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 LT50140341995071XXX01, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T05:51:37Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Virginia Coast Reserve LTER collected on 1995-04-13

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Virginia Coast Reserve LTER, originally collected on 1995-04-13 (14:49:40.8750130Z) by Landsat 5, row 034, path 014. 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 LT50140341995103XXX01, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T05:32:50Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Virginia Coast Reserve LTER collected on 1995-04-29

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Virginia Coast Reserve LTER, originally collected on 1995-04-29 (14:48:58.8390130Z) by Landsat 5, row 034, path 014. 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 LT50140341995119XXX01, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T06:05:43Z.

openOpenJan 2020View details →
edi36/100

LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Virginia Coast Reserve LTER collected on 1995-05-15

This LTER Remote Sensing spatial raster dataset consists of LEDAPS corrected Landsat Enhanced Thematic Mapper image data for Virginia Coast Reserve LTER, originally collected on 1995-05-15 (14:48:15.6520250Z) by Landsat 5, row 034, path 014. 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 LT50140341995135XXX01, LPGS_12.1.3, USGS, Sioux Falls, 2012-12-22T06:15:03Z.

openOpenJan 2020View details →

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record