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1,709 results for “Reflectivity”
ABoVE: Angular-corrected MODIS MAIAC Reflectance across Alaska and Canada, 2000-2017
This dataset provides angular corrections of MODIS Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC) surface reflectances across the ABoVE domain in Alaska and western Canada from 2000 to 2017. Using random forests (RF), a machine-learning approach, the original MAIAC reflectance data were corrected to consistent view and illumination angles (0 degree view zenith angle and 45 degree of sun zenith angle) to reduce artifacts and variability due to angular effects. The original MAIAC data's sub-daily temporal resolution and 1 km spatial resolution with seven land bands (bands 1-7) and five ocean bands (bands 8-12) were preserved. The resulting surface reflectance data are suitable for long-term studies on patterns, processes, and dynamics of surface phenomena. The data cover 11 different Terra and Aqua satellite MODIS MAIAC tiles.
VIIRS/NPP Surface Reflectance Daily L3 Global 0.05Deg CMG V002
The Visible Infrared Imaging Radiometer Suite (VIIRS) daily surface reflectance Climate Modeling Grid (VNP09CMG) Version 2 product provides an estimate of land surface reflectance from the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) VIIRS sensor. Data are provided for three imagery bands (I1-I3) and nine moderate resolution bands (M1-M5, M7, M8, M10, M11) at 0.05 degree (~5,600 meter) resolution. The data are corrected for atmospheric conditions such as the effects of molecular gases, including ozone and water vapor, and for the effects of atmospheric aerosols. This product uses a weighted average of the best quality observation and is formatted as a CMG for use in climate simulation models. This product includes the twelve reflectance bands, five moderate resolution brightness temperature bands (M12-M16) and information layers representing relative azimuth angle, sensor zenith angle, solar zenith angle, reflectance band quality, time of day, and number mapping. Known Issues* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=VIIRS) and in Section 4.0 of the User Guide.Improvements/Changes from Previous Versions* Improved calibration algorithm and coefficients for entire Suomi NPP mission.* Improved geolocation accuracy and applied updates to fix outliers around maneuver periods.* Corrected the aerosol quantity flag (low, average, high) mainly over brighter surfaces in the mid- to high-latitudes such as desert and tropical vegetation areas. This has an impact on the retrieval of other downstream data products such as VNP13 Vegetation Indices and VNP43 Bidirectional Reflectance Distribution Function (BRDF)/Albedo.* Improved cloud mask input product for corrections along coastlines and artifacts from use of coarse resolution climatology data. * Replaced the land/water mask input product with the eight-class land/water mask from the VNP03 geolocation product that better aligns with MODIS.* Added secondary day-night flag to improve retrieval of Climate Modeling Grid (CMG) values over daytime pixels.* More details can be found in this [VIIRS Land V2 Changes document](https://landweb.modaps.eosdis.nasa.gov/data/userguide/VIIRS_Land_C2_Changes_09152022.pdf).
HLS Landsat Operational Land Imager Surface Reflectance and TOA Brightness Daily Global 30m v2.0
The Harmonized Landsat Sentinel-2 (HLS) project provides consistent surface reflectance (SR) and top of atmosphere (TOA) brightness data from a virtual constellation of satellite sensors. The Operational Land Imager (OLI) is housed aboard the joint NASA/USGS Landsat 8 and Landsat 9 satellites, while the Multi-Spectral Instrument (MSI) is mounted aboard Europe’s Copernicus Sentinel-2A, Sentinel-2B, and Sentinel-2C satellites. The combined measurement enables global observations of the land every 2–3 days at 30-meter (m) spatial resolution. The HLS project uses a set of algorithms to obtain seamless products from OLI and MSI that include atmospheric correction, cloud and cloud-shadow masking, spatial co-registration and common gridding, illumination and view angle normalization, and spectral bandpass adjustment.The HLSL30 product provides 30-m Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) and is derived from Landsat 8/9 OLI data products. The [HLSS30](https://doi.org/10.5067/HLS/HLSS30.002) and HLSL30 products are gridded to the same resolution and Military Grid Reference System ([MGRS](https://hls.gsfc.nasa.gov/products-description/tiling-system/)) tiling system and thus are “stackable” for time series analysis.The HLSL30 product is provided in Cloud Optimized GeoTIFF (COG) format, and each band is distributed as a separate file. There are 11 bands included in the HLSL30 product along with one quality assessment (QA) band and four angle bands. See the User Guide for a more detailed description of the individual bands provided in the HLSL30 product.Known Issues* Unrealistically high aerosol and low surface reflectance over bright areas: The atmospheric correction over bright targets occasionally retrieves unrealistically high aerosol and thus makes the surface reflectance too low. High aerosol retrievals, both false high aerosol and realistically high aerosol, are masked when quality bits 6 and 7 are both set to 1 (see Table 9 in the [User Guide](https://lpdaac.usgs.gov/documents/1698/HLS_User_Guide_V2.pdf)); the corresponding spectral data should be discarded from analysis.* Issues over high latitudes: For scenes greater than or equal to 80 degrees north, multiple overpasses can be gridded into a single MGRS tile resulting in an L30 granule with data sensed at two different times. In this same area, it is also possible that Landsat overpasses that should be gridded into a single MGRS tile are actually written as separate data files. Finally, for scenes with a latitude greater than or equal to 65 degrees north, ascending Landsat scenes may have a slightly higher error in the BRDF correction because the algorithm is calibrated using descending scenes.* Fmask omission errors: There are known issues regarding the Fmask band of this data product that impacts HLSL30 data prior to April of 2022. The HLS Fmask data band may have omission errors in water detection for cases where water detection using spectral data alone is difficult, and omission and commission errors in cloud shadow detection for areas with great topographic relief. This issue does not impact other bands in the dataset.* Inconsistent snow surface reflectance between Landsat and Sentinel-2: The HLS snow surface reflectance can be highly inconsistent between Landsat and Sentinel-2. When assessed on same-day acquisitions from Landsat and Sentinel-2, Landsat reflectance is generally higher than Sentinel-2 reflectance in the visible bands.* Unrealistically high snow surface reflectance in the visible bands: By design, the Land Surface Reflectance Code (LaSRC) atmospheric correction does not attempt aerosol retrieval over snow; instead, a default aerosol optical thickness (AOT) is used to drive the snow surface reflectance. If the snow detection fails, the full LaSRC is used in both AOT retrieval and surface reflectance derivation over snow, which produces surface reflectance values as high as 1.6 in the visible bands. This is a common problem for spring images at high latitudes.* Unrealistically low surface reflectance surrounding snow/ice: Related to the above, the AOT retrieval over snow/ice is generally too high. When this artificially high AOT is used to derive the surface reflectance of the neighboring non-snow pixels, very low surface reflectance will result. These pixels will appear very dark in the visible bands. If the surface reflectance value of a pixel is below -0.2, a NO_DATA value of -9999 is used.* Unrealistically low reflectance surrounding clouds: Like for snow, the HLS atmospheric correction does not attempt aerosol retrieval over clouds and a default AOT is used instead. But if the cloud detection fails, an artificially high AOT will be retrieved over clouds. If the high AOT is used to derive the surface reflectance of the neighboring cloud-free pixels, very low surface reflectance values will result. If the surface reflectance value of a pixel is below -0.2, a NO_DATA value of -9999 is used.
TOMS Earth-Probe Total Ozone (O3) Aerosol Index UV-Reflectivity UV-B Erythemal Irradiances Daily L3 Global 1 deg x 1.25 deg V008 (TOMSEPL3) at GES DISC
The Earth Probe (EP) Total Ozone Mapping Spectrometer (TOMS) version 8 daily global gridded data product contains total column ozone, UV aerosol index, Lambertian effective surface reflectivity (Rayleigh corrected), and UV-B erythemal local noon irradiances. The data are mapped to a global grid of size 180 x 288 with a lat-long resolution of 1.00 x 1.25 degrees. These data are stored in the EOS Hierarchical Data Format (HDF-EOS).The TOMS data were produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 614).
ASTER L2 Surface Reflectance VNIR and Crosstalk Corrected SWIR V003
The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Surface Reflectance VNIR and Crosstalk Corrected SWIR (AST_07XT) dataset contains measures of the fraction of incoming solar radiation reflected from the Earth's surface to the ASTER instrument corrected for atmospheric effects and viewing geometry for both the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) sensors. The AST_07XT product has a spatial resolution of 15 meters (m) for the VNIR bands and 30 m for the SWIR bands. Each product delivery includes two Hierarchical Data Format - Earth Observing System (HDF-EOS) files: one for the VNIR, and the other for the SWIR. They are distinguished from one another by a one-second difference in the production time that appears as part of the file name. Both the VNIR and SWIR data are atmospherically corrected and are generated using the bands of the corresponding [ASTER L1B](https://doi.org/10.5067/ASTER/AST_L1B.003) image.AST_07XT is a multi-file product that contains atmospherically corrected data for both the VNIR and SWIR sensors. The crosstalk corrected product no longer displays blurred images initiated by stray light that caused multiple reflections with the SWIR bands.The ASTER L2 Surface Reflectance VNIR and Crosstalk Corrected SWIR data product is only available through [NASA's Earthdata Search](https://search.earthdata.nasa.gov/search?q=C1299783608-LPDAAC_ECS). The ASTER Order Instructions provide step-by-step directions for ordering this product.Known Issues* SWIR Crosstalk Correction: The ASTER SWIR sensor is affected by a crosstalk signal scattering problem, a phenomenon discovered after the launch of ASTER aboard the Terra platform in December 1999. The SWIR detector contains 2048 Pt-Si (platinum-silicide) arrays for each of its six spectral bands. There are six pairs of staggered linear CCD arrays for each band that are spaced 1.33 µm apart in the band order 7, 8, 9, 4, 5, and 6. In front of each CCD array pair, there are interference filters that spectrally separate the radiation reflected from the Earth.* Data Anomalies: Users are advised that ASTER SWIR data acquired from April 2008 to the present exhibit anomalous saturation of values and anomalous striping. This effect is also present for some prior acquisition periods. Please refer to the ASTER SWIR User Advisory for more details.* Data acquisition gaps: On November 28, 2024, one of Terra's power-transmitting shunt units failed. As a result, there was insufficient power to maintain functionality of the ASTER instrument. ASTER resumed acquisitions for the VNIR bands on January 18, 2025, and for the TIR bands on April 15, 2025. Users should note the data gap in ASTER acquisitions from November 28, 2024, through January 16, 2025, for VNIR observations, and a gap from November 28, 2024, through April 15, 2025, for TIR acquisitions.Improvements/Changes from Previous Version* The Science Scalable Scripts-based Science Processor for Missions (S4PM) Version 3.4 algorithm, which is used to generate L2 Product Generation Executables (PGEs), is relying on a new ancillary input for atmospheric parameters. Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) is global atmospheric reanalysis that combines remote sensing observations and interactions with the climate system. It will be one of the primary ozone and water vapor, pressure, and temperature inputs for L2 PGEs. MERRA-2 will provide a finer geographic resolution grid since it is a 3-dimensional, 3-hourly data collection with 50-km (latitudinal direction) spatial resolution.* The fallback options for L2 PGEs are as follows: * Ozone: [TOVS Ozone (OZ_DLY ) > AURA Ozone Monitoring Instrument (AURAOMI) > Total Ozone Analysis from Stratospheric and Tropospheric (TOAST) > Earth Probe-Total Ozone Mapping Spectrometer (EPTOMS)] or [MERRA-2] > National Centers for Environmental Prediction (NCEP)/Global Data Assimilation System (GDAS) > Climatology * Water Vapor, Pressure, and Temperature: [MOD07_L2] or [MERRA-2] > NCEP/GDAS > Climatology* Caveat: The temporal range for MERRA-2 covers 1980 to present; however, there is latency of ~3 weeks after the end of a month. Hence, NCEP/GDAS > Climatology fallback sequence will be applied for on-demand requests that fall outside of MERRA-2's temporal range or if the data is not science grade.* Starting June 23, 2021, radiometric calibration coefficient Version 5 (RCC V5) will be applied to newly observed ASTER data and archived ASTER data products. Details regarding RCC V5 are described in the following journal article. * Tsuchida, S., Yamamoto, H., Kouyama, T., Obata, K., Sakuma, F., Tachikawa, T., Kamei, A., Arai, K., Czapla-Myers, J.S., Biggar, S.F., and Thome, K.J., 2020, Radiometric Degradation Curves for the ASTER VNIR Processing Using Vicarious and Lunar Calibrations: Remote Sensing, v. 12, no. 3, at https://doi.org/10.3390/rs12030427.* As of December 15, 2021, the LP DAAC
MODIS/Aqua Surface Reflectance 8-Day L3 Global 500m SIN Grid V061
The Moderate Resolition Imaging Spectroradiometer (MODIS) Aqua MYD09A1 Version 6.1 product provides an estimate of the surface spectral reflectance of Aqua MODIS Bands 1 through 7 corrected for atmospheric conditions such as gasses, aerosols, and Rayleigh scattering. Along with the seven 500 meter (m) reflectance bands are a quality layer and four observation bands. For each pixel, a value is selected from all the acquisitions within the 8-day composite period. The criteria for the pixel choice include cloud and solar zenith. When several acquisitions meet the criteria the pixel with the minimum channel 3 (blue) value is used.Known Issues* Prior to the Aqua MODIS launch, Band 6 exhibited several anomalous detectors. Band 6 performance degraded seriously after launch and presently a majority of the Band 6 detectors are non-functional. Science users should read and use the non-functional detector flags and decide for themselves the optimum manner to handle non-functional detector "gaps" for their products. For complete information please refer to the [MODIS Characterization Support Team (MCST) website](https://mcst.gsfc.nasa.gov/time-dependent-list-non-functional-or-noisy-detector).* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=Aqua&as=61).Improvments/Changes from Previous Version* The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017.* A polarization correction has been applied to the L1B Reflective Solar Bands (RSB).
Delta-X: AVIRIS-NG BRDF-Adjusted Surface Reflectance and Mosaics, MRD, LA, 2021, V3
This data provides AVIRIS-NG Bidirectional Reflectance Distribution Function (BRDF) and sunglint-corrected surface spectral reflectance images over the Atchafalaya and Terrebonne basins of the Mississippi River Delta (MRD) of coastal Louisiana, USA. Flights were acquired during the Spring and Fall 2021 deployments of the Delta-X campaign. The imagery was acquired by the Airborne Visible/Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG) from 2021-03-27 to 2021-04-06 and 2021-08-18 to 2021-09-25. Reflectance data are provided for each flight line. In addition, ten files of mosaicked flight lines, by time period and over four locations (labeled Terre, Atcha, TerreEast, and Bara), are included. Data are provided as binary ENVI image and header files. Only land pixels were corrected; mask files for the mosaic file coverage showing presence/absence of water and clouds are also included. For the Delta-X mission, these data serve to better understand rates of soil erosion, accretion, and creation in the delta system, with the goal of building better models of how river deltas will behave under relative sea level rise.
VIIRS/JPSS1 Surface Reflectance Daily L2G Global 1km and 500m SIN Grid NRT
The VJ109GA_NRT is a Near Real Time (NRT) VIIRS/JPSS1 Surface Reflectance Daily L2G Global 1km and 500m SIN Grid product. The VIIRS surface reflectance products are estimates of surface reflectance in each of the VIIRS reflective bands I1-I3, M1-M5, M7, M8, M10, and M11. VJ109GA is a Level-2G surface reflectance product produced on a 10km x 10km grid. The VNP09GA surface reflectance product is composed of all available surface reflectance observations for a given day over a set of tiles with global coverage. The tile numbering scheme and boundaries are the same as for MODIS. The first set of observations for each data set and grid cell are projected onto a two-dimensional grid and stored as 10km square tiles at 500m and 1 km resolution.Surface reflectance is obtained by adjusting top-of-atmosphere reflectance to compensate for atmospheric effects. Corrections are made for the effects of molecular gases, including ozone and water vapor, and for the effects of atmospheric aerosols. The inputs to the surface reflectance algorithm include top-of-atmosphere reflectance for the VIIRS visible bands (VJ102MOD, VJ102IMG), the VIIRS cloud mask and aerosol product , aerosol optical thickness, and atmospheric data obtained from a reanalysis (surface pressure, atmospheric precipitable water, and ozone concentration).All surface reflectance products are produced for daytime conditions only. The product is produced under all atmospheric conditions except for night and oceans. Pixels when not produced are replaced by fill values in the Level-2 and Level-2G products.For more information read Suomi-NPP VIIRS Surface Reflectance User's Guide at https://viirsland.gsfc.nasa.gov/PDF/VIIRS_Surf_Refl_UserGuide_v2.0.pdfor visit VIIRS Land website at https://viirsland.gsfc.nasa.gov/Products/NASA/ReflectanceESDR.html
MODIS/Terra Atmospherically Corrected Surface Reflectance 5-Min L2 Swath 250m, 500m, 1km
The MODIS/Terra Atmospherically Corrected Surface Reflectance 5-Min L2 Swath 250m, 500m, 1km (MOD09) product is computed from the MODIS Level 1B land bands 1, 2, 3, 4, 5, 6, and 7 (centered at 648 nm, 858 nm, 470 nm, 555 nm, 1240 nm, 1640 nm, and 2130 nm, respectively). The product is an estimate of the surface spectral reflectance for each band as it would have been measured at ground level if there were no atmospheric scattering or absorption. The surface-reflectance product is the input for product generation for several land products: vegetation Indices (VIs), Bidirectional Reflectance Distribution Function (BRDF), thermal anomaly, snow/ice, and Fraction of Photosynthetically Active Radiation/Leaf Area Index (FPAR/LAI).
CLPX-Satellite: MODIS Radiances, Reflectances, Snow Cover and Related Grids, Version 1
This data set provides Moderate Resolution Imaging Spectroradiometer (MODIS) data as part of the Cold Land Processes Field Experiment (CLPX). Parameters include radiances, surface reflectance, snow cover, land surface temperature/emissivity, and vegetation indices.
SE-590 Field-Meas. Reflectances (OTTER)
Spectral reflectance measurements made by Spectron SE590 instruments in the context of validation of geometric-optical BRDF models.
ASTER L2 Surface Reflectance SWIR and ASTER L2 Surface Reflectance VNIR V003
The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Surface Reflectance VNIR and SWIR (AST_07) data product contains measures of the fraction of incoming solar radiation reflected from the Earth's surface to the ASTER instrument corrected for atmospheric effects and viewing geometry for both the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) sensors. The AST_07 product has a spatial resolution of 15 meters (m) for the VNIR bands and 30 m for the SWIR bands. Each product delivery includes two Hierarchical Data Format - Earth Observing System (HDF-EOS) files: one for the VNIR, and the other for the SWIR. They are distinguished from one another by a one-second difference in the production time that appears as part of the file name. The ASTER L2 Surface Reflectance VNIR and SWIR data product is only available through [NASA's Earthdata Search](https://search.earthdata.nasa.gov/search?q=C1299783800-LPDAAC_ECS). The ASTER Order Instructions provide step-by-step directions for ordering this product.Known Issues* Data Anomalies: Users are advised that ASTER SWIR data acquired from April 2008 to the present exhibit anomalous saturation of values and anomalous striping. This effect is also present for some prior acquisition periods. Please refer to the ASTER SWIR User Advisory for more details.* Data acquisition gaps: On November 28, 2024, one of Terra's power-transmitting shunt units failed. As a result, there was insufficient power to maintain functionality of the ASTER instrument. ASTER resumed acquisitions for the VNIR bands on January 18, 2025, and for the TIR bands on April 15, 2025. Users should note the data gap in ASTER acquisitions from November 28, 2024, through January 16, 2025, for VNIR observations, and a gap from November 28, 2024, through April 15, 2025, for TIR acquisitions.Improvements/Changes from Previous Version* The Science Scalable Scripts-based Science Processor for Missions (S4PM) Version 3.4 algorithm, which is used to generate L2 Product Generation Executables (PGEs), is relying on a new ancillary input for atmospheric parameters. Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) is global atmospheric reanalysis that combines remote sensing observations and interactions with the climate system. It will be one of the primary ozone and water vapor, pressure, and temperature inputs for L2 PGEs. MERRA-2 will provide a finer geographic resolution grid since it is a 3-dimensional, 3-hourly data collection with 50-km (latitudinal direction) spatial resolution.* The fallback options for L2 PGEs are as follows: * Ozone: [TOVS Ozone (OZ_DLY ) > AURA Ozone Monitoring Instrument (AURAOMI) > Total Ozone Analysis from Stratospheric and Tropospheric (TOAST) > Earth Probe-Total Ozone Mapping Spectrometer (EPTOMS)] or [MERRA-2] > National Centers for Environmental Prediction (NCEP)/Global Data Assimilation System (GDAS) > Climatology * Water Vapor, Pressure, and Temperature: [MOD07_L2] or [MERRA-2] > NCEP/GDAS > Climatology* Caveat: The temporal range for MERRA-2 covers 1980 to present; however, there is latency of ~3 weeks after the end of a month. Hence, NCEP/GDAS > Climatology fallback sequence will be applied for on-demand requests that fall outside of MERRA-2's temporal range or if the data is not science grade.* Starting June 23, 2021, radiometric calibration coefficient Version 5 (RCC V5) will be applied to newly observed ASTER data and archived ASTER data products. Details regarding RCC V5 are described in the following journal article. * Tsuchida, S., Yamamoto, H., Kouyama, T., Obata, K., Sakuma, F., Tachikawa, T., Kamei, A., Arai, K., Czapla-Myers, J.S., Biggar, S.F., and Thome, K.J., 2020, Radiometric Degradation Curves for the ASTER VNIR Processing Using Vicarious and Lunar Calibrations: Remote Sensing, v. 12, no. 3, at [https://doi.org/10.3390/rs12030427](https://doi.org/10.3390/rs12030427).* As of December 15, 2021, the LP DAAC has implemented changes to ASTER PGE Version 3.4, which will affect all ASTER Level 2 on-demand products. Changes include: * Aura Ozone Monitoring Instrument (OMI) has been added as one of the ancillary ozone inputs for any observations made after May 27, 2020. The sequence of fallbacks for ozone will remain the same. * Toolkit has been updated from Version 5.2.17 to 5.2.20. Users may notice minor differences between the two versions. Differences may include minuscule changes in digital numbers around the peripheral of the granule and boundaries of a cloud for Surface Reflectance and Surface Radiance (AST07 and AST09) QA Data Plane depending on the Operating System and libraries being used by the user to process the data.*Additionally, Climatology, which is one of the inputs for Ozone and Moisture, Temperature and Pressures (MTP) will be removed from the Earthdata Order Form. It has been observed that PGEs generated with Climatology as an input yield noticeable differ
MODIS/Aqua Surface Reflectance Daily L2G Global 1km and 500m SIN Grid V061
The MYD09GA Version 6.1 product provides an estimate of the surface spectral reflectance of Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Bands 1 through 7, corrected for atmospheric conditions such as gasses, aerosols, and Rayleigh scattering. Provided along with the 500 meter (m) surface reflectance, observation, and quality bands are a set of ten 1 kilometer observation bands and geolocation flags. The reflectance layers from the MYD09GA are used as the source data for many of the MODIS land products. Known Issues* Prior to the Aqua MODIS launch, Band 6 exhibited several anomalous detectors. Band 6 performance degraded seriously after launch and presently a majority of the Band 6 detectors are non-functional. Science users should read and use the non-functional detector flags and decide for themselves the optimum manner to handle non-functional detector "gaps" for their products. For complete information please refer to the [MODIS Characterization Support Team (MCST) website](https://mcst.gsfc.nasa.gov/time-dependent-list-non-functional-or-noisy-detector).* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=Aqua&as=61).Improvments/Changes from Previous Version* The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017.* A polarization correction has been applied to the L1B Reflective Solar Bands (RSB).
VIIRS/JPSS1 Atmospherically Corrected Surface Reflectance 6-Min L2 Swath 375m, 750m
The VIIRS/JPSS1 Atmospherically Corrected Surface Reflectance 6-Min L2 Swath 375m, 750m product, with short name VJ109, are estimates of surface reflectance in each of the Visible Infrared Imaging Radiometer Suite (VIIRS) reflective bands I1-I3, M1-M5, M7, M8, M10, and M11. The VJ109 contains approximately 6 minutes' worth of data. Surface reflectance for each moderate-resolution (750m) or imagery-resolution (375m) pixel is retrieved separately for the Level-2 products. Surface reflectance is obtained by adjusting top-of-atmosphere reflectance to compensate for atmospheric effects. Corrections are made for the effects of molecular gases, including ozone and water vapor, and for the effects of atmospheric aerosols. All surface reflectance products are produced for daytime conditions only. The product is produced under all atmospheric conditions except for night and oceans.
MODIS/Terra Surface Reflectance Daily L2G Global 250m SIN Grid V006
The MOD09GQ Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the [MOD09GQ Version 6.1](https://doi.org/10.5067/MODIS/MOD09GQ.061) data product.The MOD09GQ Version 6 product provides an estimate of the surface spectral reflectance of Terra Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter (m) bands 1 and 2, corrected for atmospheric conditions such as gasses, aerosols, and Rayleigh scattering. Along with the 250 m surface reflectance bands are the Quality Assurance (QA) layer and five observation layers. This product is intended to be used in conjunction with the quality and viewing geometry information of the 500 m product (MOD09GA). Known Issues* Striping due to a dead detector is noticeable for bands 5, 6, and 7 in scenes acquired February 24 through October 31, 2000. Corrections were implemented to reduce the striping in data acquired after November 1, 2000. Users should always check the band quality for dead detectors even though reflectance values may be in the valid range. * The Collection 6 MODIS Land Surface Reflectance product (MOD09) may [incorrectly flag retrievals as ‘High Aerosol’](https://landweb.modaps.eosdis.nasa.gov/displayissue?id=86) over brighter surfaces and at higher view angles. This will impact the downstream MODIS BRDF/Albedo (MCD43) and Vegetation Index (MOD13 and MYD13) data products which use the aerosol quantity flag to screen out high aerosol values.* [Corrections](https://landweb.modaps.eosdis.nasa.gov/data/userguide/LSRHighAerosolFlagFinal.pdf) were implemented in Collection 6.1 reprocessing.* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=Terra&as=6).Improvements/Changes from Previous Versions* Improvements to the aerosol retrieval and correction algorithm along with new aerosol retrieval look-up tables.* Refinements to the internal snow, cloud, and cloud shadow detection algorithms. Uses Bidirectional Reflectance Distribution Function (BRDF) database to better constrain the different threshold used.* Processes ocean bands to create a new Surface Reflectance Ocean product and provides Quality Assurance (QA) datasets for these bands.* Improved discrimination of salt pans from cloud and snow, along with the inclusion of a salt pan flag in the QA band.
GPM PR on TRMM Reflectivity, Precipitation Statistics, Histograms, at Surface and Fixed Heights, Descending, 1 day 5x5 and 0.25x0.25 degree V07 (GPM_3PR_DES) at GES DISC
This a new (GPM-formated) TRMM product. There is no equivalent in the old TRMM suite of products.Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.This product consists of Descending daily statistics of the PR measurements at both a low (5 degrees x 5 degrees) and a high (0.25 degrees x 0.25 degrees) horizontal resolution. The low resolution grids are in the Planetary Grid 1 structure and include 1) mean and standard deviation of the rain rate, reflectivity, path-integrated attenuation (PIA), storm height, Xi, bright band height and the NUBF (Non-Uniform Beam Filling) correction; 2) rain fractions; 3) histograms of the storm height, bright-band height, snow-ice layer, reflectivity, rain rate, path-attenuation and NUBF correction; 4) correlation coefficients. The high resolution grids are in the Planetary Grid 2 structure and contain mean rain rate along with standard deviation and rain fractions.The grids are in the Planetary Grid 2 structure matching the Dual-frequency PR on the core GPM observatory that covers 67S to 67N degrees of latitudes. The low resolution 5x5 deg grid covers 70S to 70N. Areas beyond the ±40 degrees of latitudes are padded with empty grid cells.
LPJ-PROSAIL L2 Global Simulated Dynamic Surface Reflectance V001
[LPJ-PROSAIL](https://www.greencurrey.com/lpj-prosail) simulated data products are produced through the coupling of the Lund-Potsdam-Jena dynamic global vegetation model (LPJ) and PROSAIL, a radiative transfer model. The simulated imaging spectroscopy data were produced to aid in the development of workflows, algorithm testing, and other activities during the lead up to future global spaceborne imaging spectroscopy missions such as NASA’s Surface Biology and Geology ([SBG](https://sbg.jpl.nasa.gov/)). The LPJ-PROSAIL Level 2 Global Simulated Dynamic Surface Reflectance (LPJ_L2_SSREF) Version 1 data product provides simulated dynamic surface reflectance data in five Network Common Data Format 4 (netCDF4) files, each containing a different reflectance stream at a spatial resolution of 0.5 degrees (~50 kilometers): bidirectional (BDR), bi-hemispherical (BHR), hemispherical-directional (HDR), directional-hemispherical (DHR), and directional (DR). Each reflectance file within a granule contains simulated surface reflectance measurements of 211 bands with 10 nanometer (nm) spectral resolution across a spectral range of 400 to 2500 nm for the entire globe. The data are presented with four dimensions: latitude, longitude, bands (wavelength), and time. Each netCDF4 file holds a one-dimensional list for each of the four dimensions containing the values that are associated with those dimensions. LPJ_L2_SSREF Version 1 is composed of one granule containing data for the year 2020 with monthly time increments. Known Issues* Data Usage Warning: These data are meant to be used in development of workflows, algorithms, and other instances where large imaging spectroscopy datasets are needed for testing. Due to the simulated nature of these data, these data are not intended for scientific use and should not be used for any real-world scientific analyses or conclusions.
Soil Reflectance Data (FIFE)
Soil reflectance properties are an important factor in determining landscape reflectance characteristics. No soil reflectance data were collected as part of the FIFE experiment. Therefore, the FIS staff choose spectra from soils similar to those in the FIFE study area from the atlas of soil reflectance properties (Stoner et al., 1980). The atlas represents a wide range of soil types, and FIS staff choose spectra from soils similar to those in the FIFE study area. The selection of spectra was based on soil particle size, organic carbon content, taxonomic classification, and geography of soils found in the FIFE study area. All measurements were made on uniformly moist, sieved soils, which were equilibrated for 24 hours at a one-tenth bar moisture tension. Soil reflectance was measured using an Exotech Model 20 C spectroradiometer adapted for indoor use with a reflectometer equipped with an artificial illumination source, transfer optics, and sample stage. Spectral readings were taken in 0.01 micrometer increments over the 0.52 to 2.32 micrometer wavelength range.
Progressive dosage compensation during Drosophila embryogenesis is reflected by gene arrangement on the X chromosome [ChIP-seq]
GEO Series GSE127175. Drosophila melanogaster. 42 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
HIF regulatory network reflects kidney disease progression in diabetes and reversal with SGLT2 inhibition
GEO Series GSE317226. Homo sapiens. 4 samples. Type: Other.
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.