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37 results for “Thermal anomaly”
Dataset of Hyperspectral Melt Pool Signatures and Thermal Anomalies in DED of 316L steel
<p><strong>Description of the dataset</strong><br>The dataset includes in-situ melt pool signatures (hyperspectral NIR images) during the Directed Energy Deposition of 316L steel for several classes of thermal anomalies. Thermal anomalies were created during the process by varying the scanning speed.</p> <p>Samples were printed on the MiCLAD machine at the Vrije Universiteit Brussel (Belgium).</p> <p>Process and acquisition parameters:</p> <ul> <li>Hardware: <ul> <li>Machine: MiCLAD (Vrije Universiteit Brussel)</li> <li>Laser: High-YAG BIMO 1064nm, 2.55mm fibre, flat-top</li> <li>Nozzle: Harald-Dickler HighNo 4.0</li> </ul> </li> <li>Process parameters: <ul> <li>Laser power: 600 W</li> <li>Scanning speed: 500/700/900/1100/1300 mm/min</li> <li>Powder: 316L 45-105 um</li> <li>Powder flow rate: 3.5 g/m</li> <li>Layer thickness: 0.2 mm</li> </ul> </li> <li>Image characteristics: <ul> <li>Camera: 3D-One Avior AX-M25NIR</li> <li>Hyperspectral filter layout: 5x5 (25 wavelengths per image)</li> </ul> </li> </ul> <p><strong>Description of the files</strong></p> <ul> <li>CSV dataset (hyperspectral_nir_meltpool_dataset.csv): List of filename, sample, label, time (ms), X and Z position (mm) and local scanning speed (mm/min) for all melt pool signatures. Thermal anomalies are labelled accordingly: <ul> <li>0 : baseline</li> <li>1 : edge</li> <li>2 : underheat</li> <li>3 : strong underheat</li> <li>4 : overheat</li> <li>5 : strong overheat</li> </ul> </li> <li>Melt pool signatures (hyperspectral_nir_meltpool_images_*.zip): Raw .tif thermal images of the melt pool taken in-situ. The raw images must debayered to retrieve the spectral information, see the Python function and example script. </li> <li>Python debayer function (debayer.py): Debayering function to retrieve the spectral information from the raw images. </li> </ul>
A Google Earth Engine code to analyze residential buildings' real estate values, summer surface thermal anomaly patterns and urban features: a Florence (Italy) case study
<ol> </ol> <p>The layers included in the code were from the study conducted by the research group of CNR-IBE (Institute of BioEconomy of the National Research Council of Italy) and ISPRA (Italian National Institute for Environmental Protection and Research), published by the Sustainability journal (<strong>https://doi.org/10.3390/su14148412</strong>).</p> <p>Link to the <strong>Google Earth Engine (GEE) code</strong> <strong>(link: <a href="https://code.earthengine.google.com/715aa44e13b3640b5f6370165edd3002">https://code.earthengine.google.com/715aa44e13b3640b5f6370165edd3002</a></strong>)</p> <p>You can analyze and visualize the following spatial layers by accessing the GEE link: </p> <ol> <li><strong>Daytime summer land surface temperature</strong> (raster data, horizontal resolution 30 m, from Landsat-8 remote sensing data, years 2015-2019)</li> <li><strong>Surface thermal hot-spot </strong>(raster data, horizontal resolution 30 m) was obtained by using a statistical-spatial method based on the Getis-Ord Gi* approach through the ArcGIS Pro tool.</li> <li><strong>Surface albedo</strong> (raster data, horizontal resolution 10 m, Sentinel-2A remote sensing data, year 2017)</li> <li><strong>Impervious area</strong> (raster data, horizontal resolution 10 m, ISPRA data, year 2017)</li> <li><strong>Tree cover</strong> (raster data, horizontal resolution 10 m, ISPRA data, year 2018)</li> <li><strong>Grassland area</strong> (raster data, horizontal resolution 10 m, ISPRA data, year 2017)</li> <li><strong>Water bodies</strong> (raster data, horizontal resolution 2 m, Geoscopio Platform of Tuscany, year 2016)</li> <li><strong>Sky View Factor</strong> (raster data, horizontal resolution 1 m, lidar data from the OpenData platform of Florence, year 2016)</li> <li><strong>Buildings' units</strong> of Florence (shapefile from the OpenData platform of Florence) include data on the residential real estate value from the Real Estate Market Observatory (OMI) of the National Revenue Agency of Italy (source: https://www1.agenziaentrate.gov.it/servizi/Consultazione/ricerca.htm, accessed on 14 July 2022). Data on the characterization of the buffer area (50 m) surrounding the buildings are included in this shapefile [the names of table attributes are reported in the square brackets]: averaged values of the daytime summer land surface temperature [LST_media], thermal hot-spot pattern [Thermal_cl], mean values of sky view factor [SVF_medio], surface albedo [alb_medio], and average percentage areas of imperviousness [ImperArea%], tree cover [TreeArea%], grassland [GrassArea%] and water bodies [WaterArea%]. </li> </ol> <p>Here attached the .txt file of the <strong>GEE code</strong>. </p> <p> </p> <p><em>E-mail</em></p> <p>Giulia Guerri, CNR-IBE, giulia.guerri@ibe.cnr.it</p> <p>Marco Morabito, CNR-IBE, marco.morabito@cnr.it</p> <p>Alfonso Crisci, CNR-IBE, alfonso.crisci@ibe.cnr.it</p>
Dataset used in the study "Residential buildings real estate values linked to summer surface thermal anomaly patterns and urban features: the Florence (Italy) case study."
<p>This dataset repository includes eight raster layers (Reference System EPSG:3035 - ETRS89-extended / LAEA Europe), used in the study "Residential buildings real estate values linked to summer surface thermal anomaly patterns and urban features: the Florence (Italy) case study", and obtained by the adaptation of analyses carried out by previous studies (Morabito et al., 2021; Guerri et al., 2021; 2022).</p> <p>Further information regarding the source, study period, and horizontal resolution is available in the attached text file. </p> <p> </p> <p><strong><em>References</em></strong></p> <p>Guerri, G., Crisci, A., Congedo, L., Munafò, M., Morabito, M., <strong>2022</strong>. A functional seasonal thermal hot-spot classification: Focus on industrial sites. Science of The Total Environment 806, 151383.<a href="http://https://doi.org/10.1016/j.scitotenv.2021.151383"> https://doi.org/10.1016/j.scitotenv.2021.151383</a>.</p> <p>Guerri, G., Crisci, A., Messeri, A., Congedo, L., Munafò, M., Morabito, M., <strong>2021</strong>. Thermal Summer Diurnal Hot-Spot Analysis: The Role of Local Urban Features Layers. Remote Sensing 13, 538. <a href="https://doi.org/10.3390/rs13030538">https://doi.org/10.3390/rs13030538</a>.</p> <p>Morabito, M., Crisci, A., Guerri, G., Messeri, A., Congedo, L., Munafò, M., <strong>2021</strong>. Surface Urban Heat Islands in Italian Metropolitan Cities: Tree Cover and Impervious Surface Influences. Science of The Total Environment 751, 142334. <a href="https://doi.org/10.1016/j.scitotenv.2020.142334">https://doi.org/10.1016/j.scitotenv.2020.142334</a>.</p>
E-THEMIS Thermal Anomaly Simulation Observations
<p>This dataset contains 100,000 simulated observations of Europa with the E-THEMIS instrument. Each observation was generated by randomly selecting (1) one of 46 planned Europa flybys by the Europa Clipper from the 17F12_V2 trajectory and (2) the distance of the spacecraft to Europa (±50,000 km from closest approach). We used the KRC thermal model to simulate the Europa surface temperature as a function of latitude, longitude, and local solar time (Sun position). We simulated the appearance of Europa within the E-THEMIS field of view given the Europa radius of 1591 km. We used ray tracing to determine, given the surface temperature model and the relative positions of Europa and the spacecraft, the amount of thermal radiation from Europa that a given pixel would collect. We used Monte Carlo integration over 100 uniformly random sub-pixel locations within each pixel.</p> <p>We injected artificial thermal anomalies into the simulated Europa observations by selecting a random radius between 1 m and 25 km and random temperature between 75 K and 275 K, then modifying the modeled surface temperature. We used an instrument model that converts temperature to digital numbers to generate the final E-THEMIS data product.</p> <p>The ethemis_dn_to_temp.npz file contains the mapping from digital number to temperature in each of the three E-THEMIS bands. Each observation is also a <a href="https://docs.scipy.org/doc/numpy/reference/generated/numpy.lib.format.html#module-numpy.lib.format">NPY-formatted</a> file containing the following entries:</p> <ul> <li>event_time: the simulated time at which the observation was acquired</li> <li>trial: the trial identifier (should match the file name)</li> <li>samples: the number of samples used in the Monte Carlo integration</li> <li>anomaly_radius_m: the (circular) anomaly radius in meters</li> <li>temperature: the temperature of the anomaly</li> <li>band1_dn: the digital number for each pixel in the observation (similar entries exist for the other bands)</li> <li>band1_mask: a mask specifying the fraction of each pixel containing an anomaly (similar entries exist for the other bands)</li> </ul> <p>The extracted dataset is roughly 18 Gb in size.</p>
Climate (thermal anomalies) and dengue incidence in Brazil aggregated by microregions (MRG)
<p>Climate (thermal anomalies) and dengue incidence in Brazil aggregated by microregions (MRG). The frequency of temperature anomalies wee calculated between 2007 and 2020. Dengue disease notification frequency were aggregated by MRG and divided by population to create incidence rates between 2007 and 2020.</p>
Data Tables and figures for "Quantification of 3D thermal anomalies from surface observations of an orogenic geothermal system (Grimsel Pass, Swiss Alps)"
<p>Tables and figures containing the data used in the manuscript called</p> <p><strong>"Quantification of 3D thermal anomalies from surface observations of an orogenic geothermal system (Grimsel Pass, Swiss Alps)", </strong></p> <p>which was submitted to JGR:Solid Earth</p>
MODIS/Aqua Thermal Anomalies/Fire Daily L3 Global 1km SIN Grid V006
The MYD14A1 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the [MYD14A1 Version 6.1](https://doi.org/10.5067/MODIS/MYD14A1.061) data product.The Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire Daily (MYD14A1) Version 6 data are generated every eight days at 1 kilometer (km) spatial resolution as a Level 3 product. MYD14A1 contains eight consecutive days of fire data conveniently packaged into a single file.The Science Dataset (SDS) layers include the fire mask, pixel quality indicators, maximum fire-radiative-power (MaxFRP), and the position of the fire pixel within the scan. Each layer consists of daily per pixel information for each of the eight days of data acquisition. Known Issues* Known issues are described on the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=Aqua&as=6) and in Section 7.2 of the User Guide which covers Pre-November 2000 Data Quality, Detection Confidence, Flagging of Static Sources, and the August 2020 MODIS Aqua Outage.Improvements/Changes from Previous Versions* Refinements to internal cloud mask, which sometimes flags heavy smoke as clouds.* Fix for frequent false alarms occurring in the Amazon that are caused by small (~1 km²) clearings within forests. * Fix to correct a bug that causes incorrect assessment of cloud and water pixels adjacent to fire pixels near the scan edge.* Detect small fires using dynamic thresholding.* Process ocean and coastline pixels to detect fire from oil rigs.* The Version 6 fire mask has the potential to detect fire over water pixels. Therefore, class 3 pixel values have been changed to be classified as “non-fire water pixels”.
MODIS/Terra Thermal Anomalies/Fire 5-Min L2 Swath 1km V006
The MOD14 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the [MOD14 Version 6.1](https://doi.org/10.5067/MODIS/MOD14.061) data product.The Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire MOD14 Version 6 product is produced daily in 5-minute temporal satellite increments (swaths). The MOD14 product is used to generate all of the higher level fire products, but can also be used to identify fires and other thermal anomalies, such as volcanoes. Each swath of data is approximately 2,030 kilometers along track (long), and 2,300 kilometers across track (wide). Known Issues* Known issues are described on the [MODIS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=Terra&as=6) and in Section 7.2 of the User Guide which covers Pre-November 2000 Data Quality, Detection Confidence, Flagging of Static Sources, and the August 2020 MODIS Aqua OutageImprovements/Changes from Previous Versions* Refinements to internal cloud mask, which sometimes flags heavy smoke as clouds.* Fix for frequent false alarms occurring in the Amazon that are caused by small (~1 km²) clearings within forests. * Fix to correct a bug that causes incorrect assessment of cloud and water pixels adjacent to fire pixels near the scan edge.* Detect small fires using dynamic thresholding.* Process ocean and coastline pixels to detect fire from oil rigs.* The Version 6 fire mask has the potential to detect fire over water pixels. Therefore, class 3 pixel values have been changed to be classified as “non-fire water pixels”.
VIIRS/NPP Thermal Anomalies/Fire 6-Min L2 Swath 750m NRT - V2
The VIIRS/NPP Thermal Anomalies/Fire 6-Min L2 Swath 750m NRT product, short-name VNP14_NRT is based on the MODIS Fire algorithm. The input to the Active Fires production are Level-1B moderate-resolution reflective band M7, and emissive bands M13 and M15. The fire algorithm first calculates bands M13, M15 brightness temperature (BT) statistics for a group of background pixels adjacent to each potential fire pixel. These statistics are used to set thresholds for several contextual fire detection tests. There is also an absolute fire detection test based on a pre-set M13 BT threshold. If the results of the absolute and relative fire detection tests meet certain criteria, the pixel is labeled as fire. The designation of a pixel as fire from the results of the BT threshold tests may be overridden under sun glint conditions or if too few pixels were used to calculate the background statistics.The VNP14_NRT product contains several pieces of information for each fire pixel: pixel coordinates, latitude and longitude, pixel M7 reflectance, background M7 reflectance, pixel M13 and M15 BT, background M13 and M15 BT, mean background BT difference, background M13, M15, and BT difference mean absolute deviation, fire radiative power, number of adjacent cloud pixels, number of adjacent water pixels, background window size, number of valid background pixels, detection confidence, land pixel flag, background M7 reflectance, and reflectance mean absolute deviation.The product provides day and nighttime active fire detection over land and water (from gas flares). The VNP14 product provides fire data continuity with NASA's EOS MODIS 1 km fire product. For more information visit University of Maryland VIIRS Active Fire Web page at http://viirsfire.geog.umd.edu/
VIIRS/NPP Thermal Anomalies/Fire 6-Min L2 Swath 750m V001
The VNP14 VIIRS Version 1 data product was decommissioned on April 8th, 2025. Users are encouraged to use Version 2 data products, which provide [better calibration and consistency](https://landweb.modaps.eosdis.nasa.gov/data/userguide/VIIRS_Land_C2_Changes_09152022.pdf) for the end user. VIIRS Version 2 data products are available from both the SNPP ([VNP14](https://doi.org/10.5067/VIIRS/VNP14.002)) and NOAA-20 ([VJ114]( https://doi.org/10.5067/VIIRS/VJ114.002)) satellites.The Visible Infrared Imaging Radiometer Suite (VIIRS) Thermal Anomalies (VNP14) Version 1 product is produced in 6-minute temporal satellite increments (swaths) at 750 meter resolution from the VIIRS sensor located on the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) satellite. This product is designed after the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire data products to promote the continuity of the Earth Observation System (EOS) mission. This data product can enable users to understand the location and intensity of fire events as well as identifying thermal anomalies. The VNP14 product includes 31 science dataset layers to analyze key factors in fire detection, including atmospheric conditions (e.g. atmospheric reflectance, solar zenith angle, brightness temperature) and fuel type for the event. The fire mask layer in the VNP14 product is the primary layer and can be used to identify fires and other thermal anomalies such as volcanoes. In addition to the fire mask, brightness temperature is provided for VIIRS channels M5, M7, M11, M13, M15, and M16. Each swath of data is approximately 3,060 kilometers along track (long) and 3,060 kilometers across track (wide). The VNP14 product is also used to generate higher-level fire data products.Use of the [VNP03MODLL](https://doi.org/10.5067/viirs/vnp03modll.001) data product is required to apply accurate geolocation information to the VNP14 Science Datasets (SDS).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).
MODIS/Aqua Thermal Anomalies/Fire 5-Min L2 Swath 1km V061
The Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire (MYD14) Version 6.1 product is produced daily in 5-minute temporal satellite increments (swaths). The MYD14 product is used to generate all of the higher level fire products, but can also be used to identify fires and other thermal anomalies, such as volcanoes. Each swath of data is approximately 2,030 kilometers along track (long), and 2,300 kilometers across track (wide). 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=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).
MODIS/Aqua Thermal Anomalies/Fire 5-Min L2 Swath 1km V006
The MYD14 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the [MYD14 Version 6.1](https://doi.org/10.5067/MODIS/MYD14.061) data product.The Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire MYD14 Version 6 product is produced daily in 5-minute temporal satellite increments (swaths). The MYD14 product is used to generate all of the higher level fire products, but can also be used to identify fires and other thermal anomalies, such as volcanoes. Each swath of data is approximately 2,030 kilometers along track (long), and 2,300 kilometers across track (wide). Known Issues* Known issues are described on the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=Aqua&as=6) and in Section 7.2 of the User Guide which covers Pre-November 2000 Data Quality, Detection Confidence, Flagging of Static Sources, and the August 2020 MODIS Aqua Outage.Improvements/Changes from Previous Versions* Refinements to internal cloud mask, which sometimes flags heavy smoke as clouds.* Fix for frequent false alarms occurring in the Amazon that are caused by small (~1 km²) clearings within forests.* Fix to correct a bug that causes incorrect assessment of cloud and water pixels adjacent to fire pixels near the scan edge.* Detects small fires using dynamic thresholding.* Processes ocean and coastline pixels to detect fire from oil rigs.* The Version 6 fire mask has the potential to detect fire over water pixels. Therefore, class 3 pixel values have been changed to be classified as “non-fire water pixels.”
MODIS/Aqua Thermal Anomalies/Fire 8-Day L3 Global 1km SIN Grid V061
The Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire 8-Day (MYD14A2) Version 6.1 data are generated at 1 kilometer (km) spatial resolution as a Level 3 product. The MYD14A2 gridded composite contains maximum value of individual fire pixel classes detected during the eight days of acquisition.The Science Dataset (SDS) layers include the fire mask and pixel quality indicators.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=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/NPP Thermal Anomalies and Fire Daily L3 Global 1km SIN Grid V002
The daily NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Thermal Anomalies and Fire (VNP14A1) Version 2 data product provides daily information about active fires and other thermal anomalies. The VNP14A1 data product is a global, 1 kilometer (km) gridded composite of fire pixels detected from VIIRS 750 meter (m) bands over a daily (24-hour) period. The VNP14 data products are designed after the Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies/Fire product suite. The VNP14A1 product provides a total of four Science Dataset (SDS) layers for the confidence of fire, maximum fire radiative power (FRP), quality assessment (QA), and position of fire within scan. Each data product file is provided in HDF-EOS5 format. A low resolution browse is also provided showing the fire mask layer with a color map applied in JPEG format.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).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.* 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).
VIIRS/JPSS1 Thermal Anomalies and Fire Daily L3 Global 1km SIN Grid V002
The daily NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) Thermal Anomalies and Fire (VJ114A1) Version 2 data product provides daily information about active fires and other thermal anomalies. The VJ114A1 data product is a global, 1 kilometer (km) gridded composite of fire pixels detected from VIIRS 750 meter (m) bands over a daily (24-hour) period. The VJ114 data products are designed after the Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies/Fire product suite.The VJ114A1 product provides a total of four Science Dataset (SDS) layers for the confidence of fire, maximum fire radiative power (FRP), quality assessment (QA), and position of fire within scan. Each data product file is provided in HDF-EOS5 format. A low resolution browse is also provided showing the fire mask layer with a color map applied in JPEG format. 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 5.0 “Frequently Asked Questions” of the User Guide.Improvements/Changes from Previous Version* Improved calibration algorithm and coefficients for entire NOAA-20 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.* 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).
VIIRS/NPP Thermal Anomalies/Fire 6-Min L2 Swath 750m V002
The Visible Infrared Imaging Radiometer Suite (VIIRS) Thermal Anomalies (VNP14) Version 2 product is produced in 6-minute temporal satellite increments (swaths) at 750 meter resolution from the VIIRS sensor located on the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) satellite. This product is designed after the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire data products to promote the continuity of the Earth Observation System (EOS) mission. This data product can enable users to understand the location and intensity of fire events as well as identifying thermal anomalies. The VNP14 product includes 31 science dataset layers to analyze key factors in fire detection, including atmospheric conditions (e.g., atmospheric reflectance, solar zenith angle, brightness temperature) and fuel type for the event. The fire mask layer in the VNP14 product is the primary layer and can be used to identify fires and other thermal anomalies such as volcanoes. In addition to the fire mask, brightness temperature is provided for VIIRS channels M5, M7, M11, M13, M15, and M16. Each swath of data is approximately 3,060 kilometers along track (long) and 3,060 kilometers across track (wide). The VNP14 product is also used to generate higher-level fire data products. Use of the [VNP03MODLL](https://doi.org/10.5067/viirs/vnp03modll.002) data product is required to apply accurate geolocation information to the VNP14 Science Datasets (SDS) / Variables.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).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.* 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).
MODIS/Aqua Thermal Anomalies/Fire 8-Day L3 Global 1km SIN Grid V006
The MYD14A2 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the [MYD14A2 Version 6.1](https://doi.org/10.5067/MODIS/MYD14A2.061) data product.The Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire 8-Day (MYD14A2) Version 6 data are generated at 1 kilometer (km) spatial resolution as a Level 3 product. The MYD14A2 gridded composite contains maximum value of individual fire pixel classes detected during the eight days of acquisition.The Science Dataset (SDS) layers include the fire mask and pixel quality indicators. Known Issues* Known issues are described on the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=Aqua&as=6) and in Section 7.2 of the User Guide which covers Pre-November 2000 Data Quality, Detection Confidence, Flagging of Static Sources, and the August 2020 MODIS Aqua Outage.Improvements/Changes from Previous Versions* Refinements to internal cloud mask, which sometimes flags heavy smoke as clouds.* Fix for frequent false alarms occurring in the Amazon that are caused by small (~1 km²) clearings within forests. * Fix to correct a bug that causes incorrect assessment of cloud and water pixels adjacent to fire pixels near the scan edge.* Detect small fires using dynamic thresholding.* Process ocean and coastline pixels to detect fire from oil rigs.* The Version 6 fire mask has the potential to detect fire over water pixels. Therefore, class 3 pixel values have been changed to be classified as “non-fire water pixels”.
MODIS/Terra Thermal Anomalies/Fire 8-Day L3 Global 1km SIN Grid V006
The MOD14A2 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the [MOD14A2 Version 6.1](https://doi.org/10.5067/MODIS/MOD14A2.061) data product.The Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire 8-Day (MOD14A2) Version 6 data are generated at 1 kilometer (km) spatial resolution as a Level 3 product. The MOD14A2 gridded composite contains the maximum value of the individual fire pixel classes detected during the eight days of acquisition.The Science Dataset (SDS) layers include the fire mask and pixel quality indicators.Known Issues* Known issues are described on the [MODIS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=Terra&as=6) and in Section 7.2 of the User Guide which covers Pre-November 2000 Data Quality, Detection Confidence, Flagging of Static Sources, and the August 2020 MODIS Aqua OutageImprovements/Changes from Previous Versions* Refinements to internal cloud mask, which sometimes flags heavy smoke as clouds.* Fix for frequent false alarms occurring in the Amazon that are caused by small (~1 km²) clearings within forests. * Fix to correct a bug that causes incorrect assessment of cloud and water pixels adjacent to fire pixels near the scan edge.* Detect small fires using dynamic thresholding.* Process ocean and coastline pixels to detect fire from oil rigs.* The Version 6 fire mask has the potential to detect fire over water pixels. Therefore, class 3 pixel values have been changed to be classified as “non-fire water pixels”.
MODIS/Terra Thermal Anomalies/Fire Daily L3 Global 1km SIN Grid V006
The MOD14A1 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the [MOD14A1 Version 6.1](https://doi.org/10.5067/MODIS/MOD14A1.061) data product.The Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire Daily (MOD14A1) Version 6 data are generated every eight days at 1 kilometer (km) spatial resolution as a Level 3 product. MOD14A1 contains eight consecutive days of fire data conveniently packaged into a single file.The Science Dataset (SDS) layers include the fire mask, pixel quality indicators, maximum fire radiative power (MaxFRP), and the position of the fire pixel within the scan. Each layer consists of daily per pixel information for each of the eight days of data acquisition. Known Issues* Known issues are described on the [MODIS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=Terra&as=6) and in Section 7.2 of the User Guide which covers Pre-November 2000 Data Quality, Detection Confidence, Flagging of Static Sources, and the August 2020 MODIS Aqua OutageImprovements/Changes from Previous Versions* Refinements to internal cloud mask, which sometimes flags heavy smoke as clouds.* Fix for frequent false alarms occurring in the Amazon that are caused by small (~1 km²) clearings within forests. * Fix to correct a bug that causes incorrect assessment of cloud and water pixels adjacent to fire pixels near the scan edge.* Detect small fires using dynamic thresholding.* Process ocean and coastline pixels to detect fire from oil rigs.* The Version 6 fire mask has the potential to detect fire over water pixels. Therefore, class 3 pixel values have been changed to be classified as “non-fire water pixels”.
MODIS/Aqua Terra Thermal Anomalies/Fire locations 1km FIRMS NRT (Vector data)
The MODIS/Aqua Terra Thermal Anomalies/Fire locations 1km FIRMS Near Real-Time (NRT) - Collection 61 processed by NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) Fire Information for Resource Management System (FIRMS), using swath products (MOD14/MYD14) rather than the tiled MOD14A1 and MYD14A1 products. The thermal anomalies / active fire represent the center of a 1km pixel that is flagged by the MODIS MOD14/MYD14 Fire and Thermal Anomalies algorithm (Giglio 2003) as containing one or more fires within the pixel. This is the most basic fire product in which active fires and other thermal anomalies, such as volcanoes, are identified.MCD14DL are available in the following formats: TXT, SHP, KML, WMS. These data are also provided through the LANCE FIRMS Fire Email Alerts. Please note only the TXT and SHP files contain all the attributes.Collection 61 data replaced Collection 6 (DOI:10.5067/FIRMS/MODIS/MCD14DL.NRT.006) in April 2021. The C61 processing does not contain any updates to the science algorithm; changes were made to improve the calibration approach in the generation of the Terra and Aqua MODIS Level 1B products.
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.