23 datasets found
  1. m

    Appendix for Master's thesis: LAI development, Reflectance Curves

    • data.mendeley.com
    Updated Feb 6, 2017
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    Hannah Wenng (2017). Appendix for Master's thesis: LAI development, Reflectance Curves [Dataset]. http://doi.org/10.17632/xw2c7vvc3n.1
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    Dataset updated
    Feb 6, 2017
    Authors
    Hannah Wenng
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Appendix for Master's thesis. Additional graphs for the ones exemplary printed in the thesis

  2. o

    MASTER: Jornada Experiment-Airborne Science, Southwest US, October 2008

    • daacweb-prod.ornl.gov
    • s.cnmilf.com
    • +6more
    Updated Sep 16, 2022
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    (2022). MASTER: Jornada Experiment-Airborne Science, Southwest US, October 2008 [Dataset]. http://doi.org/10.3334/ORNLDAAC/2014
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    Dataset updated
    Sep 16, 2022
    Description

    This dataset includes Level 1B (L1B) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected as part of the Hyperspectral Infrared Imager (HyspIRI) mission's preparatory airborne campaign during four flights aboard a DOE B-200 and a NASA ER-2 aircraft over California and New Mexico, U.S., 2008-10-20 to 2008-10-29. A focus of this data collection was the USDA Jornada Experimental Range (Jornada) in southern New Mexico. To complement the programs of ground measurements, JORNEX (JORNada EXperiment) began in 1995 to collect remotely sensed data from aircraft and satellite platforms to provide spatial and temporal data on physical and biological states of the Jornada rangeland. JORNEX uses remote sensing techniques to study arid rangeland and the responses of vegetation to changing hydrologic fluxes and atmospheric driving forces. This deployment was coordinated by NASA's Dryden Flight Research Center (DRFC), renamed Armstrong Flight Research Center in 2014, located in Edwards, California, and the U.S. Department of Energy's Remote Sensing Laboratory (RSL) located at Nellis Air Force Base near Las Vegas, Nevada. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 30-meter spatial resolution. The L1B file format is HDF-4. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.

  3. The Mountain Habitats Segmentation and Change Detection Dataset

    • zenodo.org
    • explore.openaire.eu
    • +1more
    bin, txt, zip
    Updated Jan 24, 2020
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    Frédéric Jean; Alexandra Branzan Albu; David Capson; Eric Higgs; Jason T. Fisher; Brian M. Starzomski; Frédéric Jean; Alexandra Branzan Albu; David Capson; Eric Higgs; Jason T. Fisher; Brian M. Starzomski (2020). The Mountain Habitats Segmentation and Change Detection Dataset [Dataset]. http://doi.org/10.5281/zenodo.12590
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    zip, txt, binAvailable download formats
    Dataset updated
    Jan 24, 2020
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Frédéric Jean; Alexandra Branzan Albu; David Capson; Eric Higgs; Jason T. Fisher; Brian M. Starzomski; Frédéric Jean; Alexandra Branzan Albu; David Capson; Eric Higgs; Jason T. Fisher; Brian M. Starzomski
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Description

    This is the dataset presented in the paper The Mountain Habitats Segmentation and Change Detection Dataset accepted for publication in the IEEE Winter Conference on Applications of Computer Vision (WACV), Waikoloa Beach, HI, USA, January 6-9, 2015. The full-sized images and masks along with the accompanying files and results can be downloaded here. The size of the dataset is about 2.1 GB.

    The dataset is released under the Creative Commons Attribution-Non Commercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/legalcode).

    The dataset documentation is hosted on GitHub at the following address: http://github.com/fjean/mhscd-dataset-doc. Direct download links to the latest revision of the documentation are provided below:

  4. Z

    Cars in Stuttgart

    • data.niaid.nih.gov
    Updated Mar 13, 2025
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    Mommert, Michael (2025). Cars in Stuttgart [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_15019407
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    Dataset updated
    Mar 13, 2025
    Dataset authored and provided by
    Mommert, Michael
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Stuttgart
    Description

    This dataset is an educational toy dataset for object detection with remote sensing data. The dataset contains aerial imagery of the city of Stuttgart at 20cm ground sample distance together with bounding box labels indicating cars (single class) present in these images. Labels are present in the COCO format.

    The dataset is split into three parts:* a training split (1000 images),* a validation split (190 images) and* a test split (190 images).

    Each image features a height and width of 128 pixels each, contains RGB bands and is stored in the png format. Image data were cropped from aerial imagery of the city of Stuttgart taken in 2021, which are available through Stadtmessungsamt Stuttgart as open data under the CC BY 4.0 license: https://opendata.stuttgart.de/dataset/luftbilder-2021

    This dataset has been labeled by Yilsey Terea Benavides Miranda, Khem Raj Devkota, David Michael Udoh and Gökhan Yücesan as part of the Master of Photogrammetry and Geoinformatics course "Remote Sensing Studio" in the 2024 summer term at the Stuttgart University of Applied Sciences.

  5. Satellite altimetry reveals intensifying global river water level...

    • zenodo.org
    Updated Apr 2, 2025
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    Chenqi Fang; Chenqi Fang; Di Long; Di Long (2025). Satellite altimetry reveals intensifying global river water level variability [Dataset]. http://doi.org/10.5281/zenodo.14671453
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    Dataset updated
    Apr 2, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Chenqi Fang; Chenqi Fang; Di Long; Di Long
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    These datasets contain all input and output data used for the paper 'Satellite altimetry reveals intensifying global river water level variability'. Detailed descriptions of the datasets and their attributes can be found in the accompanying technical documentation. The code used to generate these datasets is available in our GitHub repository at https://github.com/Fangchq/Satellite-rivers/tree/master.

  6. Master track from POLAR 6 flight P6_246_HAMAG_2024_2402120201 in 1 sec...

    • doi.pangaea.de
    zip
    Updated May 8, 2024
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    Mario Mech; Susanne Crewell; Sabrina Schnitt (2024). Master track from POLAR 6 flight P6_246_HAMAG_2024_2402120201 in 1 sec resolution (zipped, 514 KB) [Dataset]. http://doi.org/10.1594/PANGAEA.967658
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    zipAvailable download formats
    Dataset updated
    May 8, 2024
    Dataset provided by
    PANGAEA
    Authors
    Mario Mech; Susanne Crewell; Sabrina Schnitt
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Feb 12, 2024
    Area covered
    Description

    This dataset is about: Master track from POLAR 6 flight P6_246_HAMAG_2024_2402120201 in 1 sec resolution (zipped, 514 KB).

  7. 4

    Remote sensing of the river Rhine plume

    • data.4tu.nl
    zip
    Updated May 15, 2005
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    L. (Loana) Arentz (2005). Remote sensing of the river Rhine plume [Dataset]. http://doi.org/10.4121/uuid:c423619a-50d7-4174-88b6-6d4a25b60fa8
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    zipAvailable download formats
    Dataset updated
    May 15, 2005
    Dataset provided by
    TU Delft, Department Hydraulic Engineering
    Authors
    L. (Loana) Arentz
    License

    https://doi.org/10.4121/resource:terms_of_usehttps://doi.org/10.4121/resource:terms_of_use

    Time period covered
    1998
    Area covered
    Description

    The data content of remote sensing (RS) images of sea surface temperature (SST) and normalized water-leaving radiance (nLw), for the year 1998, with respect to the River Rhine plume, is investigated. Questions that this study tries to answer are: is it possible to identify the plume from the available RS images, and under which conditions is this possible? How much information on the plumes behaviour can be derived from these images? Does or can this information contribute to our general knowledge of the plume? The images provide a spatial resolution of I km2 and a temporal resolution of I or 2 images per day per sensor for nLw and SST, respectively (in the case of a cloudless atmosphere). In the presence of clouds, no signal is detected for the area of surface water underneath the clouds. Two hypotheses are set up to explain how the RS images can be used to trace the plume. In the hypotheses links are established between salinity gradients that delimit the plume and SST and nLw respectively. The results are based on these hypotheses. From the available images, 9 SST images in spring provide detailed information on the stratified plume and allow for derivation of indirect information on sub-surface processes. In winter the temperature gradients as visible on SST imagery seem to indicate the broad plume patterns. From the nLw images it was not possible to identify the boundaries of the plume. However it is expected that the nLw images are an excellent source for monitoring suspended particulate matter (SPM) in the North Sea. The general conclusion of this study is that the RS data used in this project provide a valuable source of information, with respect to the Dutch coastal zone, in addition to the currently available measurement techniques and computer models. The SST imagery turns out to be particularly useful for tracing stratification, whereas nLw imagery seems to be an excellent source for monitoring SPM in the North Sea. For detailed monitoring of the DCZ and the plume, increased spatial and temporal resolutions are required.

  8. Master tracks in different resolutions from POLAR 6 flight...

    • doi.pangaea.de
    html, tsv
    Updated May 8, 2024
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    Mario Mech; Susanne Crewell; Sabrina Schnitt (2024). Master tracks in different resolutions from POLAR 6 flight P6_246_HAMAG_2024_2402180501 [Dataset]. http://doi.org/10.1594/PANGAEA.967662
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    html, tsvAvailable download formats
    Dataset updated
    May 8, 2024
    Dataset provided by
    PANGAEA
    Authors
    Mario Mech; Susanne Crewell; Sabrina Schnitt
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Feb 18, 2024
    Area covered
    Variables measured
    LATITUDE, DATE/TIME, LONGITUDE, Flight altitude
    Description

    This dataset is about: Master tracks in different resolutions from POLAR 6 flight P6_246_HAMAG_2024_2402180501. Please consult parent dataset @ https://doi.org/10.1594/PANGAEA.967666 for more information.

  9. WPE01 Assessing the value added of NEON for using machine learning to...

    • search.dataone.org
    • portal.edirepository.org
    Updated Feb 21, 2023
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    Brynn Noble; Zak Ratajczak (2023). WPE01 Assessing the value added of NEON for using machine learning to quantify vegetation mosaics and woody plant encroachment at Konza Prairie [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fknb-lter-knz%2F167%2F2
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    Dataset updated
    Feb 21, 2023
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    Brynn Noble; Zak Ratajczak
    Time period covered
    Jun 1, 2021 - Dec 30, 2022
    Area covered
    Variables measured
    point, layer1, layer2, layer3, layer4, layer5, RecType, Comments, DataCode, ndni_mosaic, and 11 more
    Description

    Woody encroachment, or invasion of woody plants, is rapidly shifting tallgrass prairie into shrub and evergreen dominated ecosystems, mainly due to exclusion of fire. Tracking the pace and extent of woody encroachment is difficult because shrubs and small trees are much smaller than the coarse resolution (>10m2) of common remote sensed images. However, the US government has been investing in finer resolution (<2m2) remote sensing through USDA NAIP and the National Ecological Observatory Network (NEON), both of which cost multi-million dollars each year and contain different remote sensed products. We compared two methods of classification (random forests and support vector machines) with these two freely available remotely sensed aerial images to determine if and how much NEON adds to classification accuracy and determine which method of machine learning was more accurate. All models have very high overall classification accuracy (>91%), with the NEON image a few percent more accurate than NAIP. The NEON image significantly relies on canopy height (LiDAR) to make classifications, but the importance of bands is more evenly distributed during NAIP classification. Lastly, accuracy for Eastern Red Cedar specifically is high with NEON (78-84%), compared to the relatively low classification accuracy using NAIP imagery (55-61%).

  10. MODIS/ASTER (MASTER) imagery and derived data in select neighborhoods of the...

    • search.dataone.org
    • portal.edirepository.org
    Updated Nov 3, 2015
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    William Stefanov; Alex Buyantuyev; Sharon Harlan; Darrel Jenerette (2015). MODIS/ASTER (MASTER) imagery and derived data in select neighborhoods of the greater Phoenix metropolitan area [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fknb-lter-cap%2F620%2F1
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    Dataset updated
    Nov 3, 2015
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    William Stefanov; Alex Buyantuyev; Sharon Harlan; Darrel Jenerette
    Time period covered
    Jul 12, 2011 - Jul 16, 2011
    Area covered
    Description

    A data collection campaign using the MODIS/ASTER airborne simulator (MASTER) was conducted in the greater Phoenix metropolitan area in July 2011 to collect visible through mid-infrared multispectral imagery. High resolution (7 m/pixel) land surface temperature products for day and night periods were calculated using the mid-infrared bands of data; surface reflectance, albedo, and Normalized Difference Vegetation Index (NDVI) products were calculated using the visible through shortwave infrared band data for 41 select neighborhoods. While the full MASTER dataset has been processed to at-sensor radiance, it did not include native geolocation data. As georeferencing the entire dataset was not possible with funds available, the processed data described above were extracted for the 41 spatially discrete Phoenix Area Social Survey neighborhoods within the MASTER flight boundary.

  11. g

    MASTER: Jornada Experiment, Nevada-New Mexico, October 2007 | gimi9.com

    • gimi9.com
    Updated Oct 15, 2007
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    (2007). MASTER: Jornada Experiment, Nevada-New Mexico, October 2007 | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_master-jornada-experiment-nevada-new-mexico-october-2007-035bd/
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    Dataset updated
    Oct 15, 2007
    Area covered
    Nevada, New Mexico
    Description

    This dataset includes Level 1B (L1B) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during four flights aboard a DOE B-200 aircraft over Nevada, Arizona, and New Mexico, U.S., from 2007-10-01 to 2007-10-04. A focus of this data collection was the USDA Jornada Experimental Range (Jornada) in southern New Mexico. To complement the programs of ground measurements, JORNEX (JORNada EXperiment) began in 1995 to collect remotely sensed data from aircraft and satellite platforms to provide spatial and temporal data on physical and biological states of the Jornada rangeland. JORNEX uses remote sensing techniques to study arid rangeland and the responses of vegetation to changing hydrologic fluxes and atmospheric driving forces. This deployment was coordinated by the U.S. Department of Energy's Remote Sensing Laboratory (RSL) located at Nellis Air Force Base near Las Vegas, Nevada. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 10-meter spatial resolution. The L1B file format is HDF-4. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.

  12. g

    MASTER: Airborne Science, Southwest US, August 2006 | gimi9.com

    • gimi9.com
    Updated Aug 21, 2006
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    (2006). MASTER: Airborne Science, Southwest US, August 2006 | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_master-airborne-science-southwest-us-august-2006-8b545/
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    Dataset updated
    Aug 21, 2006
    Area covered
    United States
    Description

    This dataset includes Level 1B (L1B) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during 18 flights aboard a DOE B-200 aircraft over Nevada, California and Colorado, U.S., from 2006-08-21 to 2006-09-06. This data collection focused on mapping geological faults. This deployment was coordinated by the U.S. Department of Energy's Remote Sensing Laboratory (RSL) located at Nellis Air Force Base near Las Vegas, Nevada. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 10-meter spatial resolution. The L1B file format is HDF-4. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.

  13. Rao's Q and predictor variables of MSc Data.

    • figshare.com
    zip
    Updated Mar 31, 2025
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    Jolani Bezuidenhout (2025). Rao's Q and predictor variables of MSc Data. [Dataset]. http://doi.org/10.6084/m9.figshare.28160045.v1
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    zipAvailable download formats
    Dataset updated
    Mar 31, 2025
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Jolani Bezuidenhout
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This is a dataset of all climatic, anthropogenic and stable landscape characteristics used as drivers (predictor variables) of habitat heterogeneity (explanatory variable).

  14. MASTER: Geological fault mapping, California-Nevada, October, 2003 - Dataset...

    • data.nasa.gov
    • data.staging.idas-ds1.appdat.jsc.nasa.gov
    Updated Oct 5, 2003
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    nasa.gov (2003). MASTER: Geological fault mapping, California-Nevada, October, 2003 - Dataset - NASA Open Data Portal [Dataset]. https://data.nasa.gov/dataset/master-geological-fault-mapping-california-nevada-october-2003-c7bbe
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    Dataset updated
    Oct 5, 2003
    Dataset provided by
    NASAhttp://nasa.gov/
    Area covered
    Nevada, California
    Description

    This dataset includes Level 1B (L1B) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during six flights aboard a DOE B-200 aircraft over California and Nevada, U.S., on 2003-10-05 to 2003-10-12. An objective of this deployment was geological fault mapping. This deployment was coordinated by the U.S. Department of Energy's Remote Sensing Laboratory (RSL) located at Nellis Air Force Base near Las Vegas, Nevada. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 10-meter spatial resolution. The L1B file format is HDF-4. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.

  15. g

    MASTER: California Fire-Burn Area Emergency Response, California, April 2008...

    • gimi9.com
    Updated Apr 15, 2008
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    (2008). MASTER: California Fire-Burn Area Emergency Response, California, April 2008 | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_master-california-fire-burn-area-emergency-response-california-april-2008-7cee7
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    Dataset updated
    Apr 15, 2008
    Area covered
    California
    Description

    This dataset includes Level 1B (L1B) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected as part of the Hyperspectral Infrared Imager (HyspIRI) mission's preparatory airborne campaign during four flights aboard a DOE B-200 aircraft over California, U.S., 2008-04-14 to 2008-04-26. The locations sampled include areas affected by wildfires in 2007. This deployment was coordinated by the U.S. Department of Energy's Remote Sensing Laboratory (RSL) located at Nellis Air Force Base near Las Vegas, Nevada. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 10-meter spatial resolution. The L1B file format is HDF-4. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.

  16. Master tracks in different resolutions from POLAR 5 flight...

    • doi.pangaea.de
    html, tsv
    Updated Jun 3, 2025
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    Mario Mech; Lena Bruder; Marcus Klingebiel (2025). Master tracks in different resolutions from POLAR 5 flight P5-256_COMPEX-EC_2025_2504110601 [Dataset]. https://doi.pangaea.de/10.1594/PANGAEA.982823
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    tsv, htmlAvailable download formats
    Dataset updated
    Jun 3, 2025
    Dataset provided by
    PANGAEA
    Authors
    Mario Mech; Lena Bruder; Marcus Klingebiel
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Apr 11, 2025
    Area covered
    Variables measured
    LATITUDE, DATE/TIME, LONGITUDE, Flight altitude
    Description

    This dataset is about: Master tracks in different resolutions from POLAR 5 flight P5-256_COMPEX-EC_2025_2504110601. Please consult parent dataset @ https://doi.pangaea.de/10.1594/PANGAEA.982817 for more information.

  17. Master track from POLAR 5 flight P5-256_COMPEX-EC_2025_2504040201 in 1 sec...

    • doi.pangaea.de
    zip
    Updated Jun 3, 2025
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    Mario Mech; Lena Bruder; Marcus Klingebiel (2025). Master track from POLAR 5 flight P5-256_COMPEX-EC_2025_2504040201 in 1 sec resolution (zipped, 992 KB) [Dataset]. https://doi.pangaea.de/10.1594/PANGAEA.982803
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jun 3, 2025
    Dataset provided by
    PANGAEA
    Authors
    Mario Mech; Lena Bruder; Marcus Klingebiel
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Apr 4, 2025
    Area covered
    Description

    This dataset is about: Master track from POLAR 5 flight P5-256_COMPEX-EC_2025_2504040201 in 1 sec resolution (zipped, 992 KB).

  18. MASTER: Instrument validation, California, January, 1999 - Dataset - NASA...

    • data.staging.idas-ds1.appdat.jsc.nasa.gov
    • data.nasa.gov
    Updated Jan 17, 1999
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    nasa.gov (1999). MASTER: Instrument validation, California, January, 1999 - Dataset - NASA Open Data Portal [Dataset]. https://data.staging.idas-ds1.appdat.jsc.nasa.gov/dataset/master-instrument-validation-california-january-1999-b329d
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    Dataset updated
    Jan 17, 1999
    Dataset provided by
    NASAhttp://nasa.gov/
    Area covered
    California
    Description

    This dataset includes Level 1B (L1B) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during a single flight aboard a DOE B-200 aircraft over California, U.S., on 1999-01-17. A primary objective of this deployment was instrument validation. This deployment was coordinated by the U.S. Department of Energy's Remote Sensing Laboratory (RSL) located at Nellis Air Force Base near Las Vegas, Nevada. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 20-meter spatial resolution. The L1B file format is HDF-4. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.

  19. MASTER: Geological substrate mapping, Utah-Colorado, June, 2004 - Dataset -...

    • data.nasa.gov
    Updated Jun 15, 2004
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    nasa.gov (2004). MASTER: Geological substrate mapping, Utah-Colorado, June, 2004 - Dataset - NASA Open Data Portal [Dataset]. https://data.nasa.gov/dataset/master-geological-substrate-mapping-utah-colorado-june-2004-144cb
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    Dataset updated
    Jun 15, 2004
    Dataset provided by
    NASAhttp://nasa.gov/
    Area covered
    Utah, Colorado
    Description

    This dataset includes Level 1B (L1B) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during two flights aboard a DOE B-200 aircraft over Colorado and Utah, U.S., on 2004-07-01. Objectives of this deployment included mapping geological substrates and their mineral content. This deployment was coordinated by the U.S. Department of Energy's Remote Sensing Laboratory (RSL) located at Nellis Air Force Base near Las Vegas, Nevada. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 10-meter spatial resolution. The L1B file format is HDF-4. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.

  20. o

    MASTER: Airborne Science, California-Nevada-Arizona, May, 1999

    • daac.ornl.gov
    Updated Oct 6, 2022
    + more versions
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    (2022). MASTER: Airborne Science, California-Nevada-Arizona, May, 1999 [Dataset]. http://doi.org/10.3334/ORNLDAAC/2101
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    Dataset updated
    Oct 6, 2022
    Description

    This dataset includes Level 1B (L1B) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during a single flight aboard a DOE B-200 aircraft over California, Nevada, and Arizona, U.S., on 1999-05-11. This deployment was coordinated by the U.S. Department of Energy's Remote Sensing Laboratory (RSL) located at Nellis Air Force Base near Las Vegas, Nevada. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 10-meter spatial resolution. The L1B file format is HDF-4. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.

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Hannah Wenng (2017). Appendix for Master's thesis: LAI development, Reflectance Curves [Dataset]. http://doi.org/10.17632/xw2c7vvc3n.1

Appendix for Master's thesis: LAI development, Reflectance Curves

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Dataset updated
Feb 6, 2017
Authors
Hannah Wenng
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Appendix for Master's thesis. Additional graphs for the ones exemplary printed in the thesis

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