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Appendix for Master's thesis. Additional graphs for the ones exemplary printed in the thesis
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.
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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:
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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.
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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.
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This dataset is about: Master track from POLAR 6 flight P6_246_HAMAG_2024_2402120201 in 1 sec resolution (zipped, 514 KB).
https://doi.org/10.4121/resource:terms_of_usehttps://doi.org/10.4121/resource:terms_of_use
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.
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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.
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%).
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.
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.
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.
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This is a dataset of all climatic, anthropogenic and stable landscape characteristics used as drivers (predictor variables) of habitat heterogeneity (explanatory variable).
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.
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.
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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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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This dataset is about: Master track from POLAR 5 flight P5-256_COMPEX-EC_2025_2504040201 in 1 sec resolution (zipped, 992 KB).
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.
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.
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Appendix for Master's thesis. Additional graphs for the ones exemplary printed in the thesis