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- Creator:
- Dorman, Cole J
- Description:
- CHIME provides accurate measurements while enabling inter-spacecraft calibration in constellation missions, offering a significantly more affordable alternative to traditional magnetometers without compromising measurement quality. The development of CHIME is motivated by the high number of magnetometers needed in spacecraft constellations that require a cost-effective commercial solution, as traditional, precise magnetometers are expensive and require complex ground and on-orbit calibration methods that depend on geomagnetic models or special conditions. CHIME Accuracy Calibration: - Various PNI RM3100s were used for data collection, each specified when used and how - Ground CHIME was used for experiments (50 turns per axis, hand wound) - Bartington HC1 500 mm Helmholtz coil was used for calibration baseline experiments. - Python 3.7+ Coil Homogeneity Simulations: - Python 3.7+ Optimal Calibration Pulse Parameters: - Python 3.7+ - ESA Swarm Simulation Data 50 Hz: Level 1B MAGx_HR ( https://swarm-diss.eo.esa.int). - ESA Swarm Simulation Data 1 Hz: Level 1B MAGx_LR. CHIME Calibration Accuracy Across Orbital Environments: - Python 3.7+ - ESA Swarm Simulation Data 50 Hz: Level 1B MAGx_HR ( https://swarm-diss.eo.esa.int). Comparison Simulations of Single Sensor Attitude Indepedent Calibration Methods: - Python 3.7+ - ESA Swarm Simulation Data 50 Hz: Level 1B MAGx_HR ( https://swarm-diss.eo.esa.int). Definitions: CHIME- protagonist of the dataset and accompanying manuscript, the self-calibrating magnetometer Scale Factor (SF), Non-Orthogonality (NO)- forms of magnetic sensor error PNI RM3100- internal magnetic sensor in CHIME Bartington HC1 Coil- calibration tool for the RM3100 and CHIME, a Helmholtz coil itself. ESA - European Space Agency
- Keyword:
- magnetometer, calibration, Helmholtz, spacecraft, and remote sensing
- Citation to related publication:
- Dorman, C.J., Vata, J., Ojeda, L. V., Moldwin, M.B., The CHIME Magnetometer: A Self-Calibrating Approach for Enhanced Accuracy in Spaceborne Applications, Forthcoming.
- Discipline:
- Engineering
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- Creator:
- Hawes, Jason K
- Description:
- Most of this deposit is composed of a step-by-step explanation of how to replicate the work conducted in Chapters 2 and 5 of my dissertation (available in DeepBlue Documents under the title Urban Agriculture: Good for People, Places, and Planet?). Very little actual data is catalogued here, instead largely relying on links to the secondary datasets online. In fact, this is an intentional choice, since any replication would likely want updated data to produce more real-time results. This deposit is intended to accompany the dissertation and may not be the final version of these two manuscripts or their associated methods. For more up-to-date methods and analysis, please search Google Scholar or your affiliated library for Jason Hawes and some combination of keywords including urban agriculture, scaling-up, tradeoffs, or the names of the cities in question.
- Keyword:
- urban agriculture, tradeoffs, remote sensing, and multi-criteria analysis
- Discipline:
- Social Sciences
-
- Creator:
- Mateling, Marian E. and Pettersen, Claire
- Description:
- This merged Global Precipitation Measurement (GPM) Core Observatory and atmospheric river dataset contains gridded Goddard Profiling (GPROF) algorithm v7 precipitation rates (Kummerow et al. 2015; Randel et al. 2020), Remote Sensing Systems (RSS) atmospheric water vapor (Meissner et al. 2012), and Mattingly et al. (2018) atmospheric rivers in the North Atlantic and North Pacific oceans. The GPROF precipitation rates and RSS atmospheric water vapor are both derived using the GPM Microwave Imager (GMI) brightness temperature observations. The atmospheric river data is derived from MERRA-2 (Modern-Era Retrospective analysis for Research and Applications Reanalysis, Version 2) integrated water vapor transport (Mattingly et al. 2018). , The data coverage starts at the beginning of the GPM data record (GPM launched in Feb 2014 and the processed data coverage starts in May 2014). Subsequent years will be added throughout the lifetime of the project. , The monthly files are compressed into year and basin: either the North Atlantic (NA) or the North Pacific (NP) (e.g., NA_2014) and zipped. The files have the basin name indicated and are by year and month (e.g., gridded_atlantic_201405.nc). The files produced are in NetCDF format ( https://www.unidata.ucar.edu/software/netcdf/) and conform to all standard NetCDF metadata conventions ( http://cfconventions.org/cf-conventions/cf-conventions.html), and Kummerow, C. D., Randel, D. L., Kulie, M., Wang, N. Y., Ferraro, R., Joseph Munchak, S., & Petkovic, V. (2015). The evolution of the Goddard profiling algorithm to a fully parametric scheme. Journal of atmospheric and oceanic technology, 32(12), 2265-2280. https://doi.org/10.1175/JTECH-D-15-0039.1 Mattingly, K. S., Mote, T. L., & Fettweis, X. (2018). Atmospheric river impacts on Greenland Ice Sheet surface mass balance. Journal of Geophysical Research: Atmospheres, 123(16), 8538-8560. https://doi.org/10.1029/2018JD028714 Meissner, T., F. J. Wentz, and D. Draper, 2012: GMI Calibration Algorithm and Analysis Theoretical Basis Document, Remote Sensing Systems, Santa Rosa, CA, report number 041912, 124 pp. Randel, D. L., Kummerow, C. D., & Ringerud, S. (2020). The Goddard Profiling (GPROF) precipitation retrieval algorithm. Satellite Precipitation Measurement: Volume 1, 141-152. https://doi.org/10.1007/978-3-030-24568-9_8
- Keyword:
- Precipitation, satellite, microwave radiometer, atmospheric water vapor, and remote sensing
- Citation to related publication:
- Mateling et al., submitted to Earth and Space Science (updated when finalized)
- Discipline:
- Science
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- Creator:
- Horsley, Timothy J. and Sampson, Christina P.
- Description:
- The data (raw data, composite files [processed], and some images) can be read by the program TerraSurveyor. Version 3.0.34.10 of the software was used to create the composite files in this deposit. and The magnetometer data was the second step in a geophysical survey program that began with magnetic susceptibility survey of a portion of the Weedon Island Preserve in St. Petersburg, Florida. Geophysical survey was used to map human occupation of the study area and to guide subsequent archaeological excavations.
- Keyword:
- magnetometry, geophysical survey, remote sensing, Florida archaeology, and coastal archaeology
- Citation to related publication:
- Sampson, C. P. (2019) Safety Harbor at the Weeden Island Site: Late Pre-Columbian Craft, Community, and Complexity on Florida's Gulf Coast. PhD Dissertation, University of Michigan. and Sampson, Christina Perry and Timothy J. Horsley. Using Multi-Staged Magnetic Survey and Excavation to Assess Community Settlement Organization: A Case Study from the Central Peninsular Gulf Coast of Florida. Advances in Archaeological Practice. Cambridge University Press: 18 December 2019. https://doi.org/10.1017/aap.2019.45
- Discipline:
- Science and Social Sciences