cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6824341
title: Doodleverse/Segmentation Zoo Res-UNet models for identifying water in Sentinel-2 MNDWI images of coasts.

description: <strong>Doodleverse/Segmentation Zoo Res-UNet models for identifying water in Sentinel-2 MNDWI images of coasts.</strong> <strong>Based on SWED*** data</strong> https://openmldata.ukho.gov.uk/ These Residual-UNet model data are based on images of coasts and associated labels. Models have been fitted to the following types of data 1. MNDWI (1 band): mndwi MNDWI = (Green - SWIR) / (Green + SWIR)<br> Green = pixel values from the green band<br> SWIR = pixel values from the short-wave infrared band Reference: Xu, H. "Modification of Normalised Difference Water Index (NDWI) to Enhance Open Water Features in Remotely Sensed Imagery." International Journal of Remote Sensing 27, No. 14 (2006): 3025-3033." (ESRI, 2018) Classes are: {0: null, 1: water}. These files are used in conjunction with Segmentation Zoo* For each model, there are 3 files with the same root name: 1. <strong>'.json' </strong>config file: this is the file that was used by Segmentation Gym** to create the weights file. It contains instructions for how to make the model and the data it used, as well as instructions for how to use the model for prediction. It is a handy wee thing and mastering it means mastering the entire Doodleverse. 2.<strong> '.h5'</strong> weights file: this is the file that was created by the Segmentation Gym** function `train_model.py`. It contains the trained model's parameter weights. It can called by the Segmentation Gym** function `seg_images_in_folder.py` or the Segmentation Zoo* function `select_model_and_batch_process_folder.py` to segment a folder of images 3.<strong> '_modelcard.json'</strong> model card file: this is a json file containing fields that collectively describe the model origins, training choices, and dataset that the model is based upon. There is some redundancy between this file and the `config` file (described above) that contains the instructions for the model training and implementation. The model card file is not used by the program but is important metadata so it is important to keep with the other files that collectively make the model and is such is considered part of the model References * https://github.com/Doodleverse/segmentation_zoo ** https://github.com/Doodleverse/segmentation_gym *** https://www.sciencedirect.com/science/article/abs/pii/S0034425722001584
DOI: 10.5066/p9hyei46
title: Data Release for Luminescence: Late Holocene rupture history of the Ash Hill Fault, Eastern California Shear Zone, and the potential for seismogenic strain transfer between nearby faults

description: The following report summarizes the dating results from sedimentary deposits exposed by soil pits in Panamint Valley, CA. Within this report, we detail the methodology used by the USGS Luminescence Geochronology Laboratory to obtain ages including sample preparation methods, luminescence measurement, equivalent dose determination, and dating-related calculations.
DOI: 10.48527/7nxuh2/taeh3q
title: integral_JosePina.mp4

description: :unav
DOI: 10.48527/7nxuh2
title: José Pina: Rádio Águia Azul e Rádio Clube da Feira

description: No âmbito do documentário Aveiro: memórias da rádio, José Pina concedeu entrevista à equipa do projeto SOMA no dia 11 de abril de 2019, na qual falou do seu envolvimento com duas rádios “piratas” de Santa Maria da Feira: a Rádio Águia Azul e a Rádio Clube da Feira. O caráter político e social que as rádios locais tinham no período, a rádio como veículo de disseminação da música que atraía a juventude, a criação de um festival em Ílhavo, Aveiro – Portugal, inspirado na histórica Rádio Faneca, foram alguns dos temas abordados nos excertos aqui selecionados. Nasceu em 1968 em Santa Maria da Feira, Aveiro – Portugal. É diretor do Teatro Aveirense, além de colaborar com os serviços municipais na gestão cultural e na preparação de candidaturas a financiamento institucional e comunitário. Colabora, também, na direção e gestão do Festival dos Canais – festival de artes anual realizado na cidade de Aveiro – bem como na gestão da candidatura de Aveiro a Capital Europeia da Cultura 2027 (projeto promovido na esfera do programa Europa Criativa, com vista à constituição de apoios à área da cultura).
DOI: 10.25810/dwx2-w360
title: Electronic repository of raw data and calculated values from the article "Laboratory studies of salt deliquescence kinetics relevant to Mars"

description: This dataset contains the data associated with the manuscript titled "Laboratory studies of salt deliquescence kinetics relevant to Mars" submited to the Planetary Science Journal.

This dataset contains the raw microscope image files collected during experiments, associated experimental conditions that were present when each image file was collected, and calculated kinetic parameters obtained from the image analyses. Each experiment's images are contained in a zip file.
DOI: 10.5281/zenodo.6824429
title: Shoreline data at 30-m spatial resolution for regions of the USA, in geoJSON format. Region 1: Delaware/Virginia border to Maine/Canada border

description: Data file: NE_USA_Delaware_Maine_ref_shoreline.geojson Region: Delaware/Virginia border to Maine/Canada border Data fields: MEAN_SIG_WAVEHEIGHT TIDAL_RANGE CHLOROPHYLL TURBIDITY TEMP_MOISTURE EMU_PHYSICAL REGIONAL_SINUOSITY GHM MAX_SLOPE % OUTFLOW_DENSITY ERODIBILITY LENGTH_GEO ch_label river_label sinuosity_label slope_label tidal_label turbid_label wave_label CSU_Descriptor CSU_ID The data originally come from https://rmgsc.cr.usgs.gov/outgoing/ecosystems/Global/USGSEsriGlobalCoastalSegmentsv1.mpk The data are described in the following publication Roger Sayre, Suzanne Noble, Sharon Hamann, Rebecca Smith, Dawn Wright, Sean Breyer, Kevin Butler, Keith Van Graafeiland, Charlie Frye, Deniz Karagulle, Dabney Hopkins, Drew Stephens, Kevin Kelly, Zeenatul Basher, Devon Burton, Jill Cress, Karina Atkins, D. Paco Van Sistine, Beverly Friesen, Rebecca Allee, Tom Allen, Peter Aniello, Irawan Asaad, Mark John Costello, Kathy Goodin, Peter Harris, Maria Kavanaugh, Helen Lillis, Eleonora Manca, Frank Muller-Karger, Bjorn Nyberg, Rost Parsons, Justin Saarinen, Jac Steiner & Adam Reed (2019) A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units, Journal of Operational Oceanography, 12:sup2, S47-S56, DOI: 10.1080/1755876X.2018.1529714 ABSTRACT A new 30-m spatial resolution global shoreline vector (GSV) was developed from annual composites of 2014 Landsat satellite imagery. The semi-automated classification of the imagery was accomplished by manual selection of training points representing water and non-water classes along the entire global coastline. Polygon topology was applied to the GSV, resulting in a new characterisation of the number and size of global islands. Three size classes of islands were mapped: continental mainlands (5), islands greater than 1 km<sup>2</sup> (21,818), and islands smaller than 1 km<sup>2</sup> (318,868). The GSV represents the shore zone land and water interface boundary, and is a spatially explicit ecological domain separator between terrestrial and marine environments. The development and characteristics of the GSV are presented herein. An approach is also proposed for delineating standardised, high spatial resolution global ecological coastal units (ECUs). For this coastal ecosystem mapping effort, the GSV will be used to separate the nearshore coastal waters from the onshore coastal lands. The work to produce the GSV and the ECUs is commissioned by the Group on Earth Observations (GEO), and is associated with several GEO initiatives including GEO Ecosystems, GEO Marine Biodiversity Observation Network (MBON) and GEO Blue Planet. https://www.tandfonline.com/doi/full/10.1080/1755876X.2018.1529714
DOI: 10.5281/zenodo.6824428
title: Shoreline data at 30-m spatial resolution for regions of the USA, in geoJSON format. Region 1: Delaware/Virginia border to Maine/Canada border

description: Data file: NE_USA_Delaware_Maine_ref_shoreline.geojson Region: Delaware/Virginia border to Maine/Canada border Data fields: MEAN_SIG_WAVEHEIGHT TIDAL_RANGE CHLOROPHYLL TURBIDITY TEMP_MOISTURE EMU_PHYSICAL REGIONAL_SINUOSITY GHM MAX_SLOPE % OUTFLOW_DENSITY ERODIBILITY LENGTH_GEO ch_label river_label sinuosity_label slope_label tidal_label turbid_label wave_label CSU_Descriptor CSU_ID The data originally come from https://rmgsc.cr.usgs.gov/outgoing/ecosystems/Global/USGSEsriGlobalCoastalSegmentsv1.mpk The data are described in the following publication Roger Sayre, Suzanne Noble, Sharon Hamann, Rebecca Smith, Dawn Wright, Sean Breyer, Kevin Butler, Keith Van Graafeiland, Charlie Frye, Deniz Karagulle, Dabney Hopkins, Drew Stephens, Kevin Kelly, Zeenatul Basher, Devon Burton, Jill Cress, Karina Atkins, D. Paco Van Sistine, Beverly Friesen, Rebecca Allee, Tom Allen, Peter Aniello, Irawan Asaad, Mark John Costello, Kathy Goodin, Peter Harris, Maria Kavanaugh, Helen Lillis, Eleonora Manca, Frank Muller-Karger, Bjorn Nyberg, Rost Parsons, Justin Saarinen, Jac Steiner & Adam Reed (2019) A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units, Journal of Operational Oceanography, 12:sup2, S47-S56, DOI: 10.1080/1755876X.2018.1529714 ABSTRACT A new 30-m spatial resolution global shoreline vector (GSV) was developed from annual composites of 2014 Landsat satellite imagery. The semi-automated classification of the imagery was accomplished by manual selection of training points representing water and non-water classes along the entire global coastline. Polygon topology was applied to the GSV, resulting in a new characterisation of the number and size of global islands. Three size classes of islands were mapped: continental mainlands (5), islands greater than 1 km<sup>2</sup> (21,818), and islands smaller than 1 km<sup>2</sup> (318,868). The GSV represents the shore zone land and water interface boundary, and is a spatially explicit ecological domain separator between terrestrial and marine environments. The development and characteristics of the GSV are presented herein. An approach is also proposed for delineating standardised, high spatial resolution global ecological coastal units (ECUs). For this coastal ecosystem mapping effort, the GSV will be used to separate the nearshore coastal waters from the onshore coastal lands. The work to produce the GSV and the ECUs is commissioned by the Group on Earth Observations (GEO), and is associated with several GEO initiatives including GEO Ecosystems, GEO Marine Biodiversity Observation Network (MBON) and GEO Blue Planet. https://www.tandfonline.com/doi/full/10.1080/1755876X.2018.1529714
DOI: 10.5281/zenodo.6824465
title: Shoreline data at 30-m spatial resolution for regions of the USA, in geoJSON format. Region 2: Georgia/South Carolina border to North Carolina/Delaware border

description: Data file: E_USA_SouthCarolina_NorthCarolina_ref_shoreline.geojson Region: Georgia/South Carolina border to North Carolina/Delaware border Data fields: MEAN_SIG_WAVEHEIGHT TIDAL_RANGE CHLOROPHYLL TURBIDITY TEMP_MOISTURE EMU_PHYSICAL REGIONAL_SINUOSITY GHM MAX_SLOPE % OUTFLOW_DENSITY ERODIBILITY LENGTH_GEO ch_label river_label sinuosity_label slope_label tidal_label turbid_label wave_label CSU_Descriptor CSU_ID The data originally come from https://rmgsc.cr.usgs.gov/outgoing/ecosystems/Global/USGSEsriGlobalCoastalSegmentsv1.mpk The data are described in the following publication Roger Sayre, Suzanne Noble, Sharon Hamann, Rebecca Smith, Dawn Wright, Sean Breyer, Kevin Butler, Keith Van Graafeiland, Charlie Frye, Deniz Karagulle, Dabney Hopkins, Drew Stephens, Kevin Kelly, Zeenatul Basher, Devon Burton, Jill Cress, Karina Atkins, D. Paco Van Sistine, Beverly Friesen, Rebecca Allee, Tom Allen, Peter Aniello, Irawan Asaad, Mark John Costello, Kathy Goodin, Peter Harris, Maria Kavanaugh, Helen Lillis, Eleonora Manca, Frank Muller-Karger, Bjorn Nyberg, Rost Parsons, Justin Saarinen, Jac Steiner & Adam Reed (2019) A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units, Journal of Operational Oceanography, 12:sup2, S47-S56, DOI: 10.1080/1755876X.2018.1529714 ABSTRACT A new 30-m spatial resolution global shoreline vector (GSV) was developed from annual composites of 2014 Landsat satellite imagery. The semi-automated classification of the imagery was accomplished by manual selection of training points representing water and non-water classes along the entire global coastline. Polygon topology was applied to the GSV, resulting in a new characterisation of the number and size of global islands. Three size classes of islands were mapped: continental mainlands (5), islands greater than 1 km<sup>2</sup> (21,818), and islands smaller than 1 km<sup>2</sup> (318,868). The GSV represents the shore zone land and water interface boundary, and is a spatially explicit ecological domain separator between terrestrial and marine environments. The development and characteristics of the GSV are presented herein. An approach is also proposed for delineating standardised, high spatial resolution global ecological coastal units (ECUs). For this coastal ecosystem mapping effort, the GSV will be used to separate the nearshore coastal waters from the onshore coastal lands. The work to produce the GSV and the ECUs is commissioned by the Group on Earth Observations (GEO), and is associated with several GEO initiatives including GEO Ecosystems, GEO Marine Biodiversity Observation Network (MBON) and GEO Blue Planet. https://www.tandfonline.com/doi/full/10.1080/1755876X.2018.1529714
DOI: 10.5281/zenodo.6824464
title: Shoreline data at 30-m spatial resolution for regions of the USA, in geoJSON format. Region 2: Georgia/South Carolina border to North Carolina/Delaware border

description: Data file: E_USA_SouthCarolina_NorthCarolina_ref_shoreline.geojson Region: Georgia/South Carolina border to North Carolina/Delaware border Data fields: MEAN_SIG_WAVEHEIGHT TIDAL_RANGE CHLOROPHYLL TURBIDITY TEMP_MOISTURE EMU_PHYSICAL REGIONAL_SINUOSITY GHM MAX_SLOPE % OUTFLOW_DENSITY ERODIBILITY LENGTH_GEO ch_label river_label sinuosity_label slope_label tidal_label turbid_label wave_label CSU_Descriptor CSU_ID The data originally come from https://rmgsc.cr.usgs.gov/outgoing/ecosystems/Global/USGSEsriGlobalCoastalSegmentsv1.mpk The data are described in the following publication Roger Sayre, Suzanne Noble, Sharon Hamann, Rebecca Smith, Dawn Wright, Sean Breyer, Kevin Butler, Keith Van Graafeiland, Charlie Frye, Deniz Karagulle, Dabney Hopkins, Drew Stephens, Kevin Kelly, Zeenatul Basher, Devon Burton, Jill Cress, Karina Atkins, D. Paco Van Sistine, Beverly Friesen, Rebecca Allee, Tom Allen, Peter Aniello, Irawan Asaad, Mark John Costello, Kathy Goodin, Peter Harris, Maria Kavanaugh, Helen Lillis, Eleonora Manca, Frank Muller-Karger, Bjorn Nyberg, Rost Parsons, Justin Saarinen, Jac Steiner & Adam Reed (2019) A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units, Journal of Operational Oceanography, 12:sup2, S47-S56, DOI: 10.1080/1755876X.2018.1529714 ABSTRACT A new 30-m spatial resolution global shoreline vector (GSV) was developed from annual composites of 2014 Landsat satellite imagery. The semi-automated classification of the imagery was accomplished by manual selection of training points representing water and non-water classes along the entire global coastline. Polygon topology was applied to the GSV, resulting in a new characterisation of the number and size of global islands. Three size classes of islands were mapped: continental mainlands (5), islands greater than 1 km<sup>2</sup> (21,818), and islands smaller than 1 km<sup>2</sup> (318,868). The GSV represents the shore zone land and water interface boundary, and is a spatially explicit ecological domain separator between terrestrial and marine environments. The development and characteristics of the GSV are presented herein. An approach is also proposed for delineating standardised, high spatial resolution global ecological coastal units (ECUs). For this coastal ecosystem mapping effort, the GSV will be used to separate the nearshore coastal waters from the onshore coastal lands. The work to produce the GSV and the ECUs is commissioned by the Group on Earth Observations (GEO), and is associated with several GEO initiatives including GEO Ecosystems, GEO Marine Biodiversity Observation Network (MBON) and GEO Blue Planet. https://www.tandfonline.com/doi/full/10.1080/1755876X.2018.1529714
DOI: 10.5281/zenodo.6824504
title: Shoreline data at 30-m spatial resolution for regions of the USA, in geoJSON format. Region 5: California

description: Data file: W_USA_California_ref_shoreline.geojson Region: Mexico/California border to California/Oregon border Data fields: MEAN_SIG_WAVEHEIGHT TIDAL_RANGE CHLOROPHYLL TURBIDITY TEMP_MOISTURE EMU_PHYSICAL REGIONAL_SINUOSITY GHM MAX_SLOPE % OUTFLOW_DENSITY ERODIBILITY LENGTH_GEO ch_label river_label sinuosity_label slope_label tidal_label turbid_label wave_label CSU_Descriptor CSU_ID The data originally come from https://rmgsc.cr.usgs.gov/outgoing/ecosystems/Global/USGSEsriGlobalCoastalSegmentsv1.mpk The data are described in the following publication Roger Sayre, Suzanne Noble, Sharon Hamann, Rebecca Smith, Dawn Wright, Sean Breyer, Kevin Butler, Keith Van Graafeiland, Charlie Frye, Deniz Karagulle, Dabney Hopkins, Drew Stephens, Kevin Kelly, Zeenatul Basher, Devon Burton, Jill Cress, Karina Atkins, D. Paco Van Sistine, Beverly Friesen, Rebecca Allee, Tom Allen, Peter Aniello, Irawan Asaad, Mark John Costello, Kathy Goodin, Peter Harris, Maria Kavanaugh, Helen Lillis, Eleonora Manca, Frank Muller-Karger, Bjorn Nyberg, Rost Parsons, Justin Saarinen, Jac Steiner & Adam Reed (2019) A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units, Journal of Operational Oceanography, 12:sup2, S47-S56, DOI: 10.1080/1755876X.2018.1529714 ABSTRACT A new 30-m spatial resolution global shoreline vector (GSV) was developed from annual composites of 2014 Landsat satellite imagery. The semi-automated classification of the imagery was accomplished by manual selection of training points representing water and non-water classes along the entire global coastline. Polygon topology was applied to the GSV, resulting in a new characterisation of the number and size of global islands. Three size classes of islands were mapped: continental mainlands (5), islands greater than 1 km<sup>2</sup> (21,818), and islands smaller than 1 km<sup>2</sup> (318,868). The GSV represents the shore zone land and water interface boundary, and is a spatially explicit ecological domain separator between terrestrial and marine environments. The development and characteristics of the GSV are presented herein. An approach is also proposed for delineating standardised, high spatial resolution global ecological coastal units (ECUs). For this coastal ecosystem mapping effort, the GSV will be used to separate the nearshore coastal waters from the onshore coastal lands. The work to produce the GSV and the ECUs is commissioned by the Group on Earth Observations (GEO), and is associated with several GEO initiatives including GEO Ecosystems, GEO Marine Biodiversity Observation Network (MBON) and GEO Blue Planet. https://www.tandfonline.com/doi/full/10.1080/1755876X.2018.1529714
DOI: 10.5281/zenodo.6824503
title: Shoreline data at 30-m spatial resolution for regions of the USA, in geoJSON format. Region 5: California

description: Data file: W_USA_California_ref_shoreline.geojson Region: Mexico/California border to California/Oregon border Data fields: MEAN_SIG_WAVEHEIGHT TIDAL_RANGE CHLOROPHYLL TURBIDITY TEMP_MOISTURE EMU_PHYSICAL REGIONAL_SINUOSITY GHM MAX_SLOPE % OUTFLOW_DENSITY ERODIBILITY LENGTH_GEO ch_label river_label sinuosity_label slope_label tidal_label turbid_label wave_label CSU_Descriptor CSU_ID The data originally come from https://rmgsc.cr.usgs.gov/outgoing/ecosystems/Global/USGSEsriGlobalCoastalSegmentsv1.mpk The data are described in the following publication Roger Sayre, Suzanne Noble, Sharon Hamann, Rebecca Smith, Dawn Wright, Sean Breyer, Kevin Butler, Keith Van Graafeiland, Charlie Frye, Deniz Karagulle, Dabney Hopkins, Drew Stephens, Kevin Kelly, Zeenatul Basher, Devon Burton, Jill Cress, Karina Atkins, D. Paco Van Sistine, Beverly Friesen, Rebecca Allee, Tom Allen, Peter Aniello, Irawan Asaad, Mark John Costello, Kathy Goodin, Peter Harris, Maria Kavanaugh, Helen Lillis, Eleonora Manca, Frank Muller-Karger, Bjorn Nyberg, Rost Parsons, Justin Saarinen, Jac Steiner & Adam Reed (2019) A new 30 meter resolution global shoreline vector and associated global islands database for the development of standardized ecological coastal units, Journal of Operational Oceanography, 12:sup2, S47-S56, DOI: 10.1080/1755876X.2018.1529714 ABSTRACT A new 30-m spatial resolution global shoreline vector (GSV) was developed from annual composites of 2014 Landsat satellite imagery. The semi-automated classification of the imagery was accomplished by manual selection of training points representing water and non-water classes along the entire global coastline. Polygon topology was applied to the GSV, resulting in a new characterisation of the number and size of global islands. Three size classes of islands were mapped: continental mainlands (5), islands greater than 1 km<sup>2</sup> (21,818), and islands smaller than 1 km<sup>2</sup> (318,868). The GSV represents the shore zone land and water interface boundary, and is a spatially explicit ecological domain separator between terrestrial and marine environments. The development and characteristics of the GSV are presented herein. An approach is also proposed for delineating standardised, high spatial resolution global ecological coastal units (ECUs). For this coastal ecosystem mapping effort, the GSV will be used to separate the nearshore coastal waters from the onshore coastal lands. The work to produce the GSV and the ECUs is commissioned by the Group on Earth Observations (GEO), and is associated with several GEO initiatives including GEO Ecosystems, GEO Marine Biodiversity Observation Network (MBON) and GEO Blue Planet. https://www.tandfonline.com/doi/full/10.1080/1755876X.2018.1529714