cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6824473
title: Shoreline data at 30-m spatial resolution for regions of the USA, in geoJSON format. Region 3: Lousiana/Florida border to Georgia/South Carolina border

description: Data file: SE_USA_Louisiana_Georgia_ref_shoreline.geojson Region: Lousiana/Florida border to Georgia/South Carolina 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.6824472
title: Shoreline data at 30-m spatial resolution for regions of the USA, in geoJSON format. Region 3: Lousiana/Florida border to Georgia/South Carolina border

description: Data file: SE_USA_Louisiana_Georgia_ref_shoreline.geojson Region: Lousiana/Florida border to Georgia/South Carolina 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.6815719
title: Supporting Information for "Geochemical evidence for diachronous uplift and synchronous collapse of the high elevation Variscan hinterland"

description: Supplemental data for GLR manuscript submission.
DOI: 10.5281/zenodo.6815718
title: Supporting Information for "Geochemical evidence for diachronous uplift and synchronous collapse of the high elevation Variscan hinterland"

description: Supplemental data for GLR manuscript submission.
DOI: 10.5281/zenodo.6824510
title: Shoreline data at 30-m spatial resolution for regions of the USA, in geoJSON format. Region 6: Oregon and Washington

description: Data file: W_USA_Oregon_Washington_ref_shoreline.geojson Region: California/Oregon border to Washington/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.6824509
title: Shoreline data at 30-m spatial resolution for regions of the USA, in geoJSON format. Region 6: Oregon and Washington

description: Data file: W_USA_Oregon_Washington_ref_shoreline.geojson Region: California/Oregon border to Washington/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.6824487
title: Shoreline data at 30-m spatial resolution for regions of the USA, in geoJSON format. Region 4: Mexico/Texas border to Lousiana/Georgia border

description: Data file: S_USA_Texas_Louisiana_ref_shoreline.geojson Region: Mexico/Texas border to Lousiana/Georgia 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.6824486
title: Shoreline data at 30-m spatial resolution for regions of the USA, in geoJSON format. Region 4: Mexico/Texas border to Lousiana/Georgia border

description: Data file: S_USA_Texas_Louisiana_ref_shoreline.geojson Region: Mexico/Texas border to Lousiana/Georgia 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.6824539
title: Eupsittula cactorum zanfona 1

description: .
DOI: 10.5281/zenodo.6824538
title: Eupsittula cactorum zanfona 1

description: .
DOI: 10.25919/3tj9-ct66
title: Parkes observations for project P1101 semester 2022APRS_07

description: We propose to carry out fortnightly monitoring of a very active repeater, FRB~190520, with the Parkes UWL system. Our current observations show that FRB~190520 is not only the most active FRB that can be observed with Parkes, but also shows unique behaviour at 2 to 3 GHz frequency. This makes UWL the ideal instrument to carry out in-depth studies of this repeating FRB. With this program, we expect to detect a large sample of bursts from FRB~190520, and in collaboration with the FAST telescope we will study emission properties, fluence distributions and polarisation properties over an extremely wide bandwidth with high sensitivity.
DOI: 10.21227/p189-v183
title: Solar Insecticidal Lamp

description: Solar Insecticidal Lamp, as a professional device for smart phytoprotection, can kill the insects to calculate the insect density, further guiding the famers to spray pesticide accurately. Various experiments were performed by a testbed, combined Solar Insecticidal Lamp with two cameras around, to get the dataset including time, Pulse Number of Insecticidal Sounds, Pulse Number of Insecticidal Discharges, insecticidal status, abnormal value, and insecticidal quantity. The dataset can be used for a variety of methods related to the research of insecticidal counting.
DOI: 10.5517/ccdc.csd.cc28657x
title: CCDC 2091298: Experimental Crystal Structure Determination

description: Related Article: Hai-Yang Li, Xue Hua, Ting Fu, Xiao-Fei Liu, Shuang-Quan Zang|2022|Chem.Commun.|58|7753|doi:10.1039/D2CC02703H
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28658y
title: CCDC 2091299: Experimental Crystal Structure Determination

description: Related Article: Hai-Yang Li, Xue Hua, Ting Fu, Xiao-Fei Liu, Shuang-Quan Zang|2022|Chem.Commun.|58|7753|doi:10.1039/D2CC02703H
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28tfq8
title: CCDC 2109820: Experimental Crystal Structure Determination

description: Related Article: Jing Jin, Juanjuan Xue, Dan Wu, Guoping Yang, Yaoyu Wang|2022|Chem.Commun.|58|7749|doi:10.1039/D2CC02639B
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc29hnvb
title: CCDC 2130222: Experimental Crystal Structure Determination

description: Related Article: Sumit Garai, Krishna Gopal Ghosh, Ashik Biswas, Sushobhan Chowdhury, Devarajulu Sureshkumar|2022|Chem.Commun.|58|7793|doi:10.1039/D2CC03106J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b7rq2
title: CCDC 2152414: Experimental Crystal Structure Determination

description: Related Article: Sumit Garai, Krishna Gopal Ghosh, Ashik Biswas, Sushobhan Chowdhury, Devarajulu Sureshkumar|2022|Chem.Commun.|58|7793|doi:10.1039/D2CC03106J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc1kh507
title: CCDC 1444538: Experimental Crystal Structure Determination

description: Related Article: Ting Pan, Peng Wu, Weina Zhang, Yu Shen, Fengwei Huo|2022|Chem.Commun.|58|7809|doi:10.1039/D2CC01153K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2bp0hk
title: CCDC 2165148: Experimental Crystal Structure Determination

description: Related Article: Masaru Tanioka, Ayako Kuromiya, Rina Ueda, Tohru Obata, Atsuya Muranaka, Masanobu Uchiyama, Shinichiro Kamino|2022|Chem.Commun.|58|7825|doi:10.1039/D2CC02907C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.