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Articles 1 - 29 of 29
Full-Text Articles in Physical Sciences and Mathematics
Catch The King Tide 2018: All King Tide Data, Jon Derek Loftis
Catch The King Tide 2018: All King Tide Data, Jon Derek Loftis
Data
"Catch the King" is a citizen-science GPS data collection effort centered in Hampton Roads, VA, that seeks to interactively map the King Tide's maximum inundation extents. The goal is to validate and improving predictive model accuracy for future forecasting of increasingly pervasive "nuisance" flooding.
Bifurcation Of Plankton Community And Its Impact On Dms Distribution In The Southern Ocean, Kelin Zhuang
Bifurcation Of Plankton Community And Its Impact On Dms Distribution In The Southern Ocean, Kelin Zhuang
Earth & Environmental Sciences Datasets
Submitted to Journal of Geophysical Research Biogeosciences Title: Bifurcation of plankton community and its impact on DMS distribution in the Southern Ocean - A Simulated Response to Elevated CO2 Radiative Forcing Data and code
A Climatological Dataset Of Nutrient, Chlorophyll, And Particulate Matter Distributions On The Ross Sea Continental Shelf Derived From Cruise-Based Measurements Spanning 1967 To 2016, Walker O. Smith Jr., Daniel E. Kaufman
A Climatological Dataset Of Nutrient, Chlorophyll, And Particulate Matter Distributions On The Ross Sea Continental Shelf Derived From Cruise-Based Measurements Spanning 1967 To 2016, Walker O. Smith Jr., Daniel E. Kaufman
Data
This dataset includes data used in the publication Smith and Kaufman (2018), Progress in Oceanography, which examines the temporal and spatial distributions of nutrients and particulate matter in the Ross Sea continental Shelf using cruise-based observations, and compares the resulting annual productivity estimates with previously reported satellite-based estimates. Specifically, these data represent distributions of nutrients, chlorophyll, particulate organic carbon, particulate organic nitrogen, and biogenic silica that were compiled from 42 cruises (from 1967 - 2016) to the Ross Sea continental shelf to generate a comprehensive climatological dataset for November, December, January, and February. This climatology provides a novel look at …
Presence/Absence And Density Data For Epipelagic Tows Collected During R/V Blazing Seven Cruises Lf2016a And Lf2016b, Northern Gulf Of Mexico From 2016-06-09 To 2016-07-28, Jay R. Rooker, David Wells
Presence/Absence And Density Data For Epipelagic Tows Collected During R/V Blazing Seven Cruises Lf2016a And Lf2016b, Northern Gulf Of Mexico From 2016-06-09 To 2016-07-28, Jay R. Rooker, David Wells
DEEPEND Datasets
This dataset reports presence/absence and density data for epipelagic tows collected in the northern Gulf of Mexico during R/V Blazing Seven cruises LF2016A and LF2016B (2016-06-09 to 2016-07-28). Larval fishes were sampled from 48 stations and cruise data were collected at each site including latitude/longitude, date, time, environmental data (temperature, salinity, dissolved oxygen) and Sargassum dry weight. Larval catch data before and after the oil spill will be compared to improve our understanding of the causes of temporal variability as it relates to the Deep-Water Horizon oil spill (DWHOS). Habitat associations of selected taxa (billfishes, tunas, dolphinfishes, flyingfishes) will be …
Inventory Of Oceanic Fauna Data Including Species, Weight, And Measurements From R/V Point Sur (Cruise Dp05) In The Gulf Of Mexico From 2017-05-01 To 2017-05-11, April Cook, Tracey Sutton
Inventory Of Oceanic Fauna Data Including Species, Weight, And Measurements From R/V Point Sur (Cruise Dp05) In The Gulf Of Mexico From 2017-05-01 To 2017-05-11, April Cook, Tracey Sutton
DEEPEND Datasets
This dataset includes an inventory of Gulf of Mexico oceanic fauna data including species, weight, and measurements collected from R/V Point Sur (Cruise DP05) from 2017-05-01 to 2017-05-11. The main gear type used was a 10-m2 Multiple Opening Closing Net and Environmental Sensing System (MOCNESS). The MOCNESS was fitted with 6 nets which were opened according to the following depth scheme: net 0 from the surface to 1500m, net 1 from 1500-1200m, net 2 from 200-1000m, net 3 from 1000-600m, net 4 from 600-200m, and net 5 from 200m to the surface. Two trawls were conducted at each station sampled …
Section: 01 Line Frame: 01, 18 October 2017: Aerial Imagery Acquired To Monitor The Distribution And Abundance Of Submerged Aquatic Vegetation In Chesapeake Bay And Coastal Bays, Robert J. Orth, David J. Wilcox, Jennifer R. Whiting, Anna K. Kenne, Erica R. Smith
Section: 01 Line Frame: 01, 18 October 2017: Aerial Imagery Acquired To Monitor The Distribution And Abundance Of Submerged Aquatic Vegetation In Chesapeake Bay And Coastal Bays, Robert J. Orth, David J. Wilcox, Jennifer R. Whiting, Anna K. Kenne, Erica R. Smith
Data
Multispectral aerial imagery acquired in 2017 to monitor the distribution and abundance of submerged aquatic vegetation in Chesapeake Bay and coastal bays
Section: 01 Line Frame: 06, 27 August 2017: Aerial Imagery Acquired To Monitor The Distribution And Abundance Of Submerged Aquatic Vegetation In Chesapeake Bay And Coastal Bays, Robert J. Orth, David J. Wilcox, Jennifer R. Whiting, Anna K. Kenne, Erica R. Smith
Section: 01 Line Frame: 06, 27 August 2017: Aerial Imagery Acquired To Monitor The Distribution And Abundance Of Submerged Aquatic Vegetation In Chesapeake Bay And Coastal Bays, Robert J. Orth, David J. Wilcox, Jennifer R. Whiting, Anna K. Kenne, Erica R. Smith
Data
Multispectral aerial imagery acquired in 2017 to monitor the distribution and abundance of submerged aquatic vegetation in Chesapeake Bay and coastal bays
Conductivity, Temperature, And Depth (Ctd) Data For Deepend Stations, Cruise Dp05, May 2017, David English, Chuanmin Hu, April Cook, Tracey Sutton
Conductivity, Temperature, And Depth (Ctd) Data For Deepend Stations, Cruise Dp05, May 2017, David English, Chuanmin Hu, April Cook, Tracey Sutton
DEEPEND Datasets
Conductivity, temperature, and depth data from the ship's CTD, which was deployed at each of the DEEPEND stations. Depth of cast was variable, but extended from near-surface waters to below the euphotic zone. This data also includes measurements from a red light transmissometer, a chlorophyll fluorometer, and a dissolved oxygen sensor. The data is used in the assessment of the water column's vertical structure, and for comparison with physical models. Data were collected in the northern Gulf of Mexico from May 2-12, 2017.
Conductivity, Temperature And Depth (Ctd) Data For Deepend Stations, Cruise Dp03, May 2016, David English, Chuanmin Hu, April Cook, Tracey Sutton
Conductivity, Temperature And Depth (Ctd) Data For Deepend Stations, Cruise Dp03, May 2016, David English, Chuanmin Hu, April Cook, Tracey Sutton
DEEPEND Datasets
Conductivity, temperature and depth data from the ship's CTD, which is deployed at each of the DEEPEND stations. Depth of cast is variable, but extends from near-surface waters to below the euphotic zone. This data is used in the assessment of the water column's vertical structure, and for comparison with physical models. Data were collected during cruise DP03 in the northern Gulf of Mexico, May 2016.
Microbiome And Bacterioplankton Rrna Gene Sequence Data Collected From Gulf Of Mexico Seawater Samples, Cruises Dp03 And Dp04 From April - August 2016, Cole Easson, Lindsey Freed
Microbiome And Bacterioplankton Rrna Gene Sequence Data Collected From Gulf Of Mexico Seawater Samples, Cruises Dp03 And Dp04 From April - August 2016, Cole Easson, Lindsey Freed
DEEPEND Datasets
Seawater was collected and filtered for microbiome and bacterioplankton sequencing and analyses at various depths during planned DEEPEND cruise expeditions to the GOM in 2016. Filters were stored and then processed for total environmental genomic DNA according to standard methods (see earthmicrobiome.org). 16S rRNA amplicon libraries covering the V4 hypervariable regions were generated with universal PCR primers and then sequenced on an Illumina MiSeq DNA sequencing platform. Raw paired-end sequences were joined and quality filtered in the bioinformatics program, QIIME. Vertical baseline characterizations will track alpha and beta diversity at different depths ranging from 0 – 1500 m, assess seasonal …
Mitochondrial Dna Sequence Alignments And Raw Fastq Files For The Population Genetic Analysis Of The Deep Sea Isopod, Bathynomus Giganteus, Laura Timm, Barbara Moahamed
Mitochondrial Dna Sequence Alignments And Raw Fastq Files For The Population Genetic Analysis Of The Deep Sea Isopod, Bathynomus Giganteus, Laura Timm, Barbara Moahamed
DEEPEND Datasets
This data set includes three alignments (12S, 16S, COI) of mitochondrial DNA sequences, as well as two raw fastq files generated through the next-generation sequencing (NGS) method ddRADseq. This data was collected from Bathynomus giganteus specimens collected from throughout the northeastern Gulf of Mexico.
Chlorophyll Concentration And Optical Absorption Spectra Of Particulate And Dissolved Material, Collected At Several Depths On Deepend Cruises Dp05 From January-December 2017, Chuanmin Hu
DEEPEND Datasets
The optical absorption spectra from seawater’s particulate and dissolved components can be used to compute the penetration of light to various depths, estimate the proportion of living to non-living particulate matter, assess photosynthetic light availability and the type of phytoplankton present, and to validate satellite or airborne ocean color measurements. Chlorophyll and phaeopigment concentrations are often used to estimate the amount of phytoplankton present, and to allow extrapolation of in situ fluorometric measurements. Water was collected using a CTD rosette near the surface and from several depths at each sampling station occupied by the DEEPEND cruise DP05 (see GRIIDC dataset …
16s And Coi Barcoding Sequences For Crustaceans Collected From The Northern Gulf Of Mexico For Cruises Dp02, Dp03, And Dp04 From August 2015 - August 2016, Heather Bracken-Grissom Dr.
16s And Coi Barcoding Sequences For Crustaceans Collected From The Northern Gulf Of Mexico For Cruises Dp02, Dp03, And Dp04 From August 2015 - August 2016, Heather Bracken-Grissom Dr.
DEEPEND Datasets
These are the 16S and COI barcoding sequences for crustaceans collected on cruises DP02, DP03, and DP04. These barcodes, obtained from the species we collected, will be used to aid in species identification efforts, evolutionary relationships analyses, adult-larval linkages, and new species discoveries. Samples were taken from animals collected during cruises that took place in the northern Gulf of Mexico from August 2015 - August 2016.
Gis Data: New Kent County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner
Gis Data: New Kent County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner
Data
The 2018 Inventory for New Kent County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1while viewing conditions observed in Bing high resolution oblique imagery, Google Earth, and2017imagery from the Virginia Base Mapping Program (VBMP).Four GIS shapefiles are developed. The first describes land use and bank conditions (New_Kent_lubc_2018). The second portrays the presence of beaches (New_Kent_beaches_2018). The third reports shoreline structures that are described as arcs or lines(e.g. riprap)(New_Kent_sstru_2018). The final shapefile includes all structures that are represented as points(e.g. piers)(New_Kent_astru_2018).The metadata file accompanies the shapefiles and defines attribute accuracy, data development, and any use restrictions that pertain to …
Gis Data:: Arlington County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Carl Herschner
Gis Data:: Arlington County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Carl Herschner
Data
No abstract provided.
Gis Data: Caroline County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon A. Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl H. Hershner
Gis Data: Caroline County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon A. Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl H. Hershner
Data
No abstract provided.
Gis Data: Caroline County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner
Gis Data: Caroline County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner
Data
The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …
Gis Data: Caroline County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner
Gis Data: Caroline County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner
Data
No abstract provided.
Gis Data: Richmond County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Kory Angstadt, Carl Hershner
Gis Data: Richmond County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Kory Angstadt, Carl Hershner
Data
No abstract provided.
Gis Data: Richmond County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Kory Angstadt, Carl Hershner
Gis Data: Richmond County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Kory Angstadt, Carl Hershner
Data
The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …
Gis Data: Richmond County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Kory Angstadt, Carl Hershner
Gis Data: Richmond County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Kory Angstadt, Carl Hershner
Data
No abstract provided.
Gis Data: Essex County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, David Stanhope, Carl Hershner
Gis Data: Essex County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, David Stanhope, Carl Hershner
Data
No abstract provided.
Gis Data: Essex County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, David Stanhope, Carl Hershner
Gis Data: Essex County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, David Stanhope, Carl Hershner
Data
The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …
Gis Data: New Kent County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner
Gis Data: New Kent County, Virginia Shoreline Management Model, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner
Data
The Shoreline Management Model is a GIS spatial model that determines appropriate shoreline best management practices using available spatial data and decision tree logic. Available shoreline conditions used in the model include the presence or absence of tidal marshes, beaches, and forested riparian buffers, bank vegetation cover, bank height, wave exposure (fetch), nearshore water depth, and proximity of coastal development to the shoreline. The model output for shoreline best management practices is displayed in the locality Comprehensive Map Viewer. One GIS shapefile is developed that describes two arcs or lines representing practices in the upland area and practices at the …
Gis Data: Arlington County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Carl Herschner
Gis Data: Arlington County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Carl Herschner
Data
No abstract provided.
Quality Of Life In A “High-Rise Lawless Slum”: A Study Of The Kowloon Walled City, Prudencea Leung Kwok Lau, Lawrenceb Wai Chung Lai, Daniel Chi Wing Ho
Quality Of Life In A “High-Rise Lawless Slum”: A Study Of The Kowloon Walled City, Prudencea Leung Kwok Lau, Lawrenceb Wai Chung Lai, Daniel Chi Wing Ho
Faculty of Design & Environment (THEi)
Informed by the ‘quality of life’ model with specific reference to Chinese culture, this article uses reliable and publicly available information seldom used in historical or heritage study to identify the designs of flats and builders of the “Kowloon Walled City” (hereafter the City) and reliable oral testimonies to refute some myths about the quality of life within it. This settlement has been notoriously misrepresented by some as a city of darkness that was razed from the face of the Earth before 1997 to fulfill a pre-war dream of the colonial government. This article confirms the view that this extremely …
Gis Data: Essex County, Virginia Shoreline Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, David Stanhope, Carl Hershner
Gis Data: Essex County, Virginia Shoreline Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, David Stanhope, Carl Hershner
Data
No abstract provided.
Section: 01 Line Frame: 01 Aug27-17: Aerial Imagery Acquired To Monitor The Distribution And Abundance Of Submerged Aquatic Vegetation In Chesapeake Bay And Coastal Bays, R. J. Orth, David J. Wilcox, Jennifer R. Whiting, Anna K. Kenne, Erica R. Smith
Section: 01 Line Frame: 01 Aug27-17: Aerial Imagery Acquired To Monitor The Distribution And Abundance Of Submerged Aquatic Vegetation In Chesapeake Bay And Coastal Bays, R. J. Orth, David J. Wilcox, Jennifer R. Whiting, Anna K. Kenne, Erica R. Smith
Data
Multispectral aerial imagery acquired in 2017 to monitor the distribution and abundance of submerged aquatic vegetation in Chesapeake Bay and coastal bays.
Gis Data: New Kent County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner
Gis Data: New Kent County, Virginia Tidal Marsh Inventory, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner
Data
No abstract provided.