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Gis Data: Prince George’S County, Maryland – Shoreline Inventory Data 2023, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill Jun 2023

Gis Data: Prince George’S County, Maryland – Shoreline Inventory Data 2023, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …


Gis Data: Harford County, Maryland – Shoreline Inventory Data 2023, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill Jun 2023

Gis Data: Harford County, Maryland – Shoreline Inventory Data 2023, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …


Gis Data: Cecil County, Maryland – Shoreline Inventory Data 2023, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill Jun 2023

Gis Data: Cecil County, Maryland – Shoreline Inventory Data 2023, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …


Gis Data: Caroline County, Maryland – Shoreline Inventory Data 2023, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill Jun 2023

Gis Data: Caroline County, Maryland – Shoreline Inventory Data 2023, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …


Pore Connectivity Influences Mass Transport In Natural Rocks: Pore Structure, Gas Diffusion And Batch Sorption Studies, Qinhong Hu Feb 2023

Pore Connectivity Influences Mass Transport In Natural Rocks: Pore Structure, Gas Diffusion And Batch Sorption Studies, Qinhong Hu

Earth & Environmental Sciences Datasets

The Excel file contains supplementary dataset, in various sheets, for a manuscript entitled "Pore connectivity influences mass transport in natural rocks: Pore structure, gas diffusion and batch sorption studies" The Word file of "Data Dictonary" briefly explained the data in each sheet of the Excel file, from different measurements as detailed in the manuscript. Authors: Xiaoqing Yuan, Qinhong Hu (maxhu@uta.edu), Xiang Lin, Chen Zhao, Qiming Wang, Yukio Tachi, Yuta Fukatsu, Shoichiro Hamamoto, Marja Siitari-Kauppia, and Xiaodong Li


Gis Data: Charles County, Maryland – Shoreline Inventory Data 2021, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill Nov 2022

Gis Data: Charles County, Maryland – Shoreline Inventory Data 2021, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …


Gis Data: Worcester County, Maryland – Shoreline Inventory Data 2021, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill Nov 2022

Gis Data: Worcester County, Maryland – Shoreline Inventory Data 2021, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions: 1) the …


Gis Data: St Mary’S County, Maryland – Shoreline Inventory Data 2021, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill Nov 2022

Gis Data: St Mary’S County, Maryland – Shoreline Inventory Data 2021, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …


Gis Data: Somerset County, Maryland – Shoreline Inventory Data 2021, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill Nov 2022

Gis Data: Somerset County, Maryland – Shoreline Inventory Data 2021, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions: 1) the …


Gis Data: Kent County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill Sep 2022

Gis Data: Kent County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …


Gis Data: Baltimore County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill Sep 2022

Gis Data: Baltimore County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …


Gis Data: Queen Anne’S County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill Sep 2022

Gis Data: Queen Anne’S County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …


Gis Data: Baltimore City, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill Sep 2022

Gis Data: Baltimore City, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …


Gis Data: Wicomico County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill Sep 2022

Gis Data: Wicomico County, Maryland – Shoreline Inventory Data 2022, Karinna Nunez, Tamia Rudnicky, Sharon Killeen, Jessica Hendricks, Catherine R. Duning, Evan Hill

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shore zone into three regions:

1) the …


Replication Data For: Evaporation From Undulating Soil Surfaces Under Turbulent Airflow Through Numerical And Experimental Approaches, Bo Gao, Kathleen Smits, John Farnsworth Dec 2021

Replication Data For: Evaporation From Undulating Soil Surfaces Under Turbulent Airflow Through Numerical And Experimental Approaches, Bo Gao, Kathleen Smits, John Farnsworth

Earth & Environmental Sciences Datasets

Evaporation from undulating soil surfaces is rarely studied due to limited modeling theory and inadequate experimental data linking dynamic soil and atmospheric interactions. The goal of this paper is to provide exploratory insights into evaporation behavior from undulating soil surfaces under turbulent conditions through numerical and experimental approaches. A previously developed and verified coupled free flow and porous media flow model was extended by incorporating turbulent airflow through Reynolds-averaged Navier–Stokes equations. The model explicitly describes the relevant physical processes and the key properties in the free flow, porous media, and at the interface, allowing for the analysis of coupled exchange …


Replication Data For: Evaluation Of Model Concepts To Describe Water Transport In Shallow Subsurface Soil And Across The Soil–Air Interface, Zhen Li, Kathleen Smits Oct 2021

Replication Data For: Evaluation Of Model Concepts To Describe Water Transport In Shallow Subsurface Soil And Across The Soil–Air Interface, Zhen Li, Kathleen Smits

Earth & Environmental Sciences Datasets

Soil water evaporation plays a critical role in mass and energy exchanges across the land–atmosphere interface. Although much is known about this process, there is no agreement on the best modeling approaches to determine soil water evaporation due to the complexity of the numerical modeling scenarios and lack of experimental data available to validate such models. Existing studies show numerical and experimental discrepancies in the evaporation behavior and soil water distribution in soils at various scales, driving us to revisit the key process representation in subsurface soil. Therefore, the goal of this work is to test different mathematical formulations used …


Replication Data For: The Effect Of The Top Soil Layer On Moisture And Evaporation Dynamics, Zhen Li, Kathleen Smits Oct 2021

Replication Data For: The Effect Of The Top Soil Layer On Moisture And Evaporation Dynamics, Zhen Li, Kathleen Smits

Earth & Environmental Sciences Datasets

Understanding the effect of the top soil layer on surface evaporation and water distribution is critical to modeling hydrological systems. However, the dependency of near-surface soil moisture and fluxes on layering characteristics remains unclear. To address this uncertainty, we investigate how the arrangement of soil horizons affects the evaporation and soil moisture, specifically, the near-surface soil moisture, through the combination of numerical simulations and evaporation experiments. The characteristics of fluxes and moisture from different soil profiles are then used to understand the soil layering conditions. Results show that the top soil layer can significantly affect the evolution of soil moisture …


Replication Data For: Goehring Et Al., "The Transport History Of Alluvial Fan Sediment...", Nathan Brown Aug 2021

Replication Data For: Goehring Et Al., "The Transport History Of Alluvial Fan Sediment...", Nathan Brown

Earth & Environmental Sciences Datasets

This data repository contains: A) MATLAB source code B) Sample locations and chemical measurements used for Be-10 and C-14 analysis C) Dose recovery test results for luminescence protocol D) Sample locations and dosimetry information for luminescence samples.


Replication Data For: Study Of Methane Migration In The Shallow Subsurface From A Gas Pipe Leak, Kathleen Smits May 2021

Replication Data For: Study Of Methane Migration In The Shallow Subsurface From A Gas Pipe Leak, Kathleen Smits

Earth & Environmental Sciences Datasets

With the increased use of natural gas, safety and environmental concerns from underground leaking natural gas pipelines are becoming more widespread. What is not well understood in leakage incidents is how the soil conditions affect gas migration behavior, making it difficult to estimate the gas distribution. To shed light on these concerns, an increased understanding of subsurface methane migration after gas release is required to support efficient leak response and effective use of available technologies. In this study, three field-scale experiments were performed at the Methane Emission Technology Evaluation Center in Colorado State University to investigate the effect of soil …


Gis Data: Anne Arundel County, Maryland - Shoreline Inventory Data 2020, Karinna Nunez, Marcia Berman, Sharon Killeen, Jessica Hendricks, Tamia Rudnicky, Catherine Riscassi Jan 2021

Gis Data: Anne Arundel County, Maryland - Shoreline Inventory Data 2020, Karinna Nunez, Marcia Berman, Sharon Killeen, Jessica Hendricks, Tamia Rudnicky, Catherine Riscassi

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shorezone into three regions:

1) the immediate …


Gis Data: Dorchester County, Maryland - Shoreline Inventory Data 2020, Karinna Nunez, Marcia Berman, Sharon Killeen, Jessica Hendricks, Tamia Rudnicky, Catherine Riscassi Jan 2021

Gis Data: Dorchester County, Maryland - Shoreline Inventory Data 2020, Karinna Nunez, Marcia Berman, Sharon Killeen, Jessica Hendricks, Tamia Rudnicky, Catherine Riscassi

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shorezone into three regions:

1) the immediate …


Gis Data: Calvert County, Maryland - Shoreline Inventory Data 2020, Karinna Nunez, Marcia Berman, Sharon Killeen, Jessica Hendricks, Tamia Rudnicky, Catherine Riscassi Jan 2021

Gis Data: Calvert County, Maryland - Shoreline Inventory Data 2020, Karinna Nunez, Marcia Berman, Sharon Killeen, Jessica Hendricks, Tamia Rudnicky, Catherine Riscassi

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shorezone into three regions:

1) the immediate …


Gis Data: Talbot County, Maryland - Shoreline Inventory Data 2020, Karinna Nunez, Marcia Berman, Sharon Killeen, Jessica Hendricks, Tamia Rudnicky, Catherine Riscassi Jan 2021

Gis Data: Talbot County, Maryland - Shoreline Inventory Data 2020, Karinna Nunez, Marcia Berman, Sharon Killeen, Jessica Hendricks, Tamia Rudnicky, Catherine Riscassi

Data

The shoreline inventory files have been generated to support the application of the Maryland Shoreline Stabilization Model (SSM), developed by the Center for Coastal Resources Management (CCRM), Virginia Institute of Marine Science (VIMS), to enhance and streamline regulatory decision making in Maryland. This shoreline inventory includes the features needed as inputs to run the SSM.

The data developed for the Shoreline Inventory is based on a three-tiered shoreline assessment approach. This assessment characterizes conditions by using observations made remotely at the desktop using high resolution imagery. The three-tiered shoreline assessment approach divides the shorezone into three regions:

1) the immediate …


Changes In Water Vapor Adsorption And Water Film Thickness In Clayey Materials As A Function Of Relative Humidity, Qinhong Hu Sep 2020

Changes In Water Vapor Adsorption And Water Film Thickness In Clayey Materials As A Function Of Relative Humidity, Qinhong Hu

Earth & Environmental Sciences Datasets

Soil water, with adsorbed water being an important component, plays an important role in fluid flow and chemical movement in the unsaturated zone. The adsorbed water consists of water film and interlayer water, and its content is related to the relative humidity (RH). This study theoretically and experimentally focuses on the variation in adsorbed water content in clayey materials as the RH changes. Based on a slit-pore model, three types of water (water film, interlayer water, and capillary water) could be present in the water vapor adsorption process. The variation of water film is obtained from the analysis of interfacial …


Quantifying Fluid-Wettable Effective Pore Space In The Utica And Bakken Oil Shale Formations, Qinhong Hu May 2020

Quantifying Fluid-Wettable Effective Pore Space In The Utica And Bakken Oil Shale Formations, Qinhong Hu

Earth & Environmental Sciences Datasets

Laboratory results from (U)SANS [(ultra) small angle neutron scattering] work conducted at NIST to be published at an American Geophysical Union (AGU) journal. (2020-05-26)


King William County, Virginia Shoreline Inventory Data 2019, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Jessica Hendricks, Carl Hershner, Evan Hill Jan 2019

King William County, Virginia Shoreline Inventory Data 2019, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Jessica Hendricks, Carl Hershner, Evan Hill

Data

The 2019 Inventory for King William County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1 while viewing conditions observed in 2017 imagery from the Virginia Base Mapping Program (VBMP), Google Earth, and Bing high resolution oblique imagery. Five GIS shapefiles are developed. The first describes land use and bank conditions (KingWilliam_lubc_2019). The second portrays the presence of beaches (KingWilliam_beach_2019). The third reports shoreline structures that are described as arcs or lines (e.g. riprap) (KingWilliam_sstru_2019). The fourth shapefile includes all structures that are represented as points (e.g. piers) (KingWilliam_astru_2019). The Tidal Marsh Inventory is included as the fifth file …


King And Queen County, Virginia Shoreline Inventory Data 2019, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Jessica Hendricks, Carl Hershner, Evan Hill Jan 2019

King And Queen County, Virginia Shoreline Inventory Data 2019, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie Bradshaw, Jessica Hendricks, Carl Hershner, Evan Hill

Data

The 2019 Inventory for King and Queen County was generated using on-screen, digitizing techniques in ArcGIS® -ArcMap v10.4.1 while viewing conditions observed in 2017 imagery from the Virginia Base Mapping Program (VBMP), Google Earth, and Bing high resolution oblique imagery. Five GIS shapefiles are developed. The first describes land use and bank conditions (kq_lubc_2019). The second portrays the presence of beaches (kq_beach_2019). The third reports shoreline structures that are described as arcs or lines (e.g. riprap) (kq_sstru_2019). The fourth shapefile includes all structures that are represented as points (e.g. piers) (kq_astru_2019). The Tidal Marsh Inventory is included as the fifth …


Catch The King Tide 2018: All King Tide Data, Jon Derek Loftis Dec 2018

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 Oct 2018

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


Gis Data: New Kent County, Virginia Shoreline Inventory Report, Marcia Berman, Karinna Nunez, Sharon Killeen, Tamia Rudnicky, Julie G. Bradshaw, Jessica Hendricks, Carl Hershner Jan 2018

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 …