| Title |
DOMIP - Opioid Overdose Death Data |
| Description |
Opioid Overdose Death cases were received from Delaware's Division
of Forensic Sciences. Overdose statistics presented are based on the
substances found to be present in the body at the time of death as
determined by the DFS toxicology reports. Assignment of decedents to
census tracts was based on the home address of the decedents. Cases
with home addresses outside the state of Delaware or that were
determined to be homeless were excluded. Fields taken from this
dataset are: Age adjusted Opioid Overdose Death rate calculated per
100,000 Delaware residents and Age adjusted Opioid Overdose Death
rate involving an opioid calculated per 100,000 Delaware residents.
|
| Theme/Category |
Health |
| Period Coverage |
2013-2018 |
| Spatial Coverage |
State of Delaware
|
| Keywords |
opioid, overdose, delaware, GIS, mapping |
| Landing Page |
https://www.cdhs.udel.edu/projects/domip/about
|
| Access URL |
https://www.cdhs.udel.edu/projects/domip/link-to-mapping-app
|
| Creator |
Center for Drug & Health Studies, University of Delaware
|
| Publisher |
Center for Drug & Health Studies, University of Delaware
|
| Released Date |
2018 |
| Updated Date |
2019 |
| Publishing Frequency |
Yearly |
| Access Rights |
Restricted |
| Distribution Format |
CSV, XLS |
| Publication |
10.1177/2153368719877222,
10.1007/s10900-018-0583-0,
10.1177/0022042618815687
|
| Project |
| Title |
The Delaware Opioid Metric Intelligence Project (DOMIP) |
| Description |
Provides community surveillance capabilities in Delaware to
help reduce its prescription and illicit drug problems. DOMIP
achieves this by integrating data-on Opioid Overdose Deaths,
crime, population characteristics and community resources into
a user-friendly web application called the DOMIP Mapping app.
|
| Principal Investigator |
Dr. Tammy Anderson
|
| Co-Principal Investigator |
Dr. Daniel O'Connell,
Dr. Ellen A. Donnelly
|
| Funding Agency |
National Institute of Justice
|
|
| Title |
DOMIP - Crime Data |
| Description |
The Delaware Criminal Justice Information System (DELJIS) provided
data on criminal incidents reported to the police or observed by the
police and arrests conducted by Delaware law enforcement. Addresses
and Names fields were cleaned using regular expressions and
addresses were geocoded using ESRI ArcGIS address locators and
mapped to census tracts (the majority of the incident data was
already geocoded). Cases with home addresses outside the state of
Delaware or that were determined to be homeless were excluded. Drug
crimes were identified via the provided crime codes that are also
used to report to the National Incident-Based Reporting System
(NIBRS).
|
| Theme/Category |
Health |
| Period Coverage |
2013-2018 |
| Spatial Coverage |
State of Delaware
|
| Keywords |
opioid, crime, delaware, GIS, mapping |
| Landing Page |
https://www.cdhs.udel.edu/projects/domip/about
|
| Access URL |
https://www.cdhs.udel.edu/projects/domip/link-to-mapping-app
|
| Creator |
Center for Drug & Health Studies, University of Delaware
|
| Publisher |
Center for Drug & Health Studies, University of Delaware
|
| Released Date |
2018 |
| Updated Date |
2019 |
| Publishing Frequency |
Yearly |
| Access Rights |
Restricted |
| Distribution Format |
CSV, XLS |
| Publication |
10.1177/2153368719877222,
10.1007/s10900-018-0583-0,
10.1177/0022042618815687
|
| Project |
| Title |
The Delaware Opioid Metric Intelligence Project (DOMIP) |
| Description |
Provides community surveillance capabilities in Delaware to
help reduce its prescription and illicit drug problems. DOMIP
achieves this by integrating data-on Opioid Overdose Deaths,
crime, population characteristics and community resources into
a user-friendly web application called the DOMIP Mapping app.
|
| Principal Investigator |
Dr. Tammy Anderson
|
| Co-Principal Investigator |
Dr. Daniel O'Connell,
Dr. Ellen A. Donnelly
|
| Funding Agency |
National Institute of Justice
|
|
| Title |
DOMIP - Community Survey Data |
| Description |
The American Community Survey (ACS) is a constantly ongoing survey
that offers a wide variety of socio-economic information.It is the
premier source for detailed population and housing information about
our nation. Fields taken from this dataset are: Disability rate,
poverty rate and uninsured rate.
|
| Theme/Category |
Health |
| Period Coverage |
2013-2018 |
| Spatial Coverage |
State of Delaware
|
| Keywords |
opioid, crime, delaware, GIS, mapping |
| Landing Page |
https://www.cdhs.udel.edu/projects/domip/about
|
| Access URL |
https://www.cdhs.udel.edu/projects/domip/link-to-mapping-app
|
| Creator |
Center for Drug & Health Studies, University of Delaware
|
| Publisher |
Center for Drug & Health Studies, University of Delaware
|
| Released Date |
2018 |
| Updated Date |
2019 |
| Publishing Frequency |
Yearly |
| Access Rights |
Restricted |
| Distribution Format |
CSV, XLS |
| Publication |
10.1177/2153368719877222,
10.1007/s10900-018-0583-0,
10.1177/0022042618815687
|
| Project |
| Title |
The Delaware Opioid Metric Intelligence Project (DOMIP) |
| Description |
Provides community surveillance capabilities in Delaware to
help reduce its prescription and illicit drug problems. DOMIP
achieves this by integrating data-on Opioid Overdose Deaths,
crime, population characteristics and community resources into
a user-friendly web application called the DOMIP Mapping app.
|
| Principal Investigator |
Dr. Tammy Anderson
|
| Co-Principal Investigator |
Dr. Daniel O'Connell,
Dr. Ellen A. Donnelly
|
| Funding Agency |
National Institute of Justice
|
|
| Title |
The Global Urban Heat Island (UHI) Data Set, v1 (2013) |
| Description |
The Global Urban Heat Island (UHI) Data Set, 2013, estimates the
land surface temperature within urban areas in degrees Celsius
(average summer daytime maximum and average summer nighttime
minimum) as well as the difference between those temperatures and
the temperatures in surrounding rural areas, defined as a 10km
buffer around the urban extent.
|
| Theme/Category |
Geospatial |
| Period Coverage |
2013 |
| Spatial Coverage |
POLYGON(( -176.20 78.28 , 179.46 78.28 , 179.46 -54.86 , -176.20
-54.86 ))
|
| Keywords |
climate, hazards, health, infrastructure, remote sensing,
sustainability, urban, land use
|
| Landing Page |
https://sedac.ciesin.columbia.edu/data/set/sdei-global-uhi-2013
|
| Access URL |
https://sedac.ciesin.columbia.edu/downloads/data/sdei/sdei-global-uhi-2013/sdei-global-uhi-2013-shp.zip
|
| Creator |
Socioeconomic Data and Applications Center, CIESIN at Columbia University
|
| Publisher |
Socioeconomic Data and Applications Center, CIESIN at Columbia University
|
| Released Date |
20161021 |
| Access Rights |
Users are free to use, copy, distribute, transmit, and adapt the
work for commercial and non-commercial purposes, without
restriction, as long as clear attribution of the source is provided.
|
| Distribution Format |
vector, tabular, map, map service |
| Publication |
10.7927/H4H70CRF,
10.7927/H408638T,
10.7927/H44M92HC
|
| Project |
| Title |
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1)
|
| Description |
Urbanization poses both challenges and opportunities for
sustainable development and environmental management. Improved
data on patterns of human settlement and trends in population
can help researchers and policy makers better understand
differences between urban and rural areas in terms of their
impacts on the environment and vulnerability to environmental
variability and change. The Global Rural-Urban Mapping
Project, Version 1 (GRUMPv1) data collection is a valuable
resource both for researchers studying human-environment
interactions and for applied users working to address critical
environmental and societal issues.
|
| Funding Agency |
National Aeronautics and Space Administration
|
|
| Title |
The Global Summer Land Surface Temperature (LST) Grids, (2013)
|
| Description |
The Global Summer Land Surface Temperature (LST) Grids, 2013,
represent daytime maximum temperature and nighttime minimum
temperature in degree Celsius at a spatial resolution of 30
arc-seconds (~1km) during summer months of the northern and southern
hemisphere for the year 2013.
|
| Theme/Category |
Geospatial |
| Period Coverage |
2013 |
| Spatial Coverage |
POLYGON(( -180.00 80.01 , 179.99 80.01 , 179.99 -60.01 , -180.00
-60.01 ))
|
| Keywords |
climate, hazards, health, infrastructure, remote sensing,
sustainability, urban, land use
|
| Landing Page |
https://sedac.ciesin.columbia.edu/data/set/sdei-global-summer-lst-2013
|
| Access URL |
https://sedac.ciesin.columbia.edu/data/set/sdei-global-summer-lst-2013/data-download
|
| Creator |
Socioeconomic Data and Applications Center, CIESIN at Columbia University
|
| Publisher |
Socioeconomic Data and Applications Center, CIESIN at Columbia University
|
| Released Date |
20161118 |
| Access Rights |
Users are free to use, copy, distribute, transmit, and adapt the
work for commercial and non-commercial purposes, without
restriction, as long as clear attribution of the source is provided.
|
| Distribution Format |
raster, map, map service |
| Publication |
10.7927/H4H70CRF,
10.7927/H408638T,
10.7927/H48C9T68
|
| Project |
| Title |
The Global Rural-Urban Mapping Project, Version 1 (GRUMPv1)
|
| Description |
Urbanization poses both challenges and opportunities for
sustainable development and environmental management. Improved
data on patterns of human settlement and trends in population
can help researchers and policy makers better understand
differences between urban and rural areas in terms of their
impacts on the environment and vulnerability to environmental
variability and change. The Global Rural-Urban Mapping
Project, Version 1 (GRUMPv1) data collection is a valuable
resource both for researchers studying human-environment
interactions and for applied users working to address critical
environmental and societal issues.
|
| Funding Agency |
National Aeronautics and Space Administration
|
|
| Title |
Global 1-km Downscaled Population Base Year and Projection Grids
Based on the SSPs, v1.01 (2000 – 2100)
|
| Description |
The Global 1-km Downscaled Population Base Year and Projection Grids
Based on the Shared Socioeconomic Pathways, Revision 01, data set
consists of global urban, rural, and total populaton for the base
year 2000, and population projections at ten-year intervals for
2010-2100 at a resolution of 1-km (about 30 arc-seconds), consistent
both quantitatively and qualitatively with the SSPs. This 1-km data
set is a downscaled version of the one-eighth degree (7.5
arc-minutes) data published in Jones and O'Neill (2016). The
downscaling methods were published in Gao (2017). Spatial
demographic data are key inputs for the analysis of land use, energy
use, and emissions, as well as for the assessment of climate change
vulnerability, impacts, and adaptation. The SSPs are developed to
support future climate and global change research and the
Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment
Report (AR6).
|
| Theme/Category |
Geospatial |
| Period Coverage |
2000-2100 |
| Spatial Coverage |
POLYGON(( -180.00 83.63, 180.00 83.63 , 180.00 -55.77 , -180.00
-55.77))
|
| Keywords |
population estimates, socioeconomics, global, society |
| Landing Page |
https://sedac.ciesin.columbia.edu/data/set/popdynamics-1-km-downscaled-pop-base-year-projection-ssp-2000-2100-rev01
|
| Access URL |
https://sedac.ciesin.columbia.edu/data/set/popdynamics-1-km-downscaled-pop-base-year-projection-ssp-2000-2100-rev01/data-download
|
| Creator |
Socioeconomic Data and Applications Center, CIESIN at Columbia University
|
| Publisher |
Socioeconomic Data and Applications Center, CIESIN at Columbia University
|
| Released Date |
20200409 |
| Access Rights |
Users are free to use, copy, distribute, transmit, and adapt the
work for commercial and non-commercial purposes, without
restriction, as long as clear attribution of the source is provided.
|
| Distribution Format |
raster, map, map services |
| Publication |
10.7927/q7z9-9r69,
10.5065/D60Z721H
|
| Project |
| Title |
Population Dynamics |
| Description |
Population dynamics refers to the way population size and
composition changes over time by birth and death rates, and by
immigration and emigration. Topics examined include aging
populations, urbanization, population decline, and population
projections. Global net migration grids have been generated at
30 arc-second resolution (~1 sq. km at the equator) for the
decades of the 1970s, 1980s, and 1990s, where net migration is
the balance between in-migration and out-migration. Also, at
the same resolution and over the same period of time, global
population time series estimates were generated. In addition,
global urban, rural, and total population projection grids
have been produced based on Shared Socioeconomic Pathways
(SSPs) at resolutions of one km (about 30 arc-seconds) and
one-eighth degree (7.5 arc-minutes) at ten-year intervals for
2010-2100. At the regional level, county-equivalent population
estimates for Latin America and the Caribbean were developed
for 1990 and 2000, using spatially consistent and comparable
units.
|
| Funding Agency |
National Aeronautics and Space Administration
|
|
| Title |
A Global Database of Gas Fluxes from Soils after Rewetting or
Thawing, Version 1.0.
|
| Description |
This database contains information compiled from published studies
on gas flux from soil following rewetting or thawing. The resulting
database includes 222 field and laboratory observations focused on
rewetting of dry soils, and 116 field laboratory observations
focused on thawing of frozen soils studies conducted from 1956 to
2010. Fluxes of carbon dioxide, methane, nitrous oxide, nitrogen
oxide, and ammonia (CO2, CH4, N2O, NO and NH3) were compiled from
the literature and the flux rates were normalized for ease of
comparison. Field observations of gas flux following rewetting of
dry soils include events caused by natural rainfall, simulated
rainfall in natural ecosystems, and irrigation in agricultural
lands. Similarly, thawing of frozen soils include field observations
of natural thawing, simulated freezing-thawing events (i.e., thawing
of simulated frozen soil by snow removal), and thawing of seasonal
ice in temperate and high latitude regions (Kim et al., 2012).
Reported parameters include experiment type, location, site type,
vegetation, climate, soil properties, rainfall, soil moisture, soil
gas flux after wetting and thawing, peak soil gas flux properties,
and the corresponding study references. There is one comma-delimited
data file.
|
| Theme/Category |
Environmental |
| Period Coverage |
|
| Spatial Coverage |
|
| Keywords |
|
| Landing Page |
|
| Access URL |
https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1078
|
| Creator |
|
| Publisher |
|
| Released Date |
4/16/12 |
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
Kim, D.G., Vargas, R., Bond-Lamberty, B. and Turetsky, M.R., 2012.
Effects of soil rewetting and thawing on soil gas fluxes: a review
of current literature and suggestions for future research.
Biogeosciences, 9(7), p.2459.
|
| Software to view the data |
|
| Title |
CMS: Soil CO2 Efflux and Properties, Site Vegetation Measurements,
Mexico, 2011-2012. ORNL DAAC, Oak Ridge, Tennessee, USA.
|
| Description |
This data set provides the results of (1) monthly measurements of
soil CO2 efflux, volumetric water content, and temperature, and (2)
seasonal measurements of soil (porosity, bulk density, nitrogen (N)
and carbon (C) content) and vegetation (leaf area index (LAI),
litter and fine root biomass) properties in a water-limited
ecosystem in Baja California, Mexico. Measurements and samples were
collected from August 2011 to August 2012.
|
| Theme/Category |
Environmental |
| Period Coverage |
|
| Spatial Coverage |
|
| Keywords |
|
| Landing Page |
|
| Access URL |
https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1298
|
| Creator |
|
| Publisher |
|
| Released Date |
11/30/15 |
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
Leon, E., Vargas, R., Bullock, S., Lopez, E., Panosso, A.R. and La
Scala Jr, N., 2014. Hot spots, hot moments, and spatio-temporal
controls on soil CO2 efflux in a water-limited ecosystem. Soil
Biology and Biochemistry, 77, pp.12-21.
|
| Software to view the data |
|
| Title |
CMS: Evapotranspiration and Meteorology, Water-Limited Shrublands,
Mexico, 2008-2010. ORNL DAAC, Oak Ridge, Tennessee, USA.
|
| Description |
This data set provides daily average observations for
evapotranspiration (measured and gap-filled), precipitation, net
radiation, soil water content, air temperature, vapor pressure
deficit, and normalized vegetation index (NDVI) from two
water-limited shrubland sites for years 2008-2010. Both sites are
located in the northwest part of Mexico and are part of the MexFlux
network.
|
| Theme/Category |
Environmental |
| Period Coverage |
|
| Spatial Coverage |
|
| Keywords |
|
| Landing Page |
|
| Access URL |
https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1309
|
| Creator |
|
| Publisher |
|
| Released Date |
3/21/16 |
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
Villarreal, S., Vargas, R., Yepez, E.A., Acosta, J.S., Castro, A.,
Escoto‐Rodriguez, M., Lopez, E., Martínez‐Osuna, J., Rodriguez,
J.C., Smith, S.V. and Vivoni, E.R., 2016. Contrasting precipitation
seasonality influences evapotranspiration dynamics in water‐limited
shrublands. Journal of Geophysical Research: Biogeosciences, 121(2),
pp.494-508.
|
| Software to view the data |
|
| Title |
CMS: MODIS GPP, fPAR, and SST, and ENSO Index, Baja California,
Mexico, 2000-2013. ORNL DAAC, Oak Ridge, Tennessee, USA.
|
| Description |
This data set provides data for MODIS-derived (1) gross primary
productivity (GPP) for the years 2000-2010, (2) fraction of
photosynthetically active radiation (fPAR) for the years 2003-2013,
(3) sea surface temperature (SST) for the years 2003-2013, and (4)
the NOAA-source Multivariate ENSO Index (MEI) data for the years
2003-2013 (as a measure of the El Nino/Southern Oscillation). The
study areas were three transects on the Baja California Peninsula,
Mexico, and the adjacent Pacific Ocean. The terrestrial transects,
in order from North to South, West to East included Punta Colonet
(three sites-PC1, PC2, PC3), Punta Abreojos (two sites-PA1, PA2),
and Magdalena Bay (three sites-MB1, MB2, MB3).
|
| Theme/Category |
Environmental |
| Period Coverage |
|
| Spatial Coverage |
|
| Keywords |
|
| Landing Page |
|
| Access URL |
https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1310
|
| Creator |
|
| Publisher |
|
| Released Date |
3/21/16 |
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
|
| Software to view the data |
|
| Title |
Soil Organic Carbon Stock Estimates with Uncertainty across Latin
America. ORNL DAAC, Oak Ridge, Tennessee, USA.
|
| Description |
This dataset provides 5 x 5 km gridded estimates of soil organic
carbon (SOC) across Latin America that were derived from existing
point soil characterization data and compiled environmental
prediction factors for SOC. This dataset is representative for the
period between 1980 to 2000s corresponding with the highest density
of observations available in the WoSIS system and the covariates
used as prediction factors for soil organic carbon across Latin
America. SOC stocks (kg/m2) were estimated for the SOC and bulk
density point measurements and a spatially explicit measure of the
SOC estimation error was also calculated. A modeling ensemble, using
a linear combination of five statistical methods (regression
Kriging, random forest, kernel weighted nearest neighbors, partial
least squared regression and support vector machines) was applied to
the SOC stock data at (1) country-specific and (2) regional scales
to develop gridded SOC estimates (kg/m2) for all of Latin America.
Uncertainty estimates are provided for the two model predictions
based on independent model residuals and their full conditional
response to the SOC prediction factors.
|
| Theme/Category |
Environmental |
| Period Coverage |
|
| Spatial Coverage |
|
| Keywords |
|
| Landing Page |
|
| Access URL |
https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1615
|
| Creator |
|
| Publisher |
|
| Released Date |
3/7/19 |
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
|
| Software to view the data |
|
| Title |
CO2_Efflux_Eden |
| Description |
Dataset of soil CO2 efflux from a seasonally dry tropical forest.
Dataset includes information from January 2006 to April 2008. Soil
CO2 efflux was measured using the gradient method where soil CO2
concentrations were measured in conjunction with soil temperature
and soil moisture. The study site was hit by a hurricane on October
2005, thus soil CO2 efflux rates are high during the beginning of
2006. For more details about the study site and methodology please
see:
|
| Theme/Category |
Environmental |
| Period Coverage |
|
| Spatial Coverage |
|
| Keywords |
|
| Landing Page |
|
| Access URL |
https://figshare.com/articles/CO2_Efflux_Eden/8309567/1
|
| Creator |
|
| Publisher |
|
| Released Date |
6/26/19 |
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
Vargas, R., 2012. How a hurricane disturbance influences extreme CO2
fluxes and variance in a tropical forest. Environmental Research
Letters, 7(3), p.035704.
|
| Software to view the data |
|
| Title |
Annual soil moisture predictions across conterminous United States
using remote sensing and terrain analysis across 1 km grids
(1991-2016)
|
| Description |
We provide 26 annual soil moisture predictions across conterminous
United States for the years 1991-2016. These predictions are
provided in raster files with a geographical (lat, long) projection
system and a spatial resolution of 1 x 1 km grids (folder:
soil_moisture_annual_grids_1991_2016). These raster files were
populated with soil moisture data based on multiple kernel based
machine learning models for coupling hydrologically meaningful
terrain parameters (the explanatory variables) with soil moisture
microwave records (the response variable) from the European Space
Agency Climate Change Initiative. We provide a raster stack with the
annual training data from satellite soil moisture estimates (file:
annual_means_of _ESA_CCI_soil_moiture_1991_2016.tif) and the
explanatory variables (terrain) calculated on SAGA GIS (System of
Automated Geoscientific Analysis) using digital terrain analysis
(folder: explanatory_variables_dem). The explained variance for all
models-years was >70% (10-fold cross-validation). The 1 km soil
moisture grids (compared to the original satellite soil moisture
estimates) had higher correlations with field soil moisture
observations from the North American Soil Moisture Database (n=668
locations with available data between 1991-2013; 0-5 cm depth) than
soil moisture microwave records.
|
| Theme/Category |
Environmental |
| Period Coverage |
|
| Spatial Coverage |
|
| Keywords |
|
| Landing Page |
|
| Access URL |
https://www.hydroshare.org/resource/b8f6eae9d89241cf8b5904033460af61/
|
| Creator |
|
| Publisher |
|
| Released Date |
6/20/19 |
| Updated Date |
3/23/20 |
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
Guevara, M. and Vargas, R., 2019. Downscaling satellite soil
moisture using geomorphometry and machine learning. PloS one, 14(9).
|
| Software to view the data |
|
| Title |
Ecosystem Functional Type Distribution Map for Mexico, 2001-2014
|
| Description |
This dataset provides a map of the distribution of ecosystem
functional types (EFTs) at 0.05 degree resolution across Mexico for
2001 to 2014. EFTs are groupings of ecosystems based on their
similar ecosystem functioning that are used to represent the spatial
patterns and temporal variability of key ecosystem functional traits
without prior knowledge of vegetation type or canopy architecture.
Sixty-four EFTs were derived from the metrics of a 2001-2014
time-series of satellite images of the Enhanced Vegetation Index
(EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS)
product MOD13C2. EFT diversity was calculated as the modal (most
repeated) EFT for each pixel.
|
| Theme/Category |
Environmental |
| Period Coverage |
|
| Spatial Coverage |
|
| Keywords |
|
| Landing Page |
|
| Access URL |
https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1693
|
| Creator |
|
| Publisher |
|
| Released Date |
8/15/19 |
| Updated Date |
9/10/19 |
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
Villarreal, S., Guevara, M., Alcaraz‐Segura, D. and Vargas, R.,
2019. Optimizing an environmental observatory network design using
publicly available data. Journal of Geophysical Research:
Biogeosciences, 124(7), pp.1812-1826.
|
| Software to view the data |
|
| Title |
Global Gridded 1-km Annual Soil Respiration and Uncertainty Derived
from SRDB V3
|
| Description |
This dataset provides six global gridded products at 1-km resolution
of predicted annual soil respiration (Rs) and associated
uncertainty, maps of the lower and upper quartiles of the prediction
distributions, and two derived annual heterotrophic respiration (Rh)
maps. A machine learning approach was used to derive the predicted
Rs and uncertainty data using a quantile regression forest (QRF)
algorithm trained with observations from the global Soil Respiration
Database (SRDB) version 3 spanning from 1961 to 2011. The two Rh
maps were derived from the predicted Rs with two different empirical
equations. These products were produced to support carbon cycle
research at local- to global-scales, and highlight the immense
spatial variability of soil respiration and our ability to predict
it across the globe.
|
| Theme/Category |
Environmental |
| Period Coverage |
|
| Spatial Coverage |
|
| Keywords |
|
| Landing Page |
|
| Access URL |
https://doi.org/10.3334/ORNLDAAC/1736
|
| Creator |
|
| Publisher |
|
| Released Date |
|
| Updated Date |
1/9/20 |
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
Warner, D.L., Bond‐Lamberty, B., Jian, J., Stell, E. and Vargas, R.,
2019. Spatial predictions and associated uncertainty of annual soil
respiration at the global scale. Global Biogeochemical Cycles.
|
| Software to view the data |
|
| Title |
Oklahoma Soil Moisture Predictions |
| Description |
Monthly soil moisture predictions over a region of interest centered
on Oklahoma and surrounded areas from January 2000 to September
2012. Data were acquired from the European Space Agency Climate
Change Initiative soil moisture product version 4.5, 0.25-degrees
spatial resolution. The modeled product aims to fill soil moisture
spatial gaps from the original product over the region of Interest.
Soil moisture values were calculated based on three methods, e.g.
Ordinary Kriging, Regression Kriging and Generalized Linear Model.
Reference monthly soil moisture layers were generated based on daily
soil moisture estimates over each 0.25-degrees pixel in the region
of interest. Three different sampling approaches were considered to
model soil moisture estimates, using 100% of available data from the
original satellite data, 75% and 50% of available soil moisture
estimates respectively. Data were randomly removed to simulate
different scenarios of gap presence in the original ESA CCI product.
Soil Moisture values were validated by means of 10-fold cross
validation and ground-truth validation with records from the North
American Soil Moisture Data Base
|
| Theme/Category |
Environmental |
| Period Coverage |
|
| Spatial Coverage |
|
| Keywords |
|
| Landing Page |
|
| Access URL |
https://www.hydroshare.org/resource/f0091cf90bcc4487bf401ca19783d1eb/
|
| Creator |
|
| Publisher |
|
| Released Date |
2/7/20 |
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
Llamas, R.M., Guevara, M., Rorabaugh, D., Taufer, M. and Vargas, R.,
2020. Spatial Gap-Filling of ESA CCI Satellite-Derived Soil Moisture
Based on Geostatistical Techniques and Multiple Regression. Remote
Sensing, 12(4), p.665.
|
| Software to view the data |
|
| Title |
Soil respiration dataset from a temperate mix forest (James San
Jacinto Mountain Reserve)
|
| Description |
Dataset of soil CO2 efflux from a temperate mix forest. Includes
information from January 2006 to December 2008. Soil CO2 efflux was
measured using the gradient method where soil CO2 concentrations
were measured in conjunction with soil temperature and soil
moisture. The study was conducted at the University of California
James San Jacinto Mountain Reserve, a UC Natural Reserve System
field station. The Reserve is a mixed conifer-oak forest at
1640m.a.s.l. located in the San Jacinto Mountains, CA, USA
(33048'30''N, 116046'40''W).
|
| Theme/Category |
Environmental |
| Period Coverage |
|
| Spatial Coverage |
|
| Keywords |
|
| Landing Page |
|
| Access URL |
https://doi.org/10.6084/m9.figshare.11739459
|
| Creator |
|
| Publisher |
|
| Released Date |
5/3/20 |
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
Vargas, R., Detto, M., Baldocchi, D.D. and Allen, M.F., 2010.
Multiscale analysis of temporal variability of soil CO2 production
as influenced by weather and vegetation. Global Change Biology,
16(5), pp.1589-1605.
|
| Software to view the data |
|
| Title |
Mexico ATI-HRA Dataset |
| Description |
This dataset records counts of human rights abuse-related ATI
requests for each Mexican municipality-month, 06/2003-06/2018. Human
rights-abuse related ATI requests were generated via a supervised
machine learning approach at the individual request level, before
being aggregated to municipality-month counts. Separate supervised
machine coded ATI-based human abuse counts are then recorded for
state perpetrated human rights abuse, non-state perpetrated human
rights abuse, unknown perpetrator human rights abuse, human rights
abuse incidents, and human rights abuses by any perpetrator. For the
municipality-month dataset, the counts of human rights abuse-related
requests are paired with additional municipality-month variables
recording total homicide rates, counts of human rights abuse events
as derived from the ICEWS event dataset, counts of human rights
abuse events as derived from the GED dataset, distance to the US
border, economic marginalization, population, internet access, and
total ATI requests, as well as unique identifiers for each
municipality and time-point.
|
| Theme/Category |
Social Science |
| Period Coverage |
06/2003-06/2018 |
| Spatial Coverage |
Mexico, with unique identifiers for municipality and state |
| Keywords |
Mexico, Access to Information, Accountability, Human Rights Abuse
|
| Landing Page |
|
| Access URL |
|
| Creator |
|
| Publisher |
|
| Released Date |
|
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
1 |
| Distribution Format |
CSV |
| Publication |
Ellington, S.A.V., B.E. Bagozzi, D. Berliner, B. Palmer-Rubin, and
A. Erlich. 2021. "Measuring Human Rights Abuse from Access to
Information Requests" Working Paper.
|
| Software to view the data |
|
| Project |
| Title |
Measuring Human Rights Abuse from Access to Information
Requests
|
| Description |
This project uses supervised machine learning to measure fine
grained citizen concerns over human rights abuses in Mexico
via access to information request texts. The resultant data
are internally and externally validated in several manners.
The current dataset then aggregates these supervised-coded
requests to the municipality-month level, and merges these
data with several additional covariates.
|
|
| Principal Investigator |
Dr. Benjamin Bagozzi
|
|
| Title |
Mexican ATI Request-Response Dataset |
| Description |
This dataset records individual access to information (ATI) requests
and responses for Mexico's federal (national) ATI system. The text
of each individual request (along with OCR'd text of each request
attachment) is included along with a variety of indicators of each
government response. LDA-derived topics have been estimated and
assigned to reach request text. Additional request information is
then included for a unique request identifier, the date and time of
each request, the requester's location (country, state, municipality
and postal code), and the requester's designated federal Mexican
government agency or unit. Additional response data include the
government agency or unit's official response decision, the timing
(date and time) of that decision, and the elapsed time between
request and response.
|
| Theme/Category |
Social Science |
| Period Coverage |
06/2003-06/2020 |
| Spatial Coverage |
Mexico, with unique identifiers for requester municipality, state,
country, and postal code
|
| Keywords |
Mexico, Access to Information, Accountability, Transparency |
| Landing Page |
|
| Access URL |
|
| Creator |
|
| Publisher |
|
| Released Date |
|
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Non-public (Dataset is not available to members of the public)
|
| Version |
2 |
| Distribution Format |
CSV |
| Publication |
Berliner, D., B.E. Bagozzi, and B. Palmer-Rubin. 2018. "What
Information Do Citizens Want? Evidence from One Million Public
Information Requests in Mexico.'' World Development. 109: 222-235.
|
| Software to view the data |
|
| Project |
| Title |
Access to Information in Mexico |
| Description |
This project leverages text-as-data tools to better understand
the nature and drivers of information requests in Mexico.
Extensions to this analysis also consider the nature and
drivers of the Mexican government's responsiveness to these
requests, as well as the influences of politics and the media
on these processes.
|
|
| Principal Investigator |
Dr. Benjamin E. Bagozzi
|
|
| Title |
Do or Die Corpus and Metadata |
| Description |
Issues 1-10 of Do or Die, a set of British radical environmentalist
magazine ('zine) associated with the United Kingdom's Earth First!
movement. The 10-issue 'zine was published semi-annually from 1992
to 2003. Original PDFs of each 'zine were collected from online
sources. Multiple formats and versions of each 'zine are included,
including PDF images, OCR'd pages of each PDF 'zine (in .rtf and
.txt format) as well as scraped webpage versions of some individual
stories, where applicable. Additional data from these texts in terms
of UK environmental group names listed within each issue's contact
section, quantities derived from topic models of these texts, and
network information is also included.
|
| Theme/Category |
Social Science |
| Period Coverage |
1992-2003 |
| Spatial Coverage |
United Kingdom |
| Keywords |
Environmentalism, Text-as-Data, Social Movement, Direct Action
|
| Landing Page |
|
| Access URL |
https://doi.org/10.7910/DVN/PNK7AB
|
| Creator |
|
| Publisher |
|
| Released Date |
|
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
1 |
| Distribution Format |
PDF, TXT, RTF, CSV |
| Publication |
Almquist, Zack W. and Benjamin E. Bagozzi. 2019. "Using Radical
Environmentalist Texts to Uncover Network Structure and Network
Features" Sociological Methods & Research. 49(4): 905-960.
|
| Software to view the data |
|
| Project |
| Title |
Radical Environmentalist Project |
| Description |
This project seeks to better understand radical
environmentalist movements through text-as-data and network
methods.
|
|
| Principal Investigator |
Dr. Benjamin Bagozzi
|
|
| Title |
Topical Attention Bias Measures of US State Department Human Rights
Reports
|
| Description |
A corpus of 6,298 State Department Country Reports on Human Rights
Practices (1977-2012) was topic modeled to recover a plausible set
of  country-year topics pertaining to the US State Department's
monitoring of countries' human rights practices. Recovered topics
are conditional on nation-states actual human rights performance and
additional covariates, and include topics such as killings and
disappearances, freedoms of expression and movement, and labor
rights, among others. The posterior probability of topical
assignment for each estimated topic is recorded for each
country-year, 1977-2012. These quantities are argued to capture time
varying (topical) attention bias in US State Department human rights
reporting in relation to individual countries.
|
| Theme/Category |
Social Science |
| Period Coverage |
1977-2012 |
| Spatial Coverage |
Global (at the country-level) |
| Keywords |
State Department, Human Rights, Monitoring, Repression, Topic
Modeling
|
| Landing Page |
|
| Access URL |
https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/W1QQTP
|
| Creator |
|
| Publisher |
|
| Released Date |
|
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
1 |
| Distribution Format |
CSV |
| Publication |
Bagozzi, B.E. and D. Berliner. 2018. "The Politics of Scrutiny in
Human Rights Monitoring: Evidence from Structural Topic Models of US
State Department Human Rights Reports." Political Science Research
and Methods. 6(4): 661-677.
|
| Software to view the data |
|
| Project |
| Title |
Topical Attention Bias in Human Rights Reporting |
| Description |
This project seeks to better understand US State Department
human rights monitoring with text-as-data tools. Patterns of
human rights reporting are considered over time, and in
relation to a variety of US-specific and cross-national
covariates.
|
|
| Principal Investigator |
Dr. Benjamin Bagozzi
|
|
| Title |
UNFCCC Climate Speech Data |
| Description |
This text-as-data dataset includes nation-states' high-level segment
speeches from the 16th to 26th United Nations Framework Convention
on Climate Change (UNFCCC) Conference of the Parties (COPs),
10-years of speeches in total. Transcripts of all available speeches
were collected in PDF form from UN websites and then converted to
machine readable text and machine translated to English. All
resultant texts are stored as individual .txt files and in combined
.csv files. For network modeling, co-occurrences related to each
speech's co-mentions of nation-states are also extracted and
recorded as .csv files. Subsets of these speeches have also been
topic modeled.
|
| Theme/Category |
Social Science |
| Period Coverage |
2010-2020 |
| Spatial Coverage |
Global (at the country-level) |
| Keywords |
Climate Change, International Relations, International Cooperation,
UNFCCC
|
| Landing Page |
|
| Access URL |
|
| Creator |
|
| Publisher |
|
| Released Date |
|
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Non-public (Dataset is not available to members of the public)
|
| Version |
2 |
| Distribution Format |
CSV, PDF, TXT |
| Publication |
Bagozzi, B. E. 2015. "The Multifaceted Nature of Global Climate
Change Negotiations." Review of International Organizations. 10(4):
439-464.
|
| Software to view the data |
|
| Project |
| Title |
UNFCCC Speeches and Networks |
| Description |
This project seeks to use text-as-data and network methods to
understand patterns of country-level negotiation over climate
change, both at the UNFCCC and more generally. Core dimensions
include understanding the scope and dimensionality of
negotiating themes, negotiation networks, and how these
features change over time.
|
|
| Principal Investigator |
Dr. Benjamin Bagozzi
|
|
| Title |
DEOS Real-Time and Historical Environmental Data |
| Description |
DEOS operates and maintains over 80 environmental monitoring
platforms and brings in data for the following variables: air
temperature, dew point, relative humidity, wind speed, wind
direction, wind gust, heat index, wind chill, atmospheric pressure,
solar radiation, rainfall, water levels, and snow depth. (some
variables are season observations only)
|
| Theme/Category |
Environmental |
| Period Coverage |
2009 to present (some stations are earlier) |
| Spatial Coverage |
Delaware, Chester County PA |
| Keywords |
environment, monitoring, climate, atmosphere, temperature, rain,
wind
|
| Landing Page |
http://deos.udel.edu |
| Access URL |
|
| Creator |
Center for Environmental Monitoring & Analysis (CEMA) |
| Publisher |
Center for Environmental Monitoring & Analysis (CEMA) |
| Released Date |
|
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
|
| Software to view the data |
|
| Project |
| Title |
Delaware Environmental Observing System |
| Description |
For over 15 years, DEOS has been providing real-time and
archived daily and monthly environmental conditions for
Delaware and the surrounding region. Today, DEOS operates and
maintains over 80 environmental monitoring platforms and
brings in data from over 200 additional environmental
monitoring platforms throughout our region.
|
|
| Principal Investigator |
Dr. Kevin Brinson |
|
| Title |
Discourses of Fame and Celebrity |
| Description |
a systematic sample of roughly 10k N-grams (~100k words) pulled from
digital newspaper databases, along with coded identification terms,
that track how fame and celebrity were described over time and space
within the U.S., 1760-1900.
|
| Theme/Category |
Language/Discourse (though geospatial data is included) |
| Period Coverage |
1760-1900 |
| Spatial Coverage |
modern U.S. |
| Keywords |
Fame; Celebrity; Discourse; Text Mining; History; Periodicals |
| Landing Page |
N/A |
| Access URL |
|
| Creator |
|
| Publisher |
|
| Released Date |
|
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Non-public (Dataset is not available to members of the public)
|
| Version |
|
| Distribution Format |
.xlsx |
| Publication |
|
| Software to view the data |
|
| Project |
| Title |
Library of Congress Chronicling America; Readex/Am Antiquarian
Society America's Historical Newspapers Series I
|
| Description |
An effort to track the evolution of discourses of fame and
celebrity, supporting a monograph in-process on the history of
Halls of Fame.
|
|
| Principal Investigator |
Dr. Kenneth Cohen
|
|
| Title |
CORSIKA Simulations of Cosmic-Ray Air Showers |
| Description |
We have various subsets of CORSIKA 7 simulations of cosmic-ray air
showers, covering a range of energies and arrival direction. As we
are continuing to add simulations, ask for details.
|
| Theme/Category |
Astroparticle Physics |
| Period Coverage |
none |
| Spatial Coverage |
Locations of the IceCube Neutrino Observatory (South Pole) and the
Pierre Auger Observatory (Argentina)
|
| Keywords |
|
| Landing Page |
|
| Access URL |
|
| Creator |
|
| Publisher |
|
| Released Date |
|
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Can be made available upon individual requests. |
| Version |
|
| Distribution Format |
proprietary CORSIKA format |
| Publication |
|
| Software to view the data |
|
| Project |
| Title |
Various projects: IceCube, Pierre Auger Observatory, and
others
|
| Description |
We use CORSIKA to simulate expected cosmic-ray signals in
specialzed observatories.
|
|
| Principal Investigator |
Dr. Frank Schroeder
|
|
| Title |
Fall landbird migration stopover distribution maps for the
northeastern U.S.
|
| Description |
"The national network of weather surveillance radars (NEXRAD)
detects birds in flight and has proven to be a useful remote-sensing
tool for ornithological study. These maps were derived from data
collected during Fall 2008 to 2014 by 16 NEXRAD and four terminal
Doppler weather surveillance radars (TDWR) in the northeastern U.S.
to map and study the spatial distribution of landbirds shortly after
they leave daytime stopover sites to embark on nocturnal migratory
flights. NEXRAD observations of Vertically-Integrated Reflectivity
(VIR) - an estimate of the total amount of reflected cross-sectional
area of birds per hectare (i.e., bird density) from 0 to 1750 m
above the ground in units of cm2 ha-1 - were summarized across time
and aggregated to a spatial resolution of 1 km x 1 km. Observed data
(i.e., reflectivity data as measured by radars) have been filtered
to exclude areas of partial radar beam blockage, ground clutter
(i.e., non-biological reflectivity from objects on the ground) and
where radars were unable to detect birds for more than 25% of
sampling nights. This dataset represents input and output variables
of Boosted Generalized Additive Models (BGAM) developed to predict
bird stopover use throughout the Northeast and Mid-Atlantic U.S.
Predicted bird densities increased with increasing hardwood cover at
multiple scales and with vegetation productivity. Contrastingly,
predicted bird densities decreased with increasing agricultural,
emergent marsh and coniferous land cover, but did not change with
fraction of urban cover. Bird stopover density increased closer to
bright areas and the Atlantic coast. Moreover, interactive effects
indicated that migrants were extra concentrated in wooded areas that
were both brightly lit and near the Atlantic coast. Large areas of
predicted regionally important stopover sites were located along the
coastlines of Maine, Long Island Sound, New Jersey, the lower
Delmarva Peninsula, within the Adirondack Mountains, Catskill
Mountains, and eastern Virginia. Migrant densities peaked along the
Adirondack Mountains early in September, and along the Atlantic
coast in late September with the passage of Neotropical migrants.
Stopover densities peaked in the most northern extent of Maine and
New England states in late October with the arrival of temperate
migrants. The maps and ecological understanding produced can help
inform conservation planning to protect and enhance stopover sites
for migratory landbirds in the future. Known Issues and
Uncertainties: We caution against relying too heavily on our
region-wide predictions to assess the relative importance of sites
outside of radar-sampled areas. The predicted bird densities within
radar-sampled areas agreed quite well with radar-observed densities
(explained Deviances of BGAM models predicting mean bird density
were around 0.7). However, the accuracy of predicted bird densities
elsewhere remains unvalidated. Additionally, the results are not
highly precise; they are depicted at a resolution of 1 km by 1 km.
Within an area of this size, suitability for migrants may vary
dramatically depending on the types of land use and development
present. Large, intact, productive hardwood forests that provide an
abundance of insects and fruits appear to be particularly valuable
to migrants. Thus, the region-wide map should be viewed as a coarse
and preliminary guide for conservation purposes. NOTE - The data
represented were converted to raster for display purposes. The
download includes the original shapefile and layer files. In order
to view the attributes of a cell using the identify tool, select the
record for “Attributes for Migratory Landbird Stopover Habitat Data”
(dataset must be turned on). Attribute definitions can be found in
the Attachments tab on Data Basin or in the metadata available in
the download package."
|
| Theme/Category |
Environmental |
| Period Coverage |
Autumn 2008 - 2014 |
| Spatial Coverage |
12 northeastern US states from Virgina to Maine |
| Keywords |
migration, bird, stopover, ecology, distribution, wildlife,
conservation
|
| Landing Page |
https://nalcc.databasin.org/galleries/f5cc97e920ec49dfb76bc039a53c3e0a#expand=159202
|
| Access URL |
https://nalcc.databasin.org/galleries/f5cc97e920ec49dfb76bc039a53c3e0a#expand=159202
|
| Creator |
|
| Publisher |
|
| Released Date |
1/30/18 |
| Updated Date |
4/9/18 |
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
1 |
| Distribution Format |
ArcGIS shapfile |
| Publication |
McLaren, J. D., J. J. Buler, T. Schreckengost, J. A. Smolinsky, M.
Boone, E. E. van Loon, D. K. Dawson, E. L. Walters. 2018. Artificial
light confounds broad-scale habitat use by migrating birds. Ecology
Letters 21:356-364.
http://onlinelibrary.wiley.com/doi/10.1111/ele.12902/full
|
| Software to view the data |
|
| Project |
| Title |
Validation of NEXRAD data and models of bird migration
stopover sites in the Northeast U.S.
|
| Description |
This project, led by Jeffrey Buler of the University of
Delaware with a number of colleagues, fills a key gap in our
understanding of stopover habitat for migratory landbirds. It
provides a large-scale perspective on important sites for
migrants across multiple states in the Eastern U.S. Using
innovative analyses of weather radar data to detect migrating
birds, coupled with field surveys, the reports make
predictions about the importance of sites for migrants across
the Northeast and Mid-Atlantic U.S. “Importance” is defined
here by the relative number of birds that stop over throughout
the migratory season and how consistently birds depart sites
from day to day. Areas with the highest and most consistent
bird densities are considered to be of greatest stopover
importance.
|
|
| Principal Investigator |
Dr. Jeff Buler
|
|
| Title |
Cooperative Congressional Election Study (CCES) 2018 |
| Description |
The Center for Political Communication (CPC) purchased two modules
on the CCES, a nationally-representative survey of U.S. residents.
The CCES data include "common content" questions asked of
respondents across all modules; the CPC-specific items were asked of
two modules of 1,000 respondents each.
|
| Theme/Category |
Political |
| Period Coverage |
Fall 2018 |
| Spatial Coverage |
National U.S. |
| Keywords |
|
| Landing Page |
https://cces.gov.harvard.edu |
| Access URL |
|
| Creator |
|
| Publisher |
|
| Released Date |
|
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Restricted public (Dataset is available under certain use
restrictions)
|
| Version |
|
| Distribution Format |
SPSS, Stata, or csv |
| Publication |
|
| Software to view the data |
|
| Project |
| Title |
Center for Political Communication |
| Description |
The CPC is a nonpartisan, interdisciplinary center connecting
academics, students, and the community to relevant issues in
political communication. Since its creation, the CPC
consistently touches on issues that are part of, or about to
be part of, the national conversation. Whether it is racial
injustice, climate change, polarization, or the future of our
democracy, the CPC provides context through courses, research,
and programs.
|
|
| Principal Investigator |
Dr. Phil Jones |
|
| Title |
Delaware Environmental Observing System (DEOS): Station Data |
| Description |
Environmental data for the last 24 hours for all real-time data
networks, including the DEOS, Delaware Department of Transportation
(DelDOT), Delaware National Estuarine Research Reserve (DNERR) Water
Quality, National Data Buoy Center (NDBC), National Weather Service
(NWS), and United States Geological Survey (USGS) stream and tide
gauge networks.
|
| Theme/Category |
Environmental |
| Period Coverage |
Last 24 hours |
| Spatial Coverage |
New Castle, Delaware |
| Keywords |
environment, monitoring, climate, atmosphere, temperature, rain,
wind
|
| Landing Page |
http://www.deos.udel.edu/data/
|
| Access URL |
http://www.deos.udel.edu/station/index.php?station=DAGF
|
| Creator |
Center for Environmental Monitoring & Analysis (CEMA) |
| Publisher |
Center for Environmental Monitoring & Analysis (CEMA) |
| Released Date |
|
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
PNG, JPEG, SVG, PDF, CSV, XLS |
| Publication |
|
| Software to view the data |
|
| Project |
| Title |
Delaware Environmental Observing System |
| Description |
For over 15 years, DEOS has been providing real-time and
archived daily and monthly environmental conditions for
Delaware and the surrounding region. Today, DEOS operates and
maintains over 80 environmental monitoring platforms and
brings in data from over 200 additional environmental
monitoring platforms throughout our region.
|
|
| Principal Investigator |
Dr. Kevin Brinson
|
|
| Title |
Delaware Environmental Observing System (DEOS): Latest Conditions
|
| Description |
A map and table of the most recent conditions at each of the
networks for Meteorological, Hydrological, Wave, and Water Quality
parameters.
|
| Theme/Category |
Environmental |
| Period Coverage |
Past 3 hours |
| Spatial Coverage |
New Castle, Delaware |
| Keywords |
Air Temperature, PAR, Visibility, 1-Hr Precipitation, 24-Hr
Precipitation, Volumetric Water Content (2 in.), Soil Temperature (2
in.), Dew Point, Relative Humidity, Wind Speed, Wind Direction, Wind
Gust, Pressure, Wind Chill, Heat Index, Solar Radiation,
|
| Landing Page |
http://www.deos.udel.edu/data/
|
| Access URL |
http://www.deos.udel.edu/data/network_summary.php
|
| Creator |
Center for Environmental Monitoring & Analysis (CEMA) |
| Publisher |
Center for Environmental Monitoring & Analysis (CEMA) |
| Released Date |
|
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
|
| Software to view the data |
|
| Project |
| Title |
Delaware Environmental Observing System |
| Description |
For over 15 years, DEOS has been providing real-time and
archived daily and monthly environmental conditions for
Delaware and the surrounding region. Today, DEOS operates and
maintains over 80 environmental monitoring platforms and
brings in data from over 200 additional environmental
monitoring platforms throughout our region.
|
|
| Principal Investigator |
Dr. Kevin Brinson
|
|
| Title |
Delaware Environmental Observing System (DEOS): Daily Summary |
| Description |
Daily meteorological summary data for the DEOS and DelDOT networks.
|
| Theme/Category |
Environmental |
| Period Coverage |
2004 to present |
| Spatial Coverage |
New Castle County, Delaware |
| Keywords |
Air Temperature, PAR, Visibility, 1-Hr Precipitation, 24-Hr
Precipitation, Volumetric Water Content (2 in.), Soil Temperature (2
in.), Dew Point, Relative Humidity, Wind Speed, Wind Direction, Wind
Gust, Pressure, Wind Chill, Heat Index, Solar Radiation
|
| Landing Page |
http://www.deos.udel.edu/data/
|
| Access URL |
http://www.deos.udel.edu/data/daily_retrieval.php
|
| Creator |
Center for Environmental Monitoring & Analysis (CEMA) |
| Publisher |
Center for Environmental Monitoring & Analysis (CEMA) |
| Released Date |
|
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
|
| Software to view the data |
|
| Project |
| Title |
Delaware Environmental Observing System |
| Description |
For over 15 years, DEOS has been providing real-time and
archived daily and monthly environmental conditions for
Delaware and the surrounding region. Today, DEOS operates and
maintains over 80 environmental monitoring platforms and
brings in data from over 200 additional environmental
monitoring platforms throughout our region.
|
|
| Principal Investigator |
Dr. Kevin Brinson
|
|
| Title |
Delaware Environmental Observing System (DEOS): Monthly Summary
|
| Description |
Monthly data summaries for networks archived for historical use by
DEOS.
|
| Theme/Category |
Environmental |
| Period Coverage |
2004 to present |
| Spatial Coverage |
New Castle County, Delaware |
| Keywords |
Air Temperature, PAR, Visibility, 1-Hr Precipitation, 24-Hr
Precipitation, Volumetric Water Content (2 in.), Soil Temperature (2
in.), Dew Point, Relative Humidity, Wind Speed, Wind Direction, Wind
Gust, Pressure, Wind Chill, Heat Index, Solar Radiation
|
| Landing Page |
http://www.deos.udel.edu/data/
|
| Access URL |
http://www.deos.udel.edu/data/monthly_retrieval.php
|
| Creator |
Center for Environmental Monitoring & Analysis (CEMA) |
| Publisher |
Center for Environmental Monitoring & Analysis (CEMA) |
| Released Date |
|
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
|
| Software to view the data |
|
| Project |
| Title |
Delaware Environmental Observing System |
| Description |
For over 15 years, DEOS has been providing real-time and
archived daily and monthly environmental conditions for
Delaware and the surrounding region. Today, DEOS operates and
maintains over 80 environmental monitoring platforms and
brings in data from over 200 additional environmental
monitoring platforms throughout our region.
|
|
| Principal Investigator |
Dr. Kevin Brinson
|
|
| Title |
Delaware Environmental Observing System (DEOS): AgWeather Summary
|
| Description |
Monthly AgWeather data for a subset of DEOS weather stations. These
summaries agriculturally important data like reference
evapotranspiration, growing degree days, and soil moisture and soil
temperature values where these are available.
|
| Theme/Category |
Environmental |
| Period Coverage |
2004 to present |
| Spatial Coverage |
New Castle County, Delaware |
| Keywords |
Air Temperature, PAR, Visibility, 1-Hr Precipitation, 24-Hr
Precipitation, Volumetric Water Content (2 in.), Soil Temperature (2
in.), Dew Point, Relative Humidity, Wind Speed, Wind Direction, Wind
Gust, Pressure, Wind Chill, Heat Index, Solar Radiation
|
| Landing Page |
http://www.deos.udel.edu/data/
|
| Access URL |
http://www.deos.udel.edu/data/agirrigation_retrieval.php
|
| Creator |
Center for Environmental Monitoring & Analysis (CEMA) |
| Publisher |
Center for Environmental Monitoring & Analysis (CEMA) |
| Released Date |
|
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
|
| Software to view the data |
|
| Project |
| Title |
Delaware Environmental Observing System |
| Description |
For over 15 years, DEOS has been providing real-time and
archived daily and monthly environmental conditions for
Delaware and the surrounding region. Today, DEOS operates and
maintains over 80 environmental monitoring platforms and
brings in data from over 200 additional environmental
monitoring platforms throughout our region.
|
|
| Principal Investigator |
Dr. Kevin Brinson
|
|
| Title |
Delaware Environmental Observing System (DEOS): Satellite Data
|
| Description |
The University of Delaware Satellite Receiving Station (UDSRS)
provides satellite data for both geostationary and polar orbiting
satellite missions. Visible, infrared, water vapor, and other
imagery layers are available through the UDSRS website.
|
| Theme/Category |
Environmental |
| Period Coverage |
|
| Spatial Coverage |
Conus, Mid-altantic |
| Keywords |
X-Band, MODIS, L-band, NOAA, MetOP, and Fung-yen satelltes |
| Landing Page |
http://www.deos.udel.edu/data/
|
| Access URL |
http://udsrs.udel.edu/ |
| Creator |
Center for Environmental Monitoring & Analysis (CEMA) |
| Publisher |
Center for Environmental Monitoring & Analysis (CEMA) |
| Released Date |
|
| Updated Date |
|
| Publishing Frequency |
|
| Access Rights |
Public (Dataset is or could be made publicly available to all
without restrictions)
|
| Version |
|
| Distribution Format |
|
| Publication |
|
| Software to view the data |
|
| Project |
| Title |
Delaware Environmental Observing System |
| Description |
For over 15 years, DEOS has been providing real-time and
archived daily and monthly environmental conditions for
Delaware and the surrounding region. Today, DEOS operates and
maintains over 80 environmental monitoring platforms and
brings in data from over 200 additional environmental
monitoring platforms throughout our region.
|
|
| Principal Investigator |
Dr. Kevin Brinson
|
|