Disaster Management Milestone 2 (1)
docx
keyboard_arrow_up
School
Greenfield Community College *
*We aren’t endorsed by this school
Course
101
Subject
Geography
Date
Dec 6, 2023
Type
docx
Pages
5
Uploaded by PresidentMetal11647
Disaster Management: Meltdown at the Palo Verde Nuclear Generating Station
Nicole McMahon
Southern New Hampshire University
IT-242-Q7543 Intro to Geographic Info Sys 23EW2
Professor Terrence Mentzos
November 19, 2023
II.
Data
A.
Spatial Data:
There are numerous spatial datasets that can be used to address
the potential problem of a meltdown at the Palo Verde Nuclear Generating
Station. First is air quality monitoring data which includes real-time sensor data
of air quality, which includes indications of chemicals or toxins that may be an
issue.
This data helps identifies areas of potential impact and determine
decisions of evacuation and containment (EPA, 2023).
Second is weather and
environmental spatial data. This dataset shows weather patterns that may help
spread radiation due to factors such as direction of wind, rain, or snow.
Understanding weather conditions help to plan for emergency response
strategies and predict future exposure (U.S Department of Commerce, 2023).
Lastly,
spatial data from the Census Bureau is necessary to have to create an
adequate emergency response plan, this date tells us about population and
infrastructure and informs us of the potential impact of lives by showing
population density. We can plan for proper evacuation routes if we know the
areas that are highly populated.
By adding infrastructure data, we can locate
emergency shelters and hospitals. We can properly plan for emergency response
by having the appropriate datasets added into our platform, it helps with
coordinating effective emergency response and effective evacuation and routes.
Data for disaster management at nuclear facilities is different from other types
of spatial data because of the risks of danger that we have in the event of a
possible nuclear meltdown. This type of spatial data must include radiation
dispersal patterns, potential exposure zones, and the real-time monitoring data is
necessary to be able to have an effective emergency response plan.
B. Organization:
This data should be organized into layers and overlays which
would allow for multiple datasets to be used at the same time. These datasets
will help identify impact areas and areas of high risk. Radiation monitoring
datasets should include locations of monitoring stations, real-time sensor data,
and the historical radiation levels of the projected area. By adding real-time
sensor data, radiation levels can be monitored and allows for immediate
response to aid in the change of levels of radiation distribution. Weather and
environmental data can help emergency response teams plan for the potential
dispersion of radioactive materials. Also, by implementing weather data into
GIS can monitor wind and other weather changes that may affect areas that may
be in the impact zone of radiation exposure. To plan for proper evacuation
routes and emergency response, population and infrastructure databases are
important to implement. These databases contain critical information such as
population distribution, emergency shelters, and hospitals. Evacuation routes
and emergency locations can be added an overlay in GIS to plan for effective
emergency response procedures. The type of spatial data affects method
organization because most of the data is needed to accommodate real-time
updates. The purpose of this to make sure that responders have current
information to make adequate change based off changing conditions. By adding
different lays of topography, wind, and infrastructure locations it helps us
understand how these all affect conditions in the chance of a nuclear meltdown.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
Properly organizing spatial data makes accessing critical information during a
emergency situation more methodical and better decisions making will happen
that can lessen the impact and damage of a meltdown at Palo Verde Nuclear
Generating Station.
C. Quality:
The data that comes from these three types of datasets are reliable
because they come from Government Agencies. When reading data from real-
time datasets, it is important to validate the accuracy of the data to ensure that
the information is accurate. Understanding the methods used to collect the data,
equipment that is used, and quality control measures that are in place are
important to understand the information that the agencies are documenting.
Checking multiple sites that use real-time data is beneficial to check for
inconsistencies
.
The type of information that the spatial data is reporting, air
quality, population, and climate are crucial pieces of information that requires
accuracy. Considering that the datasets are from government agencies and after
being validated for accuracy and consistency, it is safe to assume that the quality
of information given is good.
References
Bureau, U. C. (2023, October 31). Population projections datasets. Census.gov.
https://www.census.gov/programs-surveys/popproj/data/datasets.html
EPA. (2023).
Interactive map of air quality monitors | US EPA
. Outdoor Air Quality Data.
https://epa.maps.arcgis.com/apps/webappviewer/index.html?
id=5f239fd3e72f424f98ef3d5def547eb5&extent=-146.2334,13.1913,-46.3896,56.5319
U.S Department of Commerce. (2023). Climate Data Online: Dataset Discovery. National
Oceanic and Atmospheric Administration.
https://www.ncdc.noaa.gov/cdo-web/datasets