Promoting Earth Systems Science Education using GeoSpatial Technologies

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Promoting Earth Systems Science Education using
GeoSpatial Technologies

• presented by
• John D. Moore
• Teacher of Geoscience and Remote Sensing
• Burlington County Institute of Technology
• Medford, New Jersey USA
• jdmoore_at_bcit.cc

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Outcomes for Session

• Develop an Understanding of Observing Earth
  as a System
• Introduce Geographic Information Systems (GIS)
  and Global Positioning Systems (GPS)
• Explore Sources of Real-Time Earth Data
• Enhance Critical Thinking Skills and Scientific
  Inquiry through the Space to Earth Earth to
  Space (SEES) Model using Geospatial Technologies
• Examine the components of Geospatial Technology
  and the implications to Workforce Readiness

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Shift in the Paradigm

• Science Education
• Environmental Education
• Technology Education
• Geography Education

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Earth Systems Education

• Atmosphere
• Geosphere
• Biosphere
• Hydrosphere

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Geographic Information Systems (GIS)

• Visual representation of Data Sets
• Layers (Themes)
• Geo-referencing (GPS)
• Analyze (Query) GeoSpatial Data
• Geospatial Thinking

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Identifying Sources of Real Time Data and Imagery

• National Aeronautics and Space Administration
• National Oceanic and Atmospheric Administration
• United States Geological Survey
• Environmental Protection Agency
• Digital Library for Earth Systems Education
• GLOBE Program
• Others

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SPACE-EARTH EARTH-SPACE

• SEES Model
• Students now have the ability to
• examine a geo-referenced location from the
• top-down and bottom-up

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Space to EarthEarth to Space SEES Model

• Examines a geo-referenced location from the
  top-down and bottom-up
• Fosters Geospatial Thinking
• Identifies geo-referenced data points/sources
• Incorporates Real-time Data

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Comparison of GLOBE Student Data to Satellite
Imagery, Remote Sensing and Computer
Visualizations

• GLOBE Student Research Project
• Global Learning Expedition II
• Sibernik, Croatia
• July 2003

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DATA SUMMARY Part 1Atmosphere
GLOBE Student Atmosphere Data (Fig.1)
This figure represents a student data set that
has been documented on the GLOBE Program website.
Student observations for specific dates and
locations can be/were recorded and retrieved via
the Internet.  
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Incorporation of Ground Truth Observations (Fig.
2)
  This image represents a local GOES image of New
Jersey, and more specifically the star represents
BCITs geographic location. Notice that a digital
photograph of the ground view (EARTH) has been
overlaid. The results of the student ground
observations are included in the box (circled and
yellow arrow). As you can see the cloud cover
(CVC) is isolated and the cloud type is cirrus.
By simply clicking on the star, BCITs data, both
observations and metadata, can be displayed for
researchers to compare with the satellite image
in the background.  
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NOAA GOES Image for November 11, 2002 (Fig. 3)
    This snapshot view shows an imported
satellite image in the background with our Cloud
model overlain, which consists of five USA GLOBE
schools represented by stars.
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GLOBE Computer Visualization November 11, 2002
(Fig. 4)
          This is a GLOBE computer visualization
representing all GLOBE student data for November
11, 2002. A visual comparison can be made
between the two data sets (GOES Imagery and
GLOBE).  
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GLOBE Student CLOUD Observations/Data (Fig.5)
      In order to create an accurate cloud model,
observations from both satellite and students
must be taken approximately around the same time,
but in this case, the GOES image was taken at
Solar Noon (UTC) give or take a few minutes.
Furthermore, since any atmospheric observation
must be entered within an hour of Solar Noon, it
puts to rest any time issue. This spreadsheet
represents one school week of observations from
five schools between the dates of November 11-15,
2002. This chart compares Clouds at a
geo-referenced point to GOES Imagery, and the
students ground truthed observations, (see
Fig.3). By simply computing of not verified over
the verified resulted in a value of 88.
Therefore, this table demonstrates that, both
school and satellite observations are consistent
88 of the time. The 12 error could be
attributed to the window of time difference
discussed earlier.
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DATA SUMMARY Part 2 Land Cover
GLOBE Student Land Cover Data MUC
Classifications (Fig. 6)
        This data represents BCIT Land Cover
Observations from the EARTH of the study site,
which can be obtained through the GLOBE website.
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World Land Cover as Viewed from SPACE (Fig. 7)
    This SPACE image from the NASA Earth
Observatory shows global land cover. Notice that
BCIT is geo-referenced (yellow circle), showing
rather green land cover, signifying vegetation.
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LANDSAT Image Bands 3-2-1 (Fig. 8)  
  This image from SPACE is a visible image.
Notice the theme is checked for a LandSat with
bands 3-2-1. Once again, BCIT is starred and
circle for quick geo-referencing.
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LANDSAT Image 4-3-2 (Fig.9)
    Unlike the previously image that has only
bands 3-2-1, this 4-3-2 band image highlights
vegetation. Notice the deep reds and greens are
now displayed in the BCIT area signifying mixed
development and vegetative land cover.
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LANDSAT 3-2-1 A Closer View (Fig. 10)
    BCIT can now be easily located and compared
to the surrounding environment. Notice the
considerable open space and suburban sprawl. BCIT
is on the edge!
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Aerial Photograph A Higher Resolution (Fig. 11)
    BCIT and the surrounding land cover can now
more easily been seen due the higher resolution
available through aerial photography. The land
cover observations continue to support each
other. Also notice, the BCIT Aerial theme is now
checked (displayed).
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GIS Land Cover Synopsis (Fig. 12)
    This GIS representation demonstrates a
consistent view of the BCIT land cover. An aerial
image, digital aerial photograph, clearly depict
what the region looks like. The displayed
attribute table shows the GLOBE data, i.e. MUC
824, cultivated land, non-agriculture.  
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DATA SUMMARY Part 3 Elevation
2m Topographic Image (Fig. 13)
    This image is a USGS the topographic map of
the BCIT (Medford, NJ) area. Notice the numbers
circled in red and pointed to by a yellow area.
These numbers represent elevation in feet for
that point. GLOBE default value of elevation for
BCIT is 17m. That number translates to about
55ft. Thus the 55ft elevation falls within the
number range of the outside numbers. Now we can
use the equation (AB, BC, and thus AC) where A
equals the elevation of the school, B equals the
topographic image provided by the USGS, and C
(see next page) would equal the digital elevation
map from the same source USGS.  
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USGS Digital Elevation Map (Fig. 14)
    This snapshot displays an elevation map
generated by the USGS. In our equation, this map
would equal (C) and so since (B) is the
topographic image, developed by the same people
(USGS), they would be equal. Therefore BC and as
indicated before that A (GLOBE School) equaled B,
then you can rightly assume that A (The School)
equals C (USGS elevation map). The circle and
arrow point out the study area for the GLOBE
Student Observation comparison. This study area
was chosen due to the extreme topographic nature
of the region. Notice BCIT is geo-referenced by
the blue star.
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Overlay of GLOBE Student Topographic Data (Fig.
15)
    ArcView was used to interpret the GLOBE
School elevation data to create contour lines.
These contour lines are then overlaid over the
elevation map so that the school data (contour
lines) can now be compared to the USGS elevation
map. Although there is no legend for the
elevation map, the GLOBE School data (contour
lines) now acts as the legend for the elevation
map, as indicated by the area. The number values
are in meters. A strong correlation obviously
exists. It is therefore concluded that there
exists a consistency between the GLOBE data and
the USGS elevation map.
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3D Representation of Study Area (Fig. 16)
    Using ArcViews 3D analyst, we can now create
a digital elevation model using the GLOBE school
data. Without even being there, the user can get
a feel for what the terrain really looks like. In
this particular snapshot, the sun is hitting the
terrain from Northwest at an angle of 45 degrees.
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Exploring the Role ofGeospatial Technologies in
the Classroom

• HOMELAND SECURITY
• AN ENVIRONMENTAL IMPACT ASSESSMENT
• USING REAL TIME EARTH DATA
• Intergraph Corporation
• Educational Best Practices Award 2004

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 Figure 1 Shown here is an aerial photography
image of the local area surrounding the crash
site. The crash site, illustrated by the red dot,
is determined by GPS and thus provides a precise
location in relation to its surroundings. The
highway on the top is I-295, the lower, NJ
Turnpike. The intersecting body of water is the
Rancocas Creek. 
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Figure 2 Within minutes, Doppler Radar is
accessed from the National Weather Service
Forecast Office, Mt. Holly, NJ. The real-time
image plotted in reference to the crash site. A
shower is forecasted to move in from the
Southwest within the next 30 minutes. The blue
dots, shown at the center of the image, represent
WeatherNet stations in the area of the crash
site. This provides quick access to not only
weather, but contact information as well.
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 Figure 3 This image shows wind speed and
direction. A little toward the right in the
center of the image are AWS WeatherNet stations
illustrated by the green dots. It is these dots,
or points of data, that allow access to weather
data for that region such as the wind data shown
here and the previous Doppler Radar Image (Fig.
2). Thus from this we can easily visualize where
the hazardous contents would go if they were to
be ignited and released into the atmosphere.
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Figure 4 An AWS WeatherNet School site is
identified, real time weather data can be
obtained and monitored through this site. This
picture displays current meteorological
conditions including temperature, humidity, wind,
rain, and atmospheric pressure.
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Figure 5 The population census data (indicated
by the contour lines) is overlaid in accordance
to the crash site. We can see that the crash site
falls within a certain census tract in which the
user is able to access population statistics
about the immediate area. In this case, 7,217
individuals live in the selected area.
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Figure 6 Here is a more accurate depiction of
affected census tracts surrounding the crash.
Because the winds are blowing from the Southwest
(see Fig. 3), the area is selected according the
location of the crash site and the winds
direction and speed. Therefore, to select census
tracts to the Southwest of the crash site are
required at this time. Instead, selecting areas
to the Northeast focuses more on the affected
population. 
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Figure 7 Pulling back even further, a View from
Space, is Burlington County, New Jersey as seen
through the NASAs LandSat satellite, which
depicts land cover. As one can see, there is a
multitude of real-time environmental/earth data
sites. Blue points represent AWS WeatherNet
sites, and the red points represent GLOBE Program
Schools. Contact information is available for
each of these geo-referenced locations.
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Figure 8 In this picture, both schools (green
markers) and hospitals (red markers) are plotted
so that the necessary steps can be taken putting
a regional Medical Emergency Plan into action.
Notice the concentration of schools toward the
northwestern part of Burlington County.
Therefore, these are the primary candidates to be
in close communication with, and also represent
an area of high population density. Furthermore,
notice the number of hospitals and where they are
located in the area. A conclusion could be drawn
that these hospitals would be involved in any
medical emergency because of their close
proximity to the affected population thus
leading to quick emergency medical treatment.
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Figure 9 Pulling back to an aerial view,
alternative traffic patterns can be identified
and established. Fortunately, I-295 and the NJ
Turnpike parallel each other in this region,
enabling law enforcement officials to quickly
re-route traffic and eliminating a huge
congestion problem.  
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Figure 10 Here you can see that I-295 southbound
traffic can pass the accident site, red point
circled in yellow, with minimal loss of time,
re-entering I-295 at the next Exit south of this
picture. North bound traffic could easily be
diverted as well to relieve massive delays, or if
determined to be required for health/safety
reasons.  
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Conclusions

• Incorporation of Satellite Imagery, Real-Time
  Data, Remote Sensing Technology, and Computer
  Visualizations in the K-12 classroom lead to true
  inquiry
• Earth Systems Education demonstrates the
  interrelationships of the Geosciences
• Incorporation of GeoSpatial Technologies in
  student learning fosters Geospatial Thinking
• Whats next? Opportunities for International
  Project Based Learning

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Contact Information

• John D. Moore
• Teacher of Geoscience and Remote Sensing
• Burlington County Institute of Technology
• 10 Hawkins Road
• Medford, New Jersey 08055 USA
• jmoore_at_bcit.cc