Clients have indicated an
interest in several potential projects on the following pages. Choose one of the following projects
and prepare a “prospectus” describing and demonstrating your proposed solution
as outlined in the following guidelines.
It is expected that your prospectus report will be professional, free
of grammatical and spelling errors, well-organized, clearly written, and
succinct. It will include:
·
Title “Page” with a very brief (single paragraph) statement of
the problem and proposed solution.
·
Table of Contents with internal hyperlinks to the report headings
(including appendix sub-headings).
·
Body
of the report organized by the headings of Introduction, Approach,
Data Requirements, Prototype Results, Additional
Considerations and Conclusion written for a non-technical reader.
·
Appendix containing step-by-step description of the implementation of the prototype
model written for a GIS-technical reader.
It is CRITICAL to
keep in mind that your report is addressing two distinctly different
audiences—1) “Big Guy” who is interested in the
“100,000-foot view” of the approach and logic behind your solution, and
2) “Techy Guy” who is very interested in the step-by-step
procedures demonstrated in your prototype solution.
The body of the
report is for Big Guy and should be
about approximately 3000 words (10 pages or less) and include only
figures/tables that contribute to the discussion, such as a generalized
flowchart of the solution and important maps critical to explaining the major
steps in the approach. Keep in mind that
“default working map displays are rarely appropriate” for getting the big picture
across to Big Guy about the results and their interpretation/utility. Make sure each figure has a figure number,
title and short caption and is adequately discussed in the text
of the report.
The appendix of
the report is for Techy Guy and can be as
large as you deem appropriate. It should
contain a detailed flowchart extending the generalized one presented in
the body of the report by including pertinent information on the input map(s),
analysis operation and output map for each major step in your
proposed solution.
Use Web Layout
view in Word to prepare your report.
Attach an electronic version of the annotated MapCalc script you develop
as a separate file included with your report (Exercise6_<names>.txt) and
submit by Sunday, February 21, 5:00 pm.
________________________
Note: General
clarification, questions and Life-line requests (see below) will be processed via
email (jberry@innovativegis.com)
weekdays 8:00am-4:00pm and 9:00-11:00am on Saturday/Sunday. It behooves you to identify a team (2-3
individuals), decide on a project, and then start outlining a solution as
soon as possible.
There is a “Life-Line”
if you get totally stuck. For the price
of one grade (drop from 100% possible to 89% possible) I will email you a
MapCalc script with the complete solution—you “just” need to write-up the
solution in a “professional, free of grammatical/spelling errors,
well-organized, clearly written, and succinct” manner that demonstrates your understanding of the processing.
Example Project – with hyperlink to a graded report (A-) from a previous class to serve as
a “benchmark”
Project 1 — Extended
Hugag Habitat
Project 2 — Timber
Harvesting Visual Exposure
Project 3 — Emergency
Response
Project 4 —
Geo-business Analysis
Project 5 — Landslide
Susceptibility
Project 6 —
Transmission Line Routing
Project 7 — Wildfire
Risk Analysis
Project 8 — Pipeline
Spill Migration
Project 9 — Forest
Biomass Accessibility
Example Project
Landfill Siting (use Tutor25.rgs). The
Garbage R’ Us consulting company has
approached you about sub-contracting the
|
Criteria |
Specifications
(1= worst … 9= best) |
Overall Weighting |
|
Gently sloped |
1 = >20 percent slope 5 = 10-20 9 = <10 percent slope |
6 Times |
|
Near roads |
1 = >5 cells away 5 = 3-5 9 = <3 cells away |
2 Times |
|
Away from water |
1 = <3 cells away 5 = 3-5 9 = >5 cells away |
4 Times |
|
Not too visually exposed to roads |
1 = >20 exposure 5 = 7-20 9 = <7 exposure |
1 Times |
|
Not in areas of high housing density (total; within
3) |
1 = >12 houses 3 = 6-12 7 = 3-6 9 = <3houses |
2 Times |
|
On appropriate soils |
0 = 0 open water 1 = 4 upland 3 = 1 floodplain 7 = 3 terrace 9 = 2 lowland |
8 Times |
|
|
|
|
|
Steepness constraint |
1 = <50 percent slope
(OK) 0 = >50 percent slope
(Illegal) |
Legal Imperative |
|
Proximity to water constraint |
1 = >1 cells away (OK) 0 = <1cells away
(Illegal) |
Legal Imperative |
Your charge is to prepare a
prospectus for deriving the Landfill Suitability map that clearly
explains how each of criteria are evaluated and then combined into an overall
suitability map that respects the legal constraints and reflects the county
commissioners’ criteria weightings.
In addition, calculate the
average landfill suitability rating for each district (Districts map). Finally,
generate a map that identifies the average rating within 300 meters (3-cell
reach) for each of the housing locations (Housing
map).
_____________
Note: see the class website (or
The layout and
comments in the graded example might be useful in preparing your
“take-it-to-the-next-level” report. Note
that the report is in Web Layout so you don’t have to worry about page breaks
and have an opportunity to use hyperlinks for sections and any critical
internal references.
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Project 1
Extended Hugag Habitat (use Tutor.rgs). The Fanatical
Hugag Protection Society was very pleased with the habitat rating model you
previously developed. Now they would
like to extend the rating model with some additional Hugag preferences as
described below and apply the model to a new area. Your charge is to incorporate the new
criteria employing the recent behavioral research into the existing model.
·
Near Water. Hugags prefer to
be near water with specific criteria of 9 (best)= 0 to 5 minutes away from
water, 7= 5 to 10 minutes away, 6= 10 to 15 minutes away, 3= 15 to 25 minutes
away and 1= more than 25 minutes away.
Friction for Hugag hiking under various cover type and slope class
combinations is shown below.
|
|
|
Covertype |
||
|
|
|
1= Open Water |
2= Meadow |
3= |
|
Slope
Classes |
10= Gentle (0 to 10%) |
0 (no go) |
1 min |
2 min |
|
20= Moderate (10 to 30%) |
0 (no go) |
2 min |
5 min |
|
|
30= Steep (30% or more) |
0 (no go) |
4 min |
8 min |
|
·
Out-of-Sight. Hugags
prefer to be out-of-sight of roads as much as possible with specific criteria
of 9 (best)= 0 to 5 times seen (visual exposure), 8= 5 to 10 times seen, 6= 10 to
30 times seen, 3= 30 to 50 times seen and 1= more than 50 times seen. They are big beasts with their eyes 6 feet
off the ground.
·
Near
·
Diverse Cover. Hugags
prefer to be in a diverse cover type setting with specific criteria of 9
(best)= three cover types, 5= two cover types, 1= one cover type within a 300
meter reach (3 cell reach).
·
Weighted Preferences. Recent
research suggests Hugag preferences for the seven habitat criteria are not the same
with specific criteria weightings for overall suitability of Gently Sloped= times 10, Southerly Aspect= times 2, Lower Elevations= times 1, Near Water= times 5, Out-of-Sight= times 5, Forest Edge= times 7 and Diverse
Cover= times 2.
The Fanatical Hugag
Protection Society is familiar with the original three-criterion habitat model
considering just slope, aspect and elevation.
Your report should emphasize how the new criteria and weighted
preference summary are integrated into the analysis and how much the new
considerations effect model results (comparison between the original and new
model results).
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Project 2
Timber Harvesting Visual Exposure (use Bighorn.rgs). As the result of an intensely passionate
meeting between the Visually Concerned community group and the Cut-out-Get-out
Timber Company, your See-All-there-Is-To-See consulting firm has
been approached to analyze the visual exposure of a new timber harvest plan to
areas of high human activity. They have
a somewhat foggy view that map analysis techniques can provide information on
the relative exposure for each of the harvest blocks, as well as identifying
the degree of exposure for each of the housing locations. It is your charge to develop a prototype
model that demonstrates applicable visual exposure analysis techniques that cut
through their hazy thinking with such clarity that they can see the impacts.
With a bit of whiteboard
thinking your project team has decided the initial analysis steps you need to
take are:
§
Use the Radiate
command to calculate a House_wVExposure surface identifying
weighted visual exposure map from the Houses map that identifies the
number of houses connected to each map location. Assume a 15 foot viewing height to simulate
second story viewing.
§
Use Renumber
to create a Binary_harvest_blocks masking map of the harvest
units on the Harvest_blocks map.
§
Use the Calculate
command with the Binary_harvest_blocks map and House_wVExposure
surface to identify a map of the House_wVExposure_Hblocks
depicting the visual exposure throughout each of the harvest blocks.
§
Use the Composite
command with the Harvest_blocks map and the House_wVExposure
surface to calculate a House_wVExposure_Hblocks_avg map
indicating the average visual exposure to houses for each of the harvest
blocks. Generate a table containing an
ascending list of overall harvesting visual impact on houses.
Repeat the processing
flow above to generate a Road_VExpose_Hblocks map (assume 4 feet
viewing height) and a Road_VExposure_Hblocks_avg map and an
ascending list of overall harvesting visual impact on roads. Assume all road locations are equally
weighted.
Finally, generate a map
that identifies THE INDIVIDUAL harvest block(s) that are visually connected to
each housing location. While the team
isn’t too certain about how to do this, the recent
As a tickler for enhancing the model, very briefly
discuss (do not implement) how you might include consideration of visual
screens (tree canopy height) and diminishing visual impact as line-of-sight
connectivity gets farther and farther away (increasing distance from viewer
locations).
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Project 3
Travel Impedance Weights |
||||||||||||||||||||||||||||||||
|
|
||||||||||||||||||||||||||||||||
|
Emergency Response Travel-time Map |
||||||||||||||||||||||||||||||||
Emergency Response (use Island.rgs). The leader of the Shangri-La
Project was hit by a bus before completing the project that would identify
off-road emergency response for the island.
His notes included the attached figure of the final map and some sketchy
comments about how it was prepared.
Your charge is to “pick-up-the-pieces” and complete the prospectus.
The
The sketchy
notes note that the spread was up to 200 minutes of travel (infinitely far
away). These inaccessible locations were
then renumbered to 0 while leaving all of the other travel time values intact
to generate the starter map for the second phase.
The second phase assumes the rescue team will
travel as far as possible on the ATV vehicles then proceed on foot into the
inaccessible areas. The Hiking_friction for determining this
phase is shown in the table on the left (assume no travel through water).
The notes emphatically suggested that the
“Explicitly” option to the Spread command was used for continuing the ATV
travel to the hiking phase. This option
causes the computer to start with the ATV travel time values and continue
“thru” the Hiking_friction to accumulate hiking travel time as it moves
into the inaccessible areas—the “explicitly” processing picks up travel time
where the ATV spread stopped.
The final step renumbers the hiking inaccessible
areas (to 200 values) to -2 to display locations that will require a special
climbing team to access. The Land_mask
was overlaid to assign -1 to the ocean areas and the user-defined display
ranges (5-minute intervals) and colors shown in the figure were applied
(Climbing Team Areas= gray, Ocean= blue and response time from green (short) to
red (long) with a yellow color inflection at the mid-range interval). Draping this information on a 3D plot of the
terrain surface will help the clients visualize the emergency response
information.
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Project 4
Geo-Business Analysis (use Smallville.rgs). Colossal
Mart recently moved into Smallville and Kent’s Emporium has approached you about helping them assess the
impact. Your analysis needs to address
couple of major concerns: relative travel time throughout the city from both
stores (Competition Analysis) and
areas of customer concentration (Density
Analysis). An old online paper
Shortcut Sam located (http://www.innovativegis.com/basis/Papers/Other/Retail/Where.htm)
and a “whiteboard discussion session” with your team resulted in an outline of
what needs to be done. Your charge is to
implement the draft model and prepare a prospectus for the client.
Competition Analysis
Part 1— Using the street map [SType, 1= Primary street= .15 minute to cross, 3= Secondary street=
.45 minutes to cross and 0= No street= 0 minutes to cross (absolute barrier)] calculate
two travel-time maps, one from Kent’s Emporium (Kents) and the other from Colossal Mart (Colossal), that identifies the number of minutes to travel from
anywhere in the city to the respective store.
(Hint: spread to 150 or more).
Part 2— Create a relative travel-time advantage map by
subtracting the travel-time maps to the two stores. Be sure to your display
clearly shows which store has the relative advantage by assigning green tones
to Kent’s advantage, red tones to Colossal’s advantage and light gray to
non-street areas.
Part 3— Generate a binary map identifying just the “combat”
zone where neither store has a strong advantage (-6 minutes to +6 minute
advantages).
Part 4— Generate a map identifying the customers (Total_customers) who reside in the
combat zone.
Density Analysis
Part 1— Create a customer density surface that identifies
the total number of customers within half a kilometer (500m= 5
cell-reach).
Part 2— Generate a binary map identifying the “pockets” of unusually
high customer density (mean + 1 Stdev or more customers per 500m reach).
Part 3— Generate a map that shows the relative travel-time
advantage within the pockets of unusually high customer density.
It is important that the prospectus identifies (but does not implement) further map analysis and modeling extensions that demonstrate the
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Project 5
Landslide
Susceptibility (use Tutor25.rgs). The Slippery Mountain
County planner has approached your Over the Hill company to prepare a
Slippery Mountain Landslide Susceptibility map for the county. The map needs to identify susceptibility ratings from 0= not susceptible, 1= minimally
susceptible to 9= extremely susceptible based on slope, soil and cover type
conditions. Specific criteria are shown
in the following table.
|
Rating |
Slope |
Soils |
Covertype |
|
0= Not Susceptible |
|
0= Open Water |
1= Open water |
|
1= Minimally susceptible |
0-5% |
|
|
|
2 |
|
1= Floodplain |
|
|
3= Low |
|
|
2= Meadow |
|
4 |
|
2= Lowland |
|
|
5= Moderate |
5-12% |
|
|
|
6 |
|
3= Terrace |
|
|
7= High |
12-30% |
|
3= |
|
8 |
|
4= |
|
|
9= Extremely susceptible |
>30% |
|
|
Overall landslide
susceptibility is defined as the weighted average rating of the three criteria
for each map location with the Slope rating most important (times 5), Soils
next (times 3) and Covertype least important (times 1). Be sure to “mask” the final map to force
areas of Open Water (lakes and ponds) to zero.
In addition, the
client wants a second map that identifies the susceptibility ratings for just
the uphill areas around roads to 250 meters (2.5 cells).
Finally, they need a map for the
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Project 6
Transmission Line
Routing
(use Bighorn.rgs). The Dewy,
Chetham and Howe Consulting firm has been awarded a large contract for
identifying potential routes for a power line connecting an existing route to a
proposed substation that will support a large development project in the
Bighorn area. A major consideration in
siting the power line is to minimize the visual impact of the route to roads
and housing in the area.
Their senior developer,
Sketchy, had nearly completed the prototype of the model before he disappeared
on a Himalayan trek. All of the files
were inadvertently erased but the following generalized flowchart of the
processing was saved.
In addition, “Sketchy’s”
notes make reference to the following considerations:
·
Derive weighted visual exposure to houses (number of Houses seen; AT 15)
·
Derive visual exposure to any road (number of Roads locations seen; AT 4)
·
Assign the data ranges on the Housing and Roads visual exposure maps into
equal intervals from 1= low to 9= high
·
Calculate arithmetic average of the two calibrated maps to generate a Discrete Cost map
·
Calculate an Accumulated Cost
surface based on the effective proximity from the existing Powerline using the discrete Cost
map as the friction surface
·
Identify the Least Cost Path
(steepest downhill path) from the proposed electrical substation (Power_substation map) along the
Accumulated Cost surface
The
client, MegaWatt Power, needs to identify three routes: 1) a route that treats
visual exposure from houses and roads equally (simple average Cost), 2) a route
considering visual exposure to houses ten times more important than exposure to
roads, and 3) a route considering visual exposure to roads ten times more
important than exposure to houses.
Sketchy’s
notes indicate that he also committed to delivering some very useful map
displays and tabular summaries:
·
Six individual map displays of each of the three routes where the map
values identify 1) the weighted visual exposure to houses and 2) the visual
exposure to roads along the route
·
An overall map identifying all three routes with a unique value assigned
to locations with more than one route (route coincidence) that indicates which
routes share a map location
·
A table identifying the maximum, average and standard deviation of the
simple average Cost associated with each route
Finally,
include a very brief discussion of how you could incorporate some other
factors that might be considered in routing the power line, such as terrain
steepness and proximity to roads and houses.
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Project 7
Wildfire Risk Analysis (use Tutor25.rgs). The Littleville Volunteer Fire Department
needs to develop a wildfire risk map and subsequent analyses that will help in
their response planning and mitigation efforts.
After considerable interaction with your Smokey the Barrier consulting firm they have asked you to develop a
prototype model that implements the initial scoping of the specification the
base maps of Elevation, Covertype and Roads.
- Terrain
Slope. Steeper slopes have higher risk— 9 (high risk)= >40%, 8= 30-40, 6= 20-30, 4= 10-20, 2= 5-10 and 1
(low)= 0-5%
- Terrain
Orientation. Southerly aspects have higher risks— 9 (high
risk)= S/SW, 8= SE, 6= E/W, 5= Flat, 3=
NW, 2= NE and 1 (low)= N
- Cover type. Forested locations have highest risk— 9
(high risk)=
- Proximity to
Roads. Closer
to roads have higher risk— 9 (high risk)= 0 cells away, 7= 1, 4= 2-3 and 1 (low)= >3 cells away
- Proximity to
Houses. Closer
to houses have higher risk— 9 (high risk)= 0 cells away, 8= 1, 6= 2, 4= 3-5 and 1 (low)= >5 cells
away
- Can’t Burn
Water. Masking
consideration— 0= Open Water (lake or pond) and the zero rating is “forced”
for these locations regardless of the calculated risk considering the other
criteria
The initial thinking was that
wildfire risk needs be summarized in a couple ways…
- Calculate the average wildfire risk for each of
the Littleville fire districts (Districts base map).
- Create a map that shows the calculated wildfire
risk for all locations within a 300 meter buffer (3 cells) around all
housing locations.
The fire fighters were
receptive to your “common sense” idea that locations closer to the fire station
at the Ranch community center (Locations base map; Ranch location) ought to
have the calculated risk lowered.
However, they are confused about how you would make the adjustment and
what impact it might have.
Subsequent thinking with your
project team mates on the solution suggested that that effective proximity should
reflect the following travel time based on the Roads and Covertype base maps:
1= 1 minute to traverse a road cell, 3= meadow, 7= forest and 0= open water
(absolute barrier). In turn, the travel
time map can be translating into a series of weighting factors that
progressively lowers the calculated wildfire risk as follows: 1.0= > 20
minutes away (no change), 0.9= 15-20, 0.8= 10-15, 0.75= 5-10 and 0.7= 0-5
minutes away. Multiplying the calculated
wildfire risk map times the weight map will lower the terrain, cover type and
human activity factors for the locations that have good fire fighting response
times. While this makes common sense you
and the team, a side-by-side display and brief discussion of the changes in the
project area between the “before weighting” and “after weighting” maps is
needed.
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Project 8
Pipeline Spill Migration (use GooseEgg.rgs). The Thickly Crude Pipeline Company has
contacted your Anything GIS
consulting company about the potential of using GIS modeling to delineate spill
path and determine impacts. The project
team’s subsequent research identified a generalized flow rate equation of —
Flow Rate = fn (physics, product properties and
terrain conditions)
= [Acceleration_gravity
* Flow_depth^2 * Specific_gravity * sin( Slope_angle )]
[Coefficient_viscosity * Friction_factor]
…with
the evaluation of the equation for flow velocity of water assuming
Acceleration_gravity= 9.801 m/sec^2, Flow_depth= 1 cm, Specific_gravity= 1
gm/cm^3, Coefficient_viscosity= 1 cp and the terrain Slope_Angle is specified
for each cell in a grid map (the .017453 value converts degrees to radians for
processing; PI/180) as—
Flow_rate_water= ( 9.801 * 1 * 1 * 1 * Sin( Slope_angle * .017453 ) ) / (
1 * 1 )
...and
conversion from meters/second flow to minutes to cross a 30m grid cell as—
Flow_friction_water= ( 30 / ( Flow_rate_water + .085 ) ) / 60
Armed with this physics
insight (Flow_friction_water map)
and the terrain surface (Elevation
map), the project’s overpaid consultant suggests that both a guiding surface
and an impedance map are needed to determine the effective movement of water as
the worst case scenario. Several
specific analyses need to be implemented to address the client’s interests in
spill migration modeling—
Identify the implied steepest
downhill spill path for each of the three test locations (Spills map) along the proposed new transmission pipeline and map as
a 3D Grid display with all three route individually identified and draped over
the Elevation surface.
Identify the minimum path
time for a spill anywhere along the entire Proposed route (Pipelines map) and map as a 3D Grid display with the spill density
map (10 Equal Ranges contours) draped over the Elevation surface.
Create a map that shows the
estimated minimum time for a spill based on the spill time map (created above)
to reach all of the impacted areas with the high population HCA (HCA_Hpopulation map).
To illustrate the model’s
sensitivity to different products create another minimum time map for the high population
HCA that considers crude oil flow instead of water with the following modified
flow equation—
Flow_rate_crude=
( 9.801 * 1 * 1 * 0.8518 * Sin( Slope_angle *
.017453 ) ) / ( 8.0 * 1 )
…and show the two maps
side-by-side for visual comparison.
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Project 9
Forest Biomass Accessibility (use Bighorn.rgs). Your “Are We Having Fun Yet?” GIS Modeling
Project team has been approached about a joint educational venture with the “Are We There Yet?” MBA Capstone Project
team:
As a requirement in
finishing our MBA program, myself and a group of three other students are
serving as consultants for a local non-profit dedicated to developing a
bio-mass solution regarding the Colorado Mountain Pine Beetle epidemic.
Through our research, your name was offered as a potential resource,
specifically with mapping.
As part of our project, we are in the process of identifying possible
staging areas for the removal of infected wood. Given our understanding
of your expertise, we are interested in overlaying infected areas in relation
to railroad networks, roads, power lines, watersheds, and other relevant
infrastructure that would allow us to create jobs, minimize forest fire risk,
increase energy independence, and reduce carbon emissions.
We would like to setup a meeting February 11, 12-4 pm in 126
Boettcher Center West, to further discuss the project and ways you may be able
to assist us in furthering the University of Denver’s collaboration with local
enterprises. -- Joseph K Salsich, M.B.A.
Candidate, 2010
Follow-up conversation noted
that their report will address—
·
business
considerations surrounding potential wood utilization products, such as
markets, price/cost structures, scale considerations, government subsidies and
regulations (bulk of the report),
·
as well as
recommendations about GIS-based approaches for 1) identifying beetle infested
areas that are suitable for remediation and 2) characterizing the relative
accessibility of these areas.
Some preliminary thoughts on
the GIS modeling application suggest two analysis scales. A macro
scale spatial analysis (1 kilometer spatial resolution) would utilize an
existing State-level beetle infestation severity map in conjunction with
infrastructure, population density, administrative boundaries and other map
layers to identify large candidate areas for potential wood removal (discrete
vector map layer). This phase would
emphasize broad economic, policy, regulatory, social and political concerns to
categorize and rank potential remediation areas throughout the State.
In turn, a micro scale spatial analysis (30
meter spatial resolution) would identify a consistent modeling methodology for
mapping relative suitability throughout these areas for wood removal on a
suitability scale of 0= unsuitable, 1=least suitable through 9= most suitable
(continuous grid map layer). This determination
would focus on considerations of terrain form (e.g., slope and surface
roughness), ecological types (e.g., forest and wildlife communities),
environmental concerns (e.g., surface runoff, stream proximity) and engineering
factors (e.g., road proximity and equipment capabilities/costs).
Further thinking notes that
the GIS modeling team could contribute in two ways—
1) Act as a “domain expert
resource” in scoping potential map analysis approaches and considerations for
the macro scale spatial analysis of
large candidate remediation areas (informal advising without formal
report).
2) Prepare a report
demonstrating and describing a prototype grid-based GIS model for the micro scale accessibility spatial
analysis.
The GIS modeling report will
conform to the GEOG 3110 Mini-Project Guidelines addressing two distinctly different audiences— 1) “Big
Guy” who is interested in the “100,000 foot view” of the approach
and logic behind your solution (forms the body of the report of about
2500 words), and 2) “Techy Guy” who is very interested in
the step-by-step procedures demonstrated in your prototype solution
(forms the appendix of the report).
The report is due by Sunday, February 21, 5:00 pm.
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