Lidar of Pensacola Florida

This module covers one common active sensor: LIDAR or Light Detection and Ranging.

LIDAR is an active remote sensing system that uses laser light instead of microwaves to illuminate the target area. The reading covered basic information on how these processes work and the benefits of each method. A decent bit of literature to read is the Airborne Altimetric LIDAR Tutorial. This tutorial gives an overview of how LiDAR works, how data is collected, how it is processed and the many applications for LiDAR.

Supervised Classification

The links posted below are for a map created using ERDAS IMAGINE 2010 software and the ground control points as part of the University of West Florida On-line Geographic Information Systems (GIS) Certification program class, Photo Interpretation and Remote Sensing (GIS4035/L). The links require Internet Explorer to open and display properly

Though the lab focused on a supervised classification, this module covers the different methods of classifying multispectral images into different patterns that represent clusters of statistically different sets of multiband data, which can be correlated into separable classes. The two main methods of classifying images are Unsupervised and Supervised Classification.

I found this lab more time consuming that expected.  I lost count of how many iterations were done to get to this point.  One thing that did work well for me was to create a flow chart for each of my steps and to take careful notes.  This ensured that precisely the same steps were taken for each class which intern created a MUCH more consistent set of results. Select .xps link below or .pdf map for a larger view. germantown_18d_classified.xps

GeoRectification

The links posted below are for a map created using ERDAS IMAGINE 2010 software and the ground control points as part of the University of West Florida On-line Geographic Information Systems (GIS) Certification program class, Photo Interpretation and Remote Sensing (GIS4035/L). The links require Internet Explorer to open and display properly.

This week's lab objective is learning to use control points from one image or map to rectify another image.  In this case we were provided a USGS map of Pensacola as our ground control point source.

Pensacola_Rectified image (bands 3,2,1)

In the "real" world, one always wants to check and recheck work before it is submitted.  This is a little bit of a challenge since the image is a much coarser resolution than what seems to be available on the map.  In this case the ground "truth" comes from the map. So once I was satisfied with the selection of the WHICH points were to be used I let the imagery point position float until I was satisfied with the visual position and RMS error. Click here for a view the ground control point results. 

Fast forward to the completed image you see below (left side).  The RMS was excellent, (<1), the coordinates seemed right so one more step was taken.  The rectified image and the map image were placed in separate windows, linked and inquire cursors activated.  Voila a perfect match.  I could also have dropped them in the same window and looked to see how they overlaid each other but that will have to be for another day.

Look at the cross hairs on both images.  They are centered on the runway intersections

Module 2 - LandSat Band Combinations

The links posted below are for maps created using ERDAS IMAGINE 2010 software as part of the University of West Florida On-line Geographic Information Systems (GIS) Certification program class, Photo Interpretation and Remote Sensing (GIS4035/L). The links require Internet Explorer to open and display properly.

This module covers satellite based sensors that operate in the visible in infrared wavelengths. 

"Features can be identified visually, by looking at the image, but also by examining the histograms under the layer information.  Certain features have definite and relatively constant reflective properties and therefore will always fall at a certain spot on the histogram.

In this exercise we examined the reflectance values found in the layer histograms to identify real features on the map." from lecture material

 Map of showing shadows on slopes of the Olympic Mountains using false Color Infrared (CIR).  I used layers 4, 3 and 2.  There was a spike between pixel values 12 and 18. 

 Map of Lake Tapps with dissolved calcium suspensions which appear as bright blue CIR and Black in layers 5 and 6. There was a spike around the pixel values of 9-11.

 Map of Grays Harbor shallow estuary showing basin bottom using the bathymetric combination with layers Red=3, Green = 2 & and Blue = 1.

Module 1 Challenge - I love Challenges

I am not sure why these are called "Challenges" rather than Labs but I like the idea. 

So this is the drill.
Import an image into Erdas Imagine 2010.
Then convert it to a map using some of the built in Erdas Imagine capabilitites.
Finally save it as a MS .xps file and publish it to a blog.
So click the link below and see what we can do!

Module_1_Challenge_AVM.xps

Final Project - Bobwhite Manatee Transmission line

Wow this was such a challenging project.  This project encompassed nearly everything we learned this semester.   This required research.  The primary tool was ArcGIS.  Support tools included Erdas Imagine MS Excel, Powerpoint and Word.

A PowerPoint presentation accompanied by a written slide‐by‐slide summary is required as the final deliverables

Carto Final Project. Mean SAT Scores and Participation Rates

Bottom line, I chose a B&W format since this was for a newspaper and it was not stipulated whether the paper would be color or B&W.

I will expand on this on Saturday.

Week 11 - Proposed Wind Turbine Locations

Ohio currently has some wind power producing capabilities. We are to study one existing wind farm and then use established criteria to determine if the Great Lakes should be the site of the next wind farm for the Midwest.

It turns out there are many sources of legitimate information about shipping lanes, average annual wind speeds, bird migration, parks, and more. For me, the issue was sifting through the volumes of data to get what I needed for the lab.
Some of the sources I used are: http://www.greenenergyohio.org/ , http://www.odh.ohio.gov/, www.bgohio.org/utility-director/trubines.html, and http://www.berr.gov.uk/energy/sources/renewables/planning/onshore-wind/ornithology/page18703.html.


I found the reading rather interesting.  There was a considerable amount of literature the could be summed up as "not in my back yard".  However, if one read all the available literature one would find most of the complaints or issues could be easily remedied.  In some cases, technology and creative thinking fixed things.  An example was noise from the turbine blades was lowered by doing three things.  Turning the turbine 180 desgree, eliminated much of the wind noise, as did restyling the blades. Finally, insulating the inside further elminated the noise so that it was no longer an issue.

Bowling Green site
Using Google Earth one can view two wind machines located near a landfill 6 miles southwest of Bowling Green, OH. Bowling Green is home to Ohio’s first utility-sized wind farm. There are four turbines that are 257 feet tall. These turbines are as tall as a 30-story building and generate up to 7.2 megawatts of power — enough to supply electricity for some 3,000 residents. Located about six miles from the city, the turbines can be seen for miles and have become a local attraction.


Lake Erie
I selected two sites on Lake Erie just north of Cleveland OH. I based the selection on the site assessment index from the BERR planning criteria. http://www.berr.gov.uk/energy/sources/renewables/planning/

- Average annual wind speed of between 16.8 and 17.9 mph
- There are no residences near the sites
- There are shipping ports but not in close proximaty but there are shipping routes near the site
- Positioned approximately 15 miles  from shore the coastal horizon is not impacted
- Natural habitats will not be affected

- Installation and constructions costs were a major reason for this selection
Some turbines have been shipped via the from Pensacola to Cincinatti. The proposed sites are near a shipping channel for that reason.  Additionally, notice the proposed sites are not in the highest wind areas since there was no financial gain for the higher speeds but there are higher construction costs.  Finally, the closer selection also means there will less energy loss via normal power transmissions.

Isohyet Precipitation Lines

This was another fun map. 

So since I had the same printer output issues noted on our discussion page I took another tack.  I selected a range of colors for the different rain levels.  In this case the colors chosen red for 70+ inches, purple for 60 inches etc.  It was actually very useful because the zones practically jumped off the page. 

Then I used the pencil tool to draw the lines and used an iterative approach to define the line  locations.  The first pass was the rough draft. Then subsequent iterations, I studied the location of the rain volumes and worked to get the proportional distances closer.  This meant, adding and deleting points on the isohyet lines.

I can see where one could get confused with which side of the line represents the isohyet line.  Consistency is key here. You will see that the volumes are generally above or inside the isohyet line.

I look forward to seeing your comments.

Bonus Exercise - Before and After

      Before                    and              After




I chose Percentile map from week 3 because I wanted make a better map product. I also wanted to see how and if a different presentation would change the intended message. Remember that the data is exactly the same as before.

I had some friends over tonight and asked their impression of the two maps. half preferred the Proportional Dot map and half leaned toward the Equal Interval map. This was a fun exercise and sparked a lot of discussion about map content.

My very informal poll of my house guests tonight suggested that the primary improvement seemed to be map type followed my map design. And I agree. One person thought thought that the positioning of the graduated symbol in the center of the county districts could mislead someone to think that is the exact location of the black population.

The following was done to the map:
1: Switched from equal interval to Graduated Symbols
2: Switched from categories to dot symbols. Circles were chosen since literature indicated that people like that shape over all others
3: Changed the entire color scheme
4: Added Source
5: Added Map compiler information.
6: Expanded the neat line to create more useable area
7: Expanded a secondary title to better reflect the map message
8: Changed font schemes to better reflect the map message
9: Repositioned the Scale information and North Arrow
10: changed the title of in the table from "p_black" to "Percent Black Population"


This lab required us to do the following
1. Choose one of the laboratory maps that was created/altered this semester (or at least
was created using an Arc shapefile).
2. Visit the following website ESRI Mapping Center.
3. See the Map library that contains various cartographic effects that can be used in Arc.
4. Download and use as many effects necessary to help display the information effectively.
5. Post your final map to your personal blog.

Week 9 - Immigration Flow Map

This was an interesting lab.  I experimented with various color schemes and pallets. I compared the "monochrome looks" with multi-colored looks and as you see here settled on the multi-color look since the regions stood out better and helped me to convey the immigration message.

 

I wanted to see how much I could do in ArcGIS then compare the end result with AI.  The end product is definitely more polished after AI than directly from ArcGIS.  Yes, I rather knew that it would.  What I find interesting is that the same information is presented and for the quick solution ArcGIS is sufficient.  If a map quality presentation is needed then one needs to have a finishing product like AI. 

My trick to get my curves was a digital version of what I did years ago.  Cartographers used to use these gizmos called french curves.  They are a set of odd looking shapes because the are made of lots of complex curves.  So I drew my lines, created some complex curves then fitted the lines to the curves.. 

Lab 8 - Dot Map Density Lab

This lab was so time consuming making and placing all those dots but in the end it looks pretty cool.  Trisha said to use the minimum of features for this map.  I experimented with different layers (specifically the hydrographic layers, and county names).  In the end I opted to leave these off (even though I edited all the county names) because it distracted the eye from the primary purpose for the map.  That being the dot density.

I lifted the description about the lab from the Discussion Board

So why map density? It emphasizes patterns rather than individual locations.  When mapping areas of different sizes and when the location of each individual feature is mapped it may be difficult to distinguish how many are in a highly populated area.
There are two ways of mapping density:
1) map graphically with a dot map
2) map density value for each area


Things to remember about this map


1) dots are distributed randomly within defined area
2) do not represent actual locations of features
3) closer together dots mean higher density of features in an area
4)This method is good for showing clustered features.


The density value= total# or value of features/area of polygon


The downside to this type of calcuation/map is that you can see which areas have higher density but not specific distribution of density within area.

Tricks I Used
Created few sets of random Dot concentrations then used a unique copy paste function
use these steps
1) Select the features you want to copy (in this case a dot cluster)
2) Copy them with
3) Bring the copy to the front a frame appears around the cluster
4) Move the cluster to your desired site.
5) voila...it is now there.  Just and aside, these clusters can be rotated using the methods we learned in previous labs.

Week 7 - Proportional Symbols

In this lab, I created a proportional circle map. The idea was to create a map to show wine consumption in Europe for 2005.  The data used, is provided by the Wine Institute (http://www.wineinstitute.org/ and is cited as the data source on the map. Specifically, Table 5.1 World Wine Consumption is the data source.  The link for the data is http://www.wineinstitute.org/files/WorldWine%20ConsumptionbyVolume.pdf .  The European wine consumption data was already in an Excel® file so that made that part much easier. Germany was missing so I added that from the source mentioned above. Note that the data is in thousands of Hectoliters per year and was annotated on the legend.

Below are UWF map requirements:

• Create your proportional symbol map by utilizing the conventional mathematical scaling (Square Root) method for determining the sizes of circles.

• Use Excel to calculate circle size
• Use ArcMap to create the base map
• Use Adobe Illustrator to complete the map
• Make sure you include all required map elements are clearly evident

Now I think I will go have a nice glass of Merlot.

Module 6 - Cloropleth Maps

In this lab, the requirement was to producing two population change maps of the United States of America using census data. The maps illustrate the percentage change in population of each state for the period of April 1, 1990 to April 1st, 2000.

We had to decide what data values to use for the choropleth maps as well  as the artistic properties needed in order to convey the appropriate information.

Included below are the map requirements:



1)  Two choropleth maps
2)  Notice that Alaska and Hawaii are included though the scales were changed.
3)  ArcMap was to produce the maps showing changes in population at the state level,
4)  Adobe Illustrator CS4 was to adjust the state map to create the regional map using calculations done in Excel.
5)  Both maps were touched up in Illustrator.

Module 5 - Percent Hispanic Population In South Florida w/ Illustrator

Conceptually, this was a very straight forward lab.  It did create the emphasis on map design.  But this took me so much time.  But I am finally almost satisfied with the result.  I still need to add a couple things that I think will make the map product pop a little better. 

So did I get to this map.

Frame and Neat  Line

These are minimized to define the extent and nothing more.

Mapped Area

This was chosen for us so we did not have much choice there.  However, we had a broad license to create the map product you see here.

Color Scheme

In this type of map, color range should track population.  In this case the lightest color corresponds with lowest population density.  Similarly, the darkest color denotes the highest population density.

I found a color I liked then used a corresponding color scheme. It seemed to work so I left it that way.

       Challenge - I could not figure out how to link the legend to the counties so I had to tint each box in the legend and each corresponding county.  I need to go back and replay the flash demo on google since there must me an easier to accomplish this task.
 

Map element positions

The map is intentionally "bottom heavy" since there have been several studies that show people are more comfortable with this approach than "top heavy".  The speculation for this is that people are visually aware of gravity and that is why this approach is better.

       Challenge.  Moving, resizing, rescaling... pretty much everything in Adobe Illustrator.  There is a lot to learn in a short time.

Font Size

Font sizes are varied based on peceived importance.  Like so much of this process, even this can be somewhat subjective.

Week 4 - The Middle Florida Keys

This was an interesting lab.  For my own convenience, I down loaded the 30 day free license from Adobe. 

The objective was to present the data in a cohesive, well-organized map that emphasizes good map design and organization.  Like many others in my class, I had much to learn with Adobe Illustrator as a new tool.  Fortunately, Adobe has several video tutorials that really shortened my learning curve.  I thank the Trisha for pointing some of them out. 

I learned so many new tricks doing this lab.  My two favorites are the Point_Text_Scaling and the text that automatically travels along an existing line.  These were really slick.  Many of the other functions were actually quite similar to the less robust functions found in Microsoft products.

It is interesting to look at the cartographic components and compare them with the professional products from organizations like the USGS and NGA.  As a result of this course, I am gaining more repect for that aspect of map construction. 

Data Classification Lab – Andrew V Murphy

Data Classification Lab

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Notice that the data only goes out to 2 or three decimals since I limited the values to 1 more than the significant value.  Presenting the additional zeros was simply map clutter.

The question asked which classification best fit or represented the given data of these four methods

Standard Deviation was ruled out first as it was limited by the number of breaks which seemed unsatisfactory to me.  Another reason to rule out the Standard Deviation is captured in the name.  Since the data does not fall into a normal distribution, this option is simply not a good choice.

Natural Break held promise but since I did not know much about the data then the weakness of this choice became evident.  As noted in our text, "the class limits are subjective and can vary" and was thus ruled out. 

Equal Intervals and Quantiles both seemed to work for me.

Quantiles, like Equal Intervals,  can be computed manually.  Another advantage is that an equal number of data in each class. Clarke goes in great detail on page 62 of our text.  In the end I ruled it out because one can have gaps which could confuse the reader as they wonder why some data was left out.

I chose Equal Intervals for my final selection.  It has several advantages - it is easy to calculate (you can choose how many classes are needed),  easy to interpret, and the limits do not contain gaps.

                                        

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An Example of a Good Map

Now this map was excellent.  It followed all edward Tufte's 6 commandments.  Tell me what you think of this one.  As one who loves the out doors, this one works for me.

An Example of a Bad Map

A quick look around the web yielded this terrible map.  At first glance, I did not notice anything major..then I read the following paragraph.

A map of the world, showing the most popular social networks by country. Most of the the colors used look the same for the color blind. As color is the only method of connecting the networks to the countries, this map is unusable for the color blind. http://wearecolorblind.com/examples/bad/world-map-of-social-networks/

And away we go

on our wild new adventure