Using LiDAR Data

Supervised Classification

After 5 attempts, sad to say, this is the best I could get. I'm not sure what to do to improve the results.

Unsupervised Image Classification

Colors were selected for contrast between the assumed land uses. The original image didn't provide me with many clues. I did a lot of assuming after that and ended with 6 catgories out of the original 15.

Rectification; uses and pitfalls

In GIS, image rectification can place an aerial image in a geographic coordinate system, and remove distortion. The image can then be placed on a map in the correct location and scale. The process involves placing control points on the image that correspond with points on a map layer with a known coordinate system. Placing the control points is critical to achieving useful results. Two pitfalls of rectification involve the placing of the control points. If it is not done accurately, or if the image lacks recognizable points that correspond to the map layer, the image will continue to contain some degree of distortion.

Module 3, Fort Worth

1. Provide a brief description of why the following features appear as they do in
this thermal infrared image:

Roads- Light shade; the surface is emitting energy absorbed during day time.

Natural and man-made vegetation- Dark shade; absorbing energy and using it rather than emitting it later.

Sidewalks and patios- Light shade; reflecting energy. Concrete will reflect even small amounts of thermal energy.

Storage sheds in back yards- Dark shade, probably the same material as the house roof shingles, which reflect during the day and cool rapidly at night.

Automobiles- Mostly dark, unless recently driven, which generates heat.

Bright spots on many of the roof tops- Light shade; vent locations from the plumbing and dryers. They are emitting heat.

Exorcise 2

1, Air field

2. golf course

3. major roads

4. baseball fields

5. boat docks

6. Bridge

7. residential subdivision

8. boats on the water

Many more of the objects would have been recognizable with some familiarity with the area.

There are very large buildings visible, but what they are would be hard to say with out a higher resolution.

SPOT image differences

The first and most obvious difference between the two photos is the clear separation of water and land. The color in the multi spectral photo helps define the shore line. The under water contours are also better defined. Vegetation is apparent in the ERDAS Viewer as a bright red which also delineates the urban area by the lack of color. I don't know why the red does not show up in the image below. All the parameters matched those in ERDAS.
The panchromatic photo is sharper and better defines the urban area. It's easier to pick out individual buildings.

Exercise II: What can you see

1. Using the projected aerial photograph, identify 8 to 10 things that you can
determine or derive from the photo.
1. Baseball fields near the shore line
2. An airport on the western edge of the photo
3. A golf course in the northeast quadrant
4. Several large buildings scattered throughout the photo
5. A small forest or woodland at the eastern end of the airport
6. Major roadways
7. A bridge in the northeast quadrant
8. A small residential subdivision south of "B"
9. Piers and beaches on the southern coast
10. Boats on the water
2. What problems might you infer or identify in using this type of photograph?
The small scale makes identification of detail difficult. The only obvious features are the limits of the developed and undeveloped areas. I would have to have some familiarity
with the area to be able to identify individual features with any certainty.

The bride and I are enjoying the weekend.

Wind Farm Evaluation

The area surrounding this section of Route 12 in the southern section of Wisconsin is mostly farm land, and runs parallel to the Lake Michigan shoreline, using a similar design in Great Britain by paralleling the road.
The area has a low population density, flat terrain and steady wind speed & direction off the lake.
Nearby Milwaukee would provide a market and existing grid to minimize start up cost and assure demand.
The location appears to be outside of any major bird migration routes.
The route would be 4 miles in approximate length, and has room to expand if the demand becomes maximized.

Isopleth Map of Georgia

Immigration Flow Map

Cartogram Maps

Household Dot Density Map of Florida 2000

Proportional Circles Map

Choropleth Maps

percent_of change_division.ai

I separated the excel file into divisions by adding a column ‘division’. I then performed the calculations to obtain the percent of increase per division, copied the totals into a second file and opened it in ArcMap. I performed a join using the division column and revised the map to Equal interval using the division column. I selected a black to white color range and saved the new map as an .ai file. I moved the scale bar into the layer with the map and put the subtitle and north arrow in each layer containing the frame. I adjusted the grays and placed heavier boarders around the states that were shaded light to give them more definition, and saved the map.

percent_of_change.ai

I separated the three areas into separate layers and sized the windows around the subject area. I then changed the projection for each layer to display the map in the proper proportions. The state_pop,shp file is in GCS North American 1983 CSRS. For the lower forty eight states I used the North American Albers Equal Area Conic projection. The Alaska frame is in NAD 1983 Alaska Albers and the Hawaii frame is in the same projection as the shape file. Changing it did not seem to make much difference in the appearance. In ‘AI’ all the features associated with a frame where moved to the group containing the map group. I renamed the layers to identify the contents and saved the map.

Adobe Illustrator torture 2/28/2009

My attempts at mapping the Hispanic population of South/Central Florida and lettering the Florida Keys. I gotta work on sizing the maps

Map Critique

Nice color & balance. Lots of info but still a clean map of the North Carolina coast on top.

Less water & smaller scale and the inset wouldn't be needed in the map of Malta. The inset blends into the overall map making me think at first it's all one map.

Mental Map

Red for Florida because that's where I am most comfortable.
Orange for New York because that's where I grew up and if I could handle the cold better I'd still be there
Green for California because if I could afford to live there it would be closer to my wife's home and cheaper to visit her family.