- Week 1: history, resolution, TM. And a closer look at landsat data, including how to get data off earthexplorer
- Week 2: lecture on reflectance, data, and stretching. Sensors. Both labs 2 and 3 handed out this week.
- Week 3: the start of atmospheric corrections. Tues was in-class lab 4 (below) Ratios (including looking at a lot of different imagery using ratios)
- Week 4:
- Week 5. Digital image processing. Rectification. Midterm exam on thursday!
- Week 6: Principal Component Analysis. Unsupervised Classification. Drones
- Week 7: supervised classification. Guest lecture on Monday - Jeff Watson.
- Week 8: LIDAR and accuracy assessment. Looked at Earth as Art book. No class wed - SOURCE lab.
- Week 9:
- 21 May: Guest speaker, Richard Diaz.
- 22 May (hopefully), morning Drones lab. Out in the field. Save this date. Weather permitting. Whoo hoo. Perfect day.
- 23-24 May. Go over unsupervised and supervised labs. Radar
- Week 10. Hyperspectral data.
- Lab 1 - Because lab one falls on the first day of class, we'll go a bit light with a little review from airphoto. Work through the "Eye in the Sky" book (available in the lab) and answer bonus question 1 from each "chapter". 3 points. Please don't write in the books - they are collector's items and can no longer be purchased. Due next monday.
- Lab 2: The lab and the worksheet 3 points. (obviously, fill out and turn in the worksheet). Due the next monday.
- Lab 3: the lab and the worksheet 3 points (due the next wednesday).
- Lab4 - in class exercise looking at different sensors. Due at the end of class. 2 points.
- Lab 5: Georectification. 3 points.
- Lab 6: Pan Sharpening. 2 points. Due in 6 days.
- Lab 7: Filters and ratios. 3 points. Due in 6 days.
- lab 8: PCA. 4 points. Due in 6 days.
- Lab 9: Unsupervised classification. 3 points. Due in 6 days.
- Lab 10: supervised classification. Part one. 5 points. Due in 6 days
- Lab 11: Accuracy assessment of your supervised classification. 4 points. See this sample for what your confusion matrices might look like. Emphasis on might.
- Lab 12: SOURCE: to be done on Wed or thursday, 16/17 May. Instead of class, your job is to attend a total of at least three talks/posters. Pick three which include maps of some sort (and preferably some sort of map analysis). At least one must be a presentation, at least one must be a poster. For each, take notes, etc and hand in a 1 page writeup for each talk/poster. Include the following for each one:
- The title and author of the talk.
- A one paragraph summary of the research project.
- A sentence or two explaining how this presentation relates to mapping.
- A short critique of the maps and spatial analysis which were presented. (1-2 paragraphs)
- One paragraph or so explaining what you liked, didn’t like, etc. Note: I really don’t care whether you like it or not, what I am interested in is the WHY. Very similar to the readings you do every week. I highly suggest you spend some quality time at SOURCE checking out what other students are doing. Then do the writeup on the three you find most interesting.
- This will be worth 3 points. Due on the Monday following the presentations.
- Lab 13 - LIDAR. Yup, frickin' planes with frickin' laser beams.
- The overall goal is to track landcover/use change in an area over, say, 30 years
- Step 1 - think of an area that has changed over the past few decades or so. Get on this part Think at least 20 miles by 20 miles. Your study area/topic (what you're mapping and where) will be due by 9 April. Write up about a paragraph. 1 point
- Step 2 - get data! Be sure to get two different types. Simplest would be landsat 8 and landsat 4, but feel free to use any sort of applicable imagery. The second image must be AT LEAST 20 years older than the current image.. Head off to http://earthexplorer.usgs.gov/ - this is the simplest place to get all sorts of imagery.
- Step 3 - get the data into ERDAS and georeferenced if necessary. But, make sure the two images line up properly in your study area. Chances are good that rectification is necessary. This will be checked on 10 May. Worth 2 points.
- Step 4, clip out your study area. Load both images (old and new). Goto raster, subset and chip, create subset image. input your input and output files. highlight the "snap pixel edges to raster image" Then build an inquire box: On the Home tab, click Inquire > Inquire Box to open an Inquire Box in the active View. Resize the box to fit the area in which you want to work. Now, back to subset.... click the "from inquire box" button. You should see the map coordinates change to fit your inquire box. Finally, make sure the input and output data types are the same and that you have selected the right number of layers. Do it. Then repeat for the second image (keep the inquire box up! Make 100% sure that you clip out the correct areas.
- Step 5 - Figure out which landuse/landcover classes exist during both dates (note, there may be ones that are in one image that aren't in the other, if enough change has happened). Follow your book, page 611 - 618.
- Step 6 - do a supervised classification of your images (we'll get to this later in the quarter). Don't forget your accuracy assessments. (Hand in a quick writeup which includes both the original and supervised images and both confusion matrices. Due on 21 May, 2 points)
- Step 7 - Head into ArcGIS and run the spatial analyst tools, zonal, tabulate area tool. Do this for each classified image/date and summarize the results. These results are much like a confusion matrix - except that in this case, they show the differences between two dates in terms of area. Give me a writeup telling me where things changed, how, why, etc. Not only the results from the tool, but LOOK at the images and tell me what you see
- Give me a final writeup which includes your question (what you're doing and why), your methods (what steps you took), your results, and a final "thoughts" section which details what worked, what didn't, what you would do differently next time, etc. Your final writeup should include good (as in readable, don't give me postage stamp images. Better to give multiples than too few) images of both images and your classifications. Due on the friday before finals week. 6 points.
Some potentially useful links for you: