- 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.
- Week 3: the start of atmospheric corrections. Ratios (including looking at a lot of different imagery using ratios)
- Week 4:
- Week 5. Digital image processing. Rectification. Midterm exam on friday, 7 February!
- 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.
- Week 9: Radar
- Week 10. Hyperspectral data.
Tutorials: Note, labs handed out on monday will be due friday, Wednesday labs will be due the next monday. And friday labs will be due the next Wednesday!
- Lab 1 - We'll start 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. Must be typed!
- Lab 2: The lab and the worksheet 3 points. (obviously, fill out and turn in the worksheet).
- Lab 3: the lab and the worksheet 3 points (since there's no class the next monday, this will be due tuesday).
- 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.
- Lab 7: Filters and ratios. 3 points.
- lab 8: PCA. 4 points.
- Lab 9: Unsupervised classification. 3 points.
- Lab 10: supervised classification. Part one. 5 points.
- 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: LIDAR. Yup, frickin' planes with frickin' laser beams.
Project: The overall goal is to track landcover/use change in an area over, say, 20-30 years
- Step 1 - think of an area that has changed over the past few decades or so. The world is your oyster. Think at least 20 miles by 20 miles. Write up about a paragraph which describes your study area/topic (what you're mapping and where). due by 9 April. 1 point
- Step 2 - get data! Simplest would be landsat, but feel free to use any sort of applicable imagery. The first image must be from the last year or two; the second image must be AT LEAST 20 years older than the current image. Head off to http://earthexplorer.usgs.gov/ - this is the best (but not only) place to get all sorts of imagery. If you wish to be more creative and find different sorts of imagery from different places, go for it. Remember, the two images MUST be taken at the same time of year.
- Step 3 - get the data into ERDAS and georeferenced if necessary. Make sure the two images line up properly in your study area. Chances are good that rectification is necessary. This will be checked in lab on 14 February - so make sure you bring everything to class that day. 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 identical 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. Or goto https://pubs.usgs.gov/pp/0964/report.pdf and take a look at table 2 on page 8. You should be able to get to Level II.
- 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. Yes, I expect readable color images with appropriate cartography (neatlines, N arrow, scale, etc).
- 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 paper which includes
- An introduction which includes your question (what you're doing and why),
- Descriptions of your data - year, sensor, time of year, where you got it, etc.
- 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.
- Note, your final writeup should include a lot of images, and they all need to be readable (no postage stamp images - fill the page!). It's better to give multiples than too few.
- Step 1: 24 January. 1 point
- Step 3 14 February. 2 points (checked in lab that day on computers)
- Step 6. 6 March. 2 points
- Final writeup: Due the friday before finals week: 13 March. 6 points
Some potentially useful links for you: