Lab 3: Image Enhancements I 65 pts Due > Canvas by 10pm

Transcription

1 Geo 448/548 Spring 2016 Lab 3: Image Enhancements I 65 pts Due > Canvas by 10pm For this lab, you will learn different ways to calculate spectral vegetation indices (SVIs). These are one category of image enhancements that are designed to detect vegetation and monitor phenology and conditions. We will revisit this more later in the semester, but this lab will give you a chance to see a few commonly used SVIs. You will calculate image enhancements for Landsat 8 OLI data using ENVI and Google Earth Engine. All data can be found in the class folder G:/CLASS/GEO448_MH/Spring_2016/Lab_3 Part 1: Image Enhancements in ENVI In this part of the lab, you will calculate Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) using ENVI. Put copies of any images you create in your folder on the G drive (make a folder called Lab3 or Lab_3 and clearly name your files). Open the Grand Canyon image file Grand_Canyon_OLI_Lab using your choice of band combination (be sure it is something that can distinguish vegetation from other land cover). Scroll around the image to familiarize yourself with the area. 1. Which band combination did you use? 2 pts 2. What color is vegetation? 2 pts 3. Where in this image is the most vegetation visible? 2 pts 4. Report a latitude and longitude coordinate (Right click > Cursor Location/Value) where you can see a lot of vegetation (change the display coordinates to decimal degrees first under Cursor Location/Value > Options > Uncheck Lat/Lon: DMS ) 2 pts 5. Create a spectral profile for a location with visible vegetation and include it in your writeup. 4 pts Calculating NDVI To calculate NDVI, you can use Transform > NDVI. Change the bands to Band 4 for red and Band 5 for near infrared. (You can leave the Input File Type as Landsat TM even though you are analyzing OLI data). Select an output file name and click OK. When the calculation is finished, open the NDVI image in a second viewer and link them (you should still have the color composite reflectance image open in the other viewer). 6. Describe the patterns in the NDVI image compared to the original- which areas are bright? Which are dark? You can use the dynamic overlay to compare. 4 pts 7. Go back to the same area you reported in question 4 and record some NDVI values. How do these compare to the non-vegetated areas? 4 pts ENVI has other built-in vegetation indices, but you will see how to calculate any index (even those not included in the software) using Band Math. Basic Tools > Band Math. Calculating SR First, calculate the Simple Ratio (NIR/red). For OLI data NIR is Band 5 and Red is Band 4. The expression you need to enter is shown below: float(b5)/float(b4)

2 Click Add to List, then OK and you will be prompted to select b4 and b5 from your Available Bands List. Select Near Infrared for b5 and Red for b4, choose an output file name and click OK. Your resulting image will be similar to NDVI, but notice the pixel values are different. NDVI scales from -1 to 1 but Simple Ratio has no bounds. 8. Record a few high SR values (bright) and low SR values (dark). How do they compare to the NDVI values you found in questions 6-7? 4 pts Calculating EVI Finally, you will calculate the Enhanced Vegetation Index. It is similar to the calculation for NDVI, but has adjustments for bare soil and atmospheric effects. EVI also tends to provide better contrast between vegetation types and is less likely to saturate at high levels of green biomass. EVI = 2.5 ρnir ρred ρnir + 6ρR 7.5ρB + 1 2

3 To enter this calculation into the Band Math calculator, use the formula below. You can copy and paste it from this lab (digital copy under Assignments on Canvas). 2.5*((float (b5) - float (b4))/(float (b5) + (6*float (b4))- (7.5*float (b2)) + 1)) 1.5*((float (b4) - float (b3))/(float (b4) + (float (b3))+ 0.5)) ß --- SAVI Be sure to use Blue for Band 2, Red for Band 4, and Near Infrared for Band 5: Give your new file a name and click OK. After you run the EVI calculation, open it in one display window with NDVI the other. Link the images, but turn off Dynamic Overlay. 9. Use Cursor Location/Value to compare NDVI and EVI for the same pixels around the image. How do they compare? 4 pts In this lab, you have just made quick comparisons of pixel values, but for more detailed analysis you can also extract pixel values using ROIs (Basic Tools > Region of Interest > Output 3

4 ROIs to ASCII). This will create a text file that you can analyze with statistics software or make charts in Excel. (Note that ROIs can also be created from existing shapefiles). Deliverables for Part 1: NDVI image, SR image, EVI image (4 points each = 12 points) Part 2: Image Enhancements in Google Earth Engine In this part of the lab, you will learn how to calculate SR and NDVI using Google Earth Engine. You can do this part of the lab on ANY COMPUTER (even a Mac!) In a browser (Chrome is recommended) go tohttps://explorer.earthengine.google.com/#workspace. Make sure you are logged in with your Miami account and click Data Catalog in the upper right. Find Landsat 8 8-Day Raw Composite and click open in workspace This will display a map, but you will have to zoom in to view the data. Keep in mind that Landsat-8 passes over the same location every 16 days, so you will not see an image for every date range in the slider bar (you should see an image for every other date range). Move the date slider to Jun 18, 2013 Jun 26, 2013 and select the band combination you would like to use. Before closing this window, zoom the map into northern Arizona, then the Grand Canyon area. Click Stretch, then Apply, and Save. You should now see a color composite image of Grand Canyon and surrounding area (this is the same image you viewed in Part 1). As you scroll around you should occasionally open the image settings and click Stretch (Apply and Save) 4

5 again. Since the contrast is set using the part of the image visible in your browser, it works best when you keep updating this. To open image settings, click the image name. To hide the image, click the eye. You can also make your image transparent- which allows you to see the map information underneath- by moving the Opacity slider to the left and clicking Apply. Try Opacity values above 0.5 up to 0.8 to see what you prefer. Calculating SR To calculate Band Math in Google Earth Engine, click Add Computation then Expression under Per-Pixel Math. Click Landsat 8 8-Day Composite under Select Image. This will be img1 in the calculations below. If you had more than one image open, you could do multiple image band math by designating img1, img2, etc. Calculate a Simple Ratio image using this expression: img1["b5"]/img1["b4"] Under Visualization it will show just B5, but it is really your calculation. Click Stretch and Apply to see your result. You can also change the name of your layer by clicking the name (Computed layer: Expression). The calculation will show for any area covered by the input 5

6 image, so you can scroll around to see how the Simple Ratio looks for other areas, too. Just remember to click Click Stretch and Apply to adjust contrast for the area you are viewing. Take a screen grab of the SR image around Grand Canyon and save it with your images (on the G drive) from Part 1 to submit for grading. Calculating NDVI Calculate NDVI for this area using the same steps with this formula (be sure to use Landsat 8 as your input image): (img1["b5"]-img1["b4"])/(img1["b5"]+img1["b4"]) 6

7 Geo 448/548 Spring 2016 Reduce the Opacity to 0.75, zoom out to show a larger area of the map, and hide the original OLI image and Simple Ratio (by clicking the eye icon). Move the map south near Phoenix and Yuma. 10. How do the shades of gray change as you move south? (Does it get brighter or darker?) 4 pts 11. Which areas show up bright in this image (more vegetation) in this largely desert landscape? 4 pts Take a screen grab of the NDVI image and save it with your images (on the G drive) from Part 1 to submit for grading. Finally, calculate one additional vegetation index or band ratio of your choice. 12. In your write-up, include the calculation you used, a screen grab of the resulting image (save to your G drive folder), and a description of what landscape features are highlighted by your new image (vegetation, bare ground, snow, clouds, etc.) 5 pts Deliverables for Part 2: Screen grabs of your SR image, NDVI image, and other ratio or index you calculated (jpeg, TIFF, or png) (4 points each = 12 points) **Submit your write-up through Canvas by 10pm on 3/11. Also make sure your deliverable files are in your G drive folder by that time, too.** Write-up part of lab = 41 points Deliverables = 24 points Total = 65 points Part 1: ENVI NDVI Simple Ratio EVI Part 2: GEE Simple Ratio NDVI Other