Foundations Of Geographic Information Systems Assignment Package

Assignment 9/Assignment 9.docx

GIS 5103 – Week 9 Assignment – Remote Sensing & Raster Data

https://earthexplorer.usgs.gov/

For this weeks assignment we are going to download multi-spectral imagery from the USGS. First we will go onto the earthexplorer and create a free account. You will have to confirm the account in the email you choose to sign up with.

Once our account is created, we will begin to search for an area of interest. There are multiple ways to do this. Simply click on the map, type in a specific address or location, or create a box/square on the map. All of these methods will find any satellite image that contains part of the area of interest. Because of this, it is important to preview the image before selecting it.

Here I only typed in Boston, and set the date range from September 2017 until September 2019. (Areas within the U.S will have more consistent images.)

Once we found our area of interest, we will have to choose which satellite system and data level we want to use. For this exercise we want the most recent up-to-date data, so we will be using Landsat 8, on demand level 2 data. This has already been converted to Surface reflectance. It will give you a warning which you can ignore.

Once we have selected the satellite system and level we can simply click results. What will appear is the following.

As you can see many of the images have clouds and will have to be skipped over. By clicking the footprint, we can see where the image lies on a world map. Once you are logged in you can click the shopping cart to order the scene from the USGS. Click the shopping cart, and it will glow green, meaning it has been added to item basket.

Once you have chosen a clear scene over your area of interest, you can view item basket and proceed to checkout. It costs nothing to order scenes, but the USGS will take some time to process your order. Real people are converting the satellite images to surface reflectance, have patience.

You will get a confirmation email and then another email with a link to download the data you selected. You should save this to your local machine or to the D Drive on the server. Make sure to delete any files in your downloads on the server.

The file should come as a .tiff or a geotiff, both can open in QGIS, ArcMap, and ArcPro.

When adding each band individually, it will prompt this box, click yes and continue adding each band. (7 total bands) Ignore any .tif file that does not have the word band in it. Once all the bands have been successfully added to ArcMap use the Composit bands tool to combine all the bands into one file.

By using the composite band tool we can reorder the bands to the correct color schemes and get a true color image of our location. The order I used below will create a true color image (4-3-2) (Red – Green – Blue)

We are going to take our multispectral data and calculate 5 indices. Indices are used to enhance the data we currently have to highlight certain features on the surface or to allow us to estimate something about the surface. (i.e. Soil moisture, vegetation health, impervious surfaces) The indices I have chosen are common amongst the environmental science fields.

We will use the raster calculator tool to creat the indices. To do this you will need to know which band number relates to what color/wavelength.

Use the raster calculator tool to type in the following equations. Make sure your parenthesis are correct, and that the correct band number is used. (Keep each individual band as a layer for calculations, and use the composite to see the true color image)

When using the raster calculator make sure to insert “Float( “ before any mathmatical function, so that you keep all of the decimal poins, otherwise it will calculate whole numbers. Without it you will get incorrect calculations. (This is the NDVI calculation)

To get the Raster Calculator tool, we have to enable some extensions. Check off the same ones I have listed below.

NDVI = { (NIR – RED) / (NIR + RED) }

Normalized Difference Vegetation Index

NDWI = { (NIR – SWIR1) / (NIR + SWIR1) }

Normalized Difference Water Index

SAVI = { (NIR – RED) / (NIR + RED + .5) } * (1 + .5)

Soil Adjusted Vegetation Index

EVI = 2.5 * { (NIR –RED) / [ (NIR +6) * (RED – 7.5) * (BLUE +1 ) ] }

Enhanced Vegetation Index

MSAVI2 = { (2 * NIR + 1) – SQRT( { [ 2 * NIR + 1 ] ^ 2 } – 8 * [NIR – RED] ) } / 2

Modified Soil-adjusted Vegetation Index

Assignment Deliverables:

1 Complete map, with map elements, for every index. (Color is up to you)

2-3 sentence descripition of what each index is highlighting.

1 paragraph on how each index can help (or not) your specific field.