Author note: This exercise was written by Grga Basic (2017); revised by Mario Giampieri (2022).
Data derived from satellite imagery is sometimes more readily available than vector data, especially when studying larger areas, calculating change over time, or estimating information about natural systems. In such cases, you may be tasked with extracting and deriving different data layers from a single starting image. In this particular case, we are tasked with creating data layers to better understand the Jordan River Valley and its adjacent tributaries using only elevation data.
Complete the exercise below, answering the embedded questions.
After completing the exercise, create one 11x17 (tabloid, landscape orientation) Flow Map of the Jordan River Valley using at the minimum Stream Network and Basins layers. If desired, add one or more of the terrain output layers to complete your map. Submit your map as a PDF.
<aside> 💾 Download and unzip the exercise data package from the link provided to you, saving the data to your working directory.
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Another important application of remote sensing is the production of digital elevation models (DEMs). A DEM is a representation of a surface created from terrain’s elevation data. For this exercise we will be using ASTER imagery, which is a global database of DEM data.
Before you work with a DEM, it should be projected so that your calculations will be as accurate as possible. It is critical to assign and use consistent coordinate system for all the datasets throughout this exercise. Both Landsat and DEM data in this package have already been assigned a projected coordinate system corresponding to its location - WGS_1984_UTM_Zone_36N. However, when you download data directly from Earth Explorer, you will notice that it comes “unprojected,” but with a defined WGS84 datum.
<aside> 💻 This section outlines suggestions for formatting both your map layout and processing environment to focus only on your chosen area of interest. While these steps are only suggestions, limiting your analysis to your area of interest can significantly reduce the processing time (and time spent laying out your final outputs).
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Launch your GIS software and start a new, blank project. Add the raster data from the exercise data package, and save the project. Create a new layout view for your map and set the page dimensions at 11x17 with landscape orientation, and ensure that the map object covers the entirety of the page.
Set the scale of the map between 1:200,000 and 1:250,000, and pan to a portion of the raster data that has an interesting height distribution. Create a new bookmark of the view for future reference.
Next, set the processing extent to match the map window (and map layout). This will reduce the amount of processing performed in all following steps.
<aside> 💻 The software skills required for the remainder of the exercise are listed below. They include several tools for working with DEMs.
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