2.1: Basics of Raster Data
One form of remote sensing done in a GIS is called raster data. Many sophisticated GIS analyses and predictive models rely on raster data. Before you can perform an analysis or create a model, however, you need to understand the fundamental concepts of the raster data model. This course teaches those concepts. You will explore the structure of raster data, learn about different raster formats and why raster data is preferred for certain GIS operations, and find out how to choose the appropriate type of raster data for a given application. In this assignment, you will be able to:
- Understand the types of geographic phenomena that raster data commonly represents.
- List some sources of raster data.
- Get information about a raster dataset in ArcMap.
- Adjust raster symbology in ArcMap to improve visualization.
- Decide which raster data format would be most suitable for a given use.
Discuss how using raster imagery has changed your perspective and understanding of viewing satellite imagery.
Last time I went camping down in Southern Utah, and was sitting around the camp fire, my friends and I witnessed a very bright reflection from up in the dark night sky right down to our camp site. In the moment, we kidded about spaceships and aliens, but really we spotted the culprit – a satellite! Satellite imagery has always been neat to look at especially since we can view our own planet from an entirely different perspective. Viewing and utilizing raster imagery has forever changed how I look at satellite imagery as well as other types of images. For example, in the Physical Geography class I took last year, we used the google Earth application to view Earthquakes and Volcanoes. When I was surfing and toggling around the globe, looking at the Himalayan Mountain Range from above, and then coming up the immense canyons and ridges, I never imagined that the amount of raster data that goes into creating the imagery. I used to look at a satellite image and think it was really cool, but now I find myself saying “Wow!” because my mind is blown by the amount of information that is captured, analyzed and interpreted through the radiation detection of satellites that we cannot perceive with our own eyes. The fact that the satellite images are bounced back to Earth and the information is placed into pixels (cells) make researching and exploring so much more understandable. Raster imagery is phenomenal and how it is organized makes a lot of sense to me. I like the simplicity of the Cartesian model x, y grid and yet the complexity of what each pixel holds. It makes me appreciate even more now, the technology that we have at our fingertips and how we can use it to interpret the constant evolution of our planet and all of its inhabitants.
2.2: Composite Imagery
How is the urban growth of the Las Vegas area encroaching on the boundary of desert that surrounds the sprawling metropolis? Urban planning is not only key to answering this question, but also essential to balancing how land is used when it comes to accommodating population growth as well as preserving the natural environment surrounding the city. To analyze our current situation, we must first look at a Landsat TM satellite image. Our goal is to produce a series of color composite images and then utilize them to study the environmental landscape.
Taken by the Landsat satellite in May 2006, we will be looking at a composite image of several electromagnetic spectral bands so that we can analyze the imagery data and draw potential answers to the questions at hand. You can note that the population of Las Vegas from the July 2006 census was 552,855 people. First, we will look at just the first band of Blue light which penetrates clear water better than the other colors. By looking at just the blue light, we will be able to see bodies of water easier and somewhat make out man made structures. However, you will also notice that we are unable to locate any desert vegetation.
Now, we can compare Band 1 (Blue light) with that of Band 3 (Red light) Band 5 (Shortwave Infrared Light) and Band 7 (a second Shortwave Infrared Light).
Bands 1 and 3 display land features in a similar way by being able to define boundaries of features but not with great contrast while they do show, with increased visibility, the urban, populated area of the map. Bands 1 and 3 show man-made structures with more detail and visibility than Bands 5 and 7. Bands 5 and 7 display land features with much greater detail not only with more clarity of image, but also with the varying shades of white to black. It is much easier to pick out different types of terrain and soil with these two bands.
Using Bands 1, 2, and 3 of the composite image, we will first note their color assignment (also known as display colors). By default, Band 1 is assigned Red, Band 2 is assigned Green and Band 3 is assigned Blue. Still looking at Bands 1, 2 and 3, we created a 3-2-1 Composite image by changing Band 1 to Blue and Band 3 to Red. This image displayed a much more realistic image of the Las Vegas area looking to the west of the city at Red Rock Canyon National Conservation area also to the east at Lake Mead and the Colorado River. If we view the same map of Las Vegas, but with the initial band combination (of 1, 2, 3), the shading of the lake, backyards in the city, and even out toward Red Rock Canyon look like a different planet. The coloring is quite off and not true of the actual representation of the area. Here is the Natural Color image we produced:
|Columns and Rows||7871, 7001|
|Number of Bands||3|
|Cell Size (meters a pixel represents)||30, 30|
In creating other composite images, we can alter how an image appears by assigning RGB to represent different wavelengths. For example, if we create a new composite image using Bands 4, 5 and 7,
- Band 4 which is Near Infrared (NIR) will be represented by Red Light and it will clearly show us shorelines (around Lake Mead) and vegetation .
- Band 5 which is Shortwave Infrared (SWIR) will be represented by Green Light will provide contrast among the vegetation for us.
- Band 7 which is another SWIR will be represented by Blue Light will provide even more contrast in the vegetation than Band 5 above.
In order to demonstrate the boundaries between the urban area of Las Vegas and the how it is encroaching on the desert that surrounds it, we created three different kinds of composite images shown below.
Types of Land Cover
Natural Color Image
False Color Image
Pseudo Color Image
Out of all of three images we created, I believe the False Color Image best visually represents vegetation since the live vegetation stands out in a bright reddish color that one cannot mistake for anything else. Because of the infrared wavelength used in this composite image, it makes it extremely easy to discern the vegetation both within Las Vegas proper as well as in the surrounding desert. While the False Color Image best displays the vegetation, I believe that the Pseudo Color Image best visually represents the urban areas of Las Vegas. Because of the differences in colors, the aqua and browns really “pop” so that one can immediately hone in on where the city is and where the desert lies beyond.
▪ Acquire – Describe the type of data you used for this assignment. The type of data and the geographic scope of your assignment dictated how the data was collected and how it was analyzed.
▪ Examine – Was the data you used for the assignment appropriate for the study area? This includes how the data is organized, how accurate it is, and where the data came from.
▪ Analyze – Geographic analysis is the core strength of spatial knowledge. Describe how you analyzed the data and imagery used for the assignment. What information did you acquire and learn from the analyses.
▪ Act – The results of your analyses can be shared through reports, maps, tables, and charts and delivered in printed format or digitally over a network or on the web. Describe how you shared your analyses for the assignment.
▪ Connect – How might you apply this type of geographic inquiry in other contexts (i.e. real-world and other courses you’ve taken or are taking throughout your academic career)?
2.3: Bird’s Eye View of Earth