Lab Exercise GEOG 361 651 Lab Exercise 8 Interpreting Radar Images Dr Andrew Klein This lab is a combination of labs originally developed by Dr Liu and modified by Dr Klein with help implementing the labs in ENVI from Songgang Gu I Introduction As an active remote sensing system a radar sensor transmits long wavelength microwaves 3 25cm with its own source of energy through the atmosphere and then records radar signal backscattered toward the sensor from the terrain as an image The primary advantages of radar remote sensing systems over the optical sensors lie in their capability in operating day and night and at all weather conditions The microwave wavelengths in which radars operate provide information about different properties of the surface than can be determined from multispectral and thermal images Radar images provide information on the roughness of the surface the presence and amount of moisture in the surface among other properties It should be emphasized that imaging geometry and physical and mathematical principles used to create radar imagery are very different from those used in visible near infrared and thermal infrared remote sensing systems This lab aims to develop the students understanding of basic radar remote sensing concepts and skills in analyzing radar imagery Specific tasks include to 1 Interpret a series of radar image chips to gain the understanding of the following fundamental concepts 1 2 3 4 5 6 Examine the direction and looking angle depression angles Understand what is meant by slant range ground range near range and far range Know what wavelengths frequencies radar system operates at Consider geometric distortions including layover foreshortening and shadows Understand the concepts of surface roughness and corner reflectors Utilize the day and night all weather imaging capability of today s SAR systems 2 Create a topographic contour map from a digital elevation model and display it with a Radarasat Synthetic Aperture Radar SAR image as the backdrop Visualize the Radarsat SAR image using HSV color model Create a 3D perspective view by draping the SAR image on top of a Digital Elevation Model 1 II Instructions and Exercises Task 1 The Synthetic Aperture Radar SAR image radarsat img is located in the directory lab08 folder This image was acquired by the Canadian Radarsat 1 satellite using the standard beam 7 on a winter night 1997 over the Pennell Coast Antarctica The near range depression angle and farrange depression angle for the standard beam 7 mode are 45 1 and 40 6 The image has been georeferenced in Polar Stereographic map projection The geometric distortions induced by the topography have been removed In other words radarsat img is a geocoded and orthorectified image Please visually interpret this RADARSAT image and answer the following questions Question 1 What band does the Radrasat 1 use to acquire the SAR image radarsat img What is the corresponding wavelength for this band Question 2 What is the look direction and satellite flight direction Print out a screen capture of the entire image and label the near range and far range on the image Question 3 Why can the Radarsat 1 obtain this sharp image even during the long winter night of Antarctica when there is no reflected solar energy Question 4 What geomorphologic features mountains coastlines etc can you observed from this SAR image 2 Task 2 From the digital elevation model elev dem in the lab08 folder create a contour map and display it with the SAR image radarsat img as the backdrop You should also select the geographic area where the SAR image and the contours overlap and make a hardcopy map to turn in with your report Tips 1 To display contour lines over the RADARSAT image you first need to open both the SAR image and Digital Elevation Model DEM 2 From the Image menu select Overlay Contours Lines to open Contour Band Choice dialog Select the DEM as the image from which the contour lines will be created The minimum and maximum DN values which represent what quantity of this image automatically appear as Min and Max values in the Contour Plot dialog box To adjust the starting contour value and the elevation increment between contour lines Click on the Options Add New Levels Add New Levels dialog appears Set Level Start to 0 Level Increment to 220 Calculate the number of levels required based on these values and the Min and Max values from the previous dialog box or by Computing Statistics for the Image Set the contour line color to yellow or select another color that will show up well on the grayscale SAR image Remember some colors are better suited for the screen and some for the printer you just have to experiment to arrive at a cartographic solution you like If you do not like the contour interval you can Clear the Levels from the Contour Plot dialog box select Clear Levels and perform the above processing again using a different starting value and increments Sometimes to produce a good contour map takes a little experimentation as well 3 Task 3 for Extra Credit Use the SAR image the digital elevation model and the constant saturation file saturatn which the TA has been kind enough to create for you to construct a HSV color composite that highlights both the terrain features and elevation information You will also create a 3D perspective view of this HSV color composite Write a short description of the relationship of the spatial pattern of geomorphologic features with the topography that you observed from the HSV color composite and 3D perspective view Please include the hardcopies of the HSV color composite and 3D perspective view to illustrate your description Tips 1 Use Band Math to linearly scale the elevation values of the digital elevation model into the range between 0 and 240 This scaled new DEM image will be used as a Hue image Hue Value 0 blue corresponds to the lowest elevation value and a Hue value of 240 red corresponds to the highest elevation You might think it is difficult to perform this type of scaling it actually is not and is quite commonly done In essence all you need to do is first to convert the original values to the range 0 1 This is done by dividing every value in the original DEM by the maximum value which you can determine using Compute Statistics These scaled values can then be expanded into the 0 240 range by simply multiplying by 240 Both steps can be combined into the following single equation in band math but think about why it works before just