A DTM (or synonymously DEM for Digital Elevation Model) is a grid, or raster, file describing elevation values at regularly spaced points, or posts.

HiRISE DTMs are made from two images of the same area on the ground, taken from different look angles. All the stereo pairs acquired so far are available here. Not all of these have been made into DTMs due to the time-intensive process. Creating a DTM is complicated and involves sophisticated software and a lot of time, both computing time and man-hours.

As mentioned in a previous post, the great advantage of a HiRISE DTM is the high resolution of the source imagery. As a general guide, terrain can be derived at a post spacing about 4X the pixel scale of the input imagery. HiRISE images are usually 0.25 – 0.5 m/pixel, so the post spacing is 1-2 m with vertical precision in the tens of centimeters.

The three basic stages of creating a DTM are:

1. Prepare the images for ingestion into the stereo software
2. Triangulate the images
3. Extract terrain

In order to prepare the images, we must first correct the geometry by removing any optical distortions inherent to HiRISE. Then the spacecraft pointing information at the time of each observation is gathered.

Triangulation is also called bundle adjustment. This step requires the most operator skill and time. The result is a transformation of the original images to epipolar space. What this means is that all the stereo information is now captured in the horizontal direction, or x-parallax. During triangulation, we also align the stereo model to MOLA elevations, so the end result is tied to the global elevation map produced by the MOLA instrument team. This is the same map that you see in the context map pane of every HiRISE observation page.

Once the images are triangulated, then terrain can be extracted. This step is computationally intensive, but automated, so it just takes a lot of computer time. The output of terrain extraction is reviewed for any artifacts or errors. These are edited out if possible. Since editing is extremely time-consuming, it is only done on easily corrected errors and in the areas of most interest to the researcher. The less editing we have to do, the better, so a lot of effort goes into preparing the images so that the input is as high quality as possible. The excellent contrast and value range of HiRISE imagery usually result in high quality terrain extraction that requires minimal editing.

After we have terrain, we can make other products, such as orthoimages. An orthoimage is a picture that has been orthorectified. This means that the pixels have been projected so that at each pixel it is as if you are looking directly down at the terrain. In the original stereo images, we rely on the fact that there are topographical distortions (parallax) to derive the elevations in the terrain model. In the orthoimages, all topographic distortions have been removed.

The final products are map projected using the same mapping definitions as the regular HiRISE RDR products.

A really useful (and cool) thing to do with the orthoimages is to drape them over the terrain for 3D viewing. Below is a subimage from the Newton Gullies DTM showing the imagery draped over the terrain.

You can see animated fly-throughs made with HiRISE DTMs by going to the HiClips page and clicking on the JPL Flythrough Clips. This is a great way to see and understand the geological relationships from a ground perspective.

Researchers use DTMs to take measurements and model geological processes. DTMs are very powerful research tools. In fact, almost every HiRISE DTM produced results in publication. There is a long waiting list for these products because they are so valuable and so difficult to produce. Several institutions involved with HiRISE contribute to DTM production to maximize the number of projects produced and to avoid duplication of effort.

Standard PDS products linked to the DTM project page are usually quite large files. The links provided will download the files to your system. To get a quick view of what the project looks like, click on the Extras links to see a reduced version of the products, displayed as images, grayscale, shaded relief and colorized altimetry.

Standard PDS products:

• The DTM in standard PDS image object (.IMG) format with an embedded label
• The left orthoimage at the same resolution as the DTM, in JPEG2000 format with detached label
• The left orthoimage at the resolution of the original image, in JPEG2000 format with detached label
• The right orthoimage at the same resolution as the DTM, in JPEG2000 format with detached label
• The right orthoimage at the resolution of the original image, in JPEG2000 format with detached label

Extras available in the PDS Extras directory (letters in parentheses correspond to PDS file names such as <Product_ID>.br.jpg):

• Browse (br), annotated browse (ab), and thumbnail (th) jpegs of the DTM as a grayscale image
• Browse (sb), annotated browse (sa), and thumbnail (st) jpegs of the DTM as a shaded relief image
• Browse (cb), annotated browse (ca), and thumbnail (ct) jpegs of the DTM as colorized altimetry
• Browse (br), annotated browse (ab), and thumbnail (th) jpegs of the lower resolution orthoimages

PDS product naming convention for HiRISE DTMs:

PRODUCT_ID = aabcd_xxxxxx_xxxx_yyyyyy_yyyy_Vnn
where
aa = DT, indicating it’s a DTM product
b = type of data

• E = areoid elevations
• 1 = orthoimage pixels from first image
• 2 = orthoimage pixels from second image

c = projection (others are possible but these are the important ones)

• E = Equirectangular
• P = Polar Stereographic

d = grid spacing (think of this as pixel scale in meters)

• A = 0.25 m
• B = 0.5 m
• C = 1.0 m
• D=2.0 m

xxxxxx_xxxx = orbit number and latitude bin from SOURCE_PRODUCT_ID[1]
yyyyyy_yyyy = orbit number and latitude bin from SOURCE_PRODUCT_ID[2]
V = letter indicating producing institution

• U = USGS
• A = University of Arizona
• C = CalTech
• N = NASA Ames
• J = JPL
• O = Ohio State
• Z = other

nn= 2 digit version number

Below is an example of the set of annotated browse images for the Russell Crater Dunes DTM.

The grayscale image of the DTM looks weird, if you have not looked at lots of these before, but keep in mind that the color of the pixels represents elevation. The higher the elevation, the brighter the pixel. Lower elevations are darker. The shaded relief is another way of visualizing the topography. The pixels are illuminated from a certain direction, to show the relief of the topography, rather than the elevation. It is also emphasizes any artifacts in the DTM. In the example here, many artifacts (errors) can be seen such as the faceted areas and boxes in the lower left and top of the image. These artifacts are usually caused by areas of low contrast (such as in this project) or sharply differing shadows. Most HiRISE DTMs will not have a lot of these artifacts, fortunately! The area of most interest to the researcher who requested this DTM was the long slope with the gullies, which was well-illuminated and had good contrast. So in that area, there were few, if any, artifacts. Adding color-coded elevation to the shaded relief creates the colorized altimetry map, where the lowest elevations are purple, green is the median elevation value, and white is the highest elevation. In the Russell Crater Dunes project shown here, the difference in elevation from the highest to the lowest point is almost 590 meters (~1935 ft.). That is a tall dune!!

We are happy to be able to share HiRISE DTMs with the scientific community and with the public. We will continue to release more DTMs as they become available, so stay posted!

Here is a tip: once you have translated a page, all pages on the HiRISE website that you click through will be translated, too! There will be a link at the top of your browser to return to the original page. You can also hover over a sentence to see it in the original language, English.

Look for the little flag buttons on the right hand side of an observation page, under the link to Facebook.

We hope our international viewers benefit from this added feature.

We would love to be able to release a DEM for every HiRISE stereo pair, but alas, they don’t exist yet! We here at HiROC and a few other groups have made some DEMs, but only a small percentage of all the acquired stereo has  been processed so far. Why?? Because creating a DEM is actually quite difficult, and requires specialized software and a fair amount of time.

But there is hope! So far, the USGS Astrogeology group has created several DEMs in support of the MSL landing site selection workshops, the Phoenix lander and the MER mission. They are available on the USGS website. Here is an example of one of their products:

Columbia Hills DEM

Soon, we will begin preparing the DEMs we have made for release to the PDS Imaging Node. So stay tuned…

This process seems simple in concept, but in practice it is quite complicated. There are three factors to account for:

• Relative timing
• Pixel binning
• Spacecraft jitter

First of all, HiRISE nearly always uses different resolutions for each color. For instance, RED might be at a scale of 25 cm/pixel (bin1) while IR and BG are at 1 meter/pixel (bin4). This “binning” minimizes the amount of data that has to be sent back to Earth, which is the most important constraint that HiRISE needs to deal with. Another reason for binning color is to improve the signal-to-noise ratio (SNR). This means that you can get a better signal by combining pixels at the expense of spatial resolution. In order to get the binned IR and BG images to line up properly, they must be enlarged to match the dimensions of the RED image. For example: RED is bin1, IR and BG are bin2. The RED image will be 2000 pixels wide by 40,000 pixels long (for example), the corresponding IR and BG images will be 1000 pixels wide by 20,000 pixels long. So the first step is to make the dimensions of all three images match.

Now the relative timing is easy to take care of. The start time of all images is a known quantity, and does not change from image to image. We know exactly when the BG detector starts imaging, followed by the RED detector, followed by the IR detector. So the beginning of each image is offset by a fixed amount. Once the images are shifted by this fixed offset (accounting for binning), they will be approximately lined up.

This brings us to the third factor in coregistering images — spacecraft jitter. Because HiRISE is imaging at such a high spatial resolution and at great speed, tiny motions of the MRO spacecraft cause slight variations in where the surface features appear in each of the three color detectors. Imagine that HiRISE is taking a picture of a 1m sized boulder on Mars. If the rock shows up in line 100 of the RED image, and we have already accounted for the relative offsets of the detectors and for binning, then the rock should also show up in line 100 of the BG image. But say we look and it is actually in line 99. Now when we try to stack the two images, the objects in them won’t line up exactly. Our color processing software corrects for this by holding the RED image fixed, and adjusting the corresponding BG and IR images to match it precisely. This is not a perfect process, but most of the time it works extremely well.

Producing the color HiRISE products is not a trivial process. But it is to a point where the processing is automated so new data is released without delay. Enjoy the colorful view!

The magic happens when we succeed at coregistering the IR and BG to the RED parts of the image to produce the center strip, false color images. More about this in an upcoming post. The maximum width of a color image is 4048 pixels. Some HiRISE images are 100,000 pixels long, which makes for a very long skinny image. These are affectionately dubbed “color noodles” by the HiPI (PI=Principle Investigator).

The image below illustrates where the color portion of the image is located. The zoomed in part of the same image just shows more clearly how the colors can offer more detailed geologic information than is available in the RED (black and white) image. For detailed information about the use of the color products and how they can be interpreted for scientific purposes, please refer to “Information for Scientific Users of HiRISE Color Products”

Is this what Mars really looks like? The images are not true color. The three color images taken by HiRISE are coregistered and stacked on top of each other. Then each color layer is assigned to red, blue or green, because those are the colors that are projected on your screen. So you can see how the word “color” becomes quite confusing. First, red is black and white. Then, we have all those I’s R’s and G’s and B’s! The color in HiRISE color products is really false color, because we are assigning a visible color to one that is invisible to human eyes. Also, there are only three wavelengths of light, not the full visible spectrum we are used to seeing. The RGB products are more similar to “natural” color. Even with HiRISE’s limited color capability, there is still an incredible amount of information gained by having the two extra wavelengths.

Why is there a garish green strip along the right side of the color image (left side in the nomap products)? You will notice this in some of the HiRISE color products. It will be apparent in the IRB, but not the RGB products. This is due to one half of the IR10 CCD having electronics issues during the earlier part of the mission. This problem was resolved for most cases, so that later images have both channels of IR10 — no green strip. Some of the earlier images were also able to be reprocessed to restore the missing IR information.

What is the difference between “RGB” and “IRB”? The RGB products are different than the IRB products in that the IR channel has been replaced by a “synthetic blue” layer that creates an image that is somewhat closer to natural color. In many of the images, the infrared band does not contribute a lot of information. The bands in this product have also been stretched to provide better contrast. In other words, the RGB images are more aesthetic. The IRB product is a science product. It contains the IR, RED and BG layers.

In the IAS viewer, you can turn the bands on and off to see what information each one contributes to a particular image. Use this button to switch from color to grayscale. This dialogue will also allow you to switch the color assigned to each band. The way the images are stacked in the HiRISE images goes like this:

Changing two bands to display the same color will show what kind of information is contributed by each band.

Below is a detail from PSP_004052_2045 showing the IRB color overlaid on the RED image. It is a beautiful example of how the color available in HiRISE images gives us new information that aids in interpreting the images. They are also just plain beautiful.