Tag Archives: Evolution

A High-Resolution Digital Elevation Model of the Turkana Basin


Nestled in the midst of the Turkana Basin, the world’s fourth largest salt lake rests: Lake Turkana. The regions around the lake has produced numerous key hominin fossils that shape the understanding of our human origins.

The Turkana Basin is home to perhaps the most tightly controlled and extensive collection of data for hominid evolution, preserving an extensive record of biota within a dynamic geologic history stretching back to more than 4 million years. Due to the continuing work of diverse researchers from a multitude of disciplines, and from personal research interests, my project aims to create a digital elevation topographic map of the basin from existing technologies.

Conventional methods of creating topographic maps have produced maps of differing qualities: some with remarkable accuracies, some with poor accuracies.  The maps may exhibit different scales and resolutions that are inconsistent with other maps created by conventional methods. The factor of coverage due to logistic, economic, and/or political restraints contribute to missing maps across the earth. The issue of such inconsistent (conventional) topographic maps can be remedied by using an earth-wide consistent mapping strategy. The 1990s saw the rise of synthetic aperture radar (SAR) interferometry, heightening the debate of creating a consistent, affordable, and efficient global digital elevation model (DEM).

NASA’s Shuttle Radar Topography Mission: The Road to Consistency.

NASA set out to obtain the first Earth-wide high-resolution elevation topographic database of our planet using SAR interferometry. NASA’s mission–called the Shuttle Radar Topography Mission (SRTM)–repurposed and modified radar instruments from prior Space Shuttle missions for its own goals. A second antenna was added to the SRTM. A series of C-band and X-band transmit and receive antennas were retrofitted in the Space Shuttle Endeavour. The strategy using two or more SARs to capture surface deformation or digital elevation is referred to as Interferometric Synthetic Aperture Radar (InSAR). The differences of radar transmitted waves hitting the Earth’s surface were collected using two SRTM antennas and recorded on highspeed tape systems. This resulted in capturing topographic data similar to that of stereo photography.  The reader is referred to the cited literature to understand the complexities of this technology.

A space-artist’s conception of the SRTM. The green radar waves are transmitted to the Earth’s surface while the red waves represent the reflected data being transmitted back to the shuttle. Image credit: Detlev Van Ravenswaay http://www.vanravenswaay.com/index.aspx

On February 11, 2000, The Endeavour Space Shuttle launched into orbit. The Endeavour Space Shuttle orbited the Earth 176 times over a period of 11 days before returning to its home on February 22, 2000. Due to missed orbits, the SRTM did not capture some regions in North America and Antarctica. The SRTM was the first space-borne technology to capture a near-global (80% of the Earth) topographical database. The data was publicly made available in 2014.

Obtaining the SRTM data: USGS EarthExplorer

EarthExplorer is an online interactive interface tool that allows a researcher to search a wide variety of satellite images, aerial photographs, and other image data inventories of our planet. The tool was developed by the United States Geological Survey (USGS) for (free) research and academic use. NASA’s SRTM datum are hosted on USGS EarthExplorer. EarthExplorer is the tool used to obtain specific SRTM data used for the creation of our DEM.

A personal research account was created, granting access on USGS EarthExplorer. Using the interactive interface, the position of the Earth was oriented over the Turkana Basin. Under search criteria, a defined area was drawn around basin (see Figure 1) using the map coordinate tool. With the research region selected, the Data Sets tab was open with the specific criteria to search and display SRTM 1 Arc-Second Global data only. The query displayed the available SRTM grids for my pre-defined region. The interactive USGS EarthExplorer allowed me to visually examine the loci of the SRTM grids on my research area using the Show Footprint feature. Using the Browse Overlay feature allowed a small preview of the raw SRTM data inside of a grid (see 5th grid in Figure 1).

Figure 1 – USGS EarthExplorer workflow.

After visually verifying SRTM grid coverage for my research region, each SRTM grid was downloaded in the Georeferenced Tagged Image File Format (GeoTIFF). GeoTIFF is a standard image format used in GIS applications worldwide. GeoTIFFs encodes MetaTags within the image that defines projection types, coordinates and coordinate systems, ellipsoids, and other data. The GeoTIFF files were stored locally on the laboratory computer at the Paleoenvironmental Research Laboratory at Rutgers University for DEM processing and a raw copy archived on the cloud (Kuilan, 2018). A list of the SRTM GeoTIFF files used for this research are found at the end of this blog post.   

SRTM – Accuracies & Known Limitations

Although a primary goal of the SRTM was to collect data that was globally consistent, producing consistent data with quantified known errors were part of the mission. An extensive ground-truth effort using kinematic Global Positioning System (KGPS) transects was undertaken by NASA. The data were collected by land vehicles equipped with Global Positioning System (GPS) receivers along roads that can be identified by radar. The KGPS spanned six continents and the data collection effort harvested almost 9.4 million samples. An additional 86,774 Ground Control Points (GCPs) were used from NASA affiliates. The collective efforts show that ground truthing the SRTM data has an accuracy of roughly 50 cm.

The SRTM team wanted to achieve an absolute vertical accuracy within 16 m with 90% confidence. The vertical accuracies vary around the Earth, increasing in high altitude regions (e.g. Tibetan Plateau, Mount Everest). SRTM has been independently tested by various researchers since SRTM data is being widely used in various applications. Multiple studies found that SRTM’s goal of vertical accuracy and confidence are met, but one independent study found that data in some continents did not adhere to SRTM’s goal. However, the cumulative studies show that the continent of Africa—where our research site is found—adheres to SRTM’s goal. Africa has a vertical accuracy of ~10 m, more than SRTM’s goal of 16 m.

I’d like to note that a possible limitation of using SRTM data is that it will not account for topographical changes since its recording. The SRTM was a one-time mission that captured topographical data in 2000. Any significant or gradual land changes that occurred post-2000 due to weathering, erosion, tectonic activities, deposition, or other geological processes will not be reflected in contemporary SRTM terrain analyses.

The Software: Global Mapper

Global Mapper is the software used for the interpolation of SRTM data to construct our DEM of Lake Turkana. The origins of Global Mapper extend back over two decades. It was developed by the United States Geological Survey (USGS) as a Microsoft Windows tool to view their products. The tool was known as DLGV32. The USGS released the source code into the public domain in 1998. Users continued to expand DLGV32. An individual created a commercial version of the tool—DLGV32 Pro—in 2001. Within that year, DLGV32 Pro evolved in “Global Mapper,” a product of Global Mapper Software LLC, while the USGS kept distributing the DLGV32 Pro version. In 2011, Blue Marble Geographics purchased Global Mapper LLC.

The interface of Global Mapper with the Turkana Basin DEM.

Blue Marble Geographics further evolved Global Mapper to be a well-respected software in the geographic information system (GIS) world. The software is a competitive leader against other popular GIS software—such as ArcGIS—due to its small footprint and affordability. Global Mapper is able to open a wide range of popular GIS, 3D, Gridded Elevation, Raster, and Vector formats. Global Mapper has numerous integrated features that include geocoding, digitizing, rendering, data processing, GPS tracking, spatial database support, graphing, LiDAR processing, and support for Unmanned Aerial Vehicle (UAV) data. It is my opinion that what makes Global Mapper powerful is not only its collaborative design team, but their focus on listening to the real-world GIS experiences and needs of scientists, researchers, and other users.  This allows Global Mapper’s team to keep evolving their product, integrating new features in succeeding releases.

Methodology in Global Mapper

The version of Global Mapper used for the construction of the Turkana Basin DEM is v19.1 x64 edition with LiDAR module. The SRTM GeoTIFF files were opened within Global Mapper and saved as a Global Mapper Workspace (*.gmw). The Create Elevation Grid under the Analysis menu was selected and initiated. After a period of computer processing time, the Elevation Grid was completed. The processed SRTM data was now exported to DEM format.

The Enable Hill Shading feature was enabled. Shading uses light direction and shadows to emphasize the topography of a terrain, creating a 3D effect that visually allows a researcher to see how flat or hilly a region is. Global Mapper has options with dynamic variables to manipulate the direction of the light and the darkness of shadows. For our model, these options were left at default with light direction at altitude 45°, azimuth 45°.

Shaded relief is often colored. It’s a method to represent topography in a natural, aesthetic, and intuitive manner. There are many philosophies and techniques of using colors in topography. For example, a researcher creating a topographic map of a dense vegetated Amazonian region may want to use different shades of greens to differentiate botanical life, or a terrain analyst may want to create a theme of brown colors of their arid, mountainous site. The researcher can also artistically represent the topographic regions with the colors that are pleasing to them. Global Mapper has a variety of options to create custom color schemes, modify values of slope colors, or import palette files of different formats. Global Mapper has 10 color presets for shaded relief. For our model, no custom color or modifying of existing color occurred. I used 3 pre-defined stock color presets to create 3 DEMs: Atlas Shader, Global Shader, and Slope Shader.

Our color shaders result in hypsometric DEMs using the Atlas and Global shaders. It represents the elevation of the terrain with the applicable colors in gradient intervals. An Elevation Legend and Distance Scale were added to DEMs from Global Mapper’s Configuration tool. The Slope Shader based DEM has a Slope Degree legend. Legends and scales were set at 75% transparency.

3 high-resolution PDFs and 3 high-resolution JPGs were exported from Global Mapper using Atlas, Global, and Slope shaders (see Figures 1-4). Due to the rise of using Google Earth for geological applications, I decided to also export 3 high-resolution KMZ files. KMZs are Google’s Keyhole Markup Language (KML) file format that are compressed. KML/KMZ is a language that’s focused on geographic visualization and the annotation of its images and maps. The small-scale image depictions of the actual JPGs and PDFs on this article make it difficult for the viewer to appreciate the scale of detail contained. Figures 5 & 6 contains zoomed regions in an attempt for the reader to understand its scale of detail. (A list of all exported files are found at the end of this blog post.)

Below are the exported KMZ files added to Google Earth Pro.

DEM Applications

DEMs are useful in examining the sand grain mineralogy distribution to topography, hydrological flows, and to study the influence of geological structures and tectonic processes on geomorphology. Active tectonics can also produce dynamic landscapes rich in geomorphological features that may play a crucial role in long-term patterns of hominid land use and the application of satellite-derived DEMs are useful for analyses.

Image from Winder et al. 2013. The Complex Topography hypothesis, or “Scrambler Man”

A multitude of other research postulates the correlation of land features to hominid evolution events. One research puts forth the Scrambler Man” hypothesis. The argument is that the use of rugged topography by early hominins to monitor and hunt mammals would have selected for transition to an upright posture, greater speed, and agility over time. The application of DEMs might be valuable to flesh out this hypothesis and possibly correlate applicable hominin features in other rugged landscapes.

DEMs are used in the reconstruction of paleo-elevations. Constructed DEMs interpolated from satellite data can be used with modern geological data collected by researchers to work backwards to produce paleo-digital elevation models. Not only could paleo-DEMs be useful to understand ancient surface processes, but can be applied to other hominid-landscape research, such as the “Scrambler Man” hypothesis. Paleo-DEMs were invaluable to reconstruct and simulate historical tsunamis.

DEMs are also useful for topographical archaeological surveys and other archaeological applications, that if interpolated with care, it can be used in GIS for effective predication of site locations. A DEM can be analyzed to create elevation profiles and to examine the link of geomorphologies to structures which can then be plotted against existing archaeological data.

3D printed DEM from Hasiuk & Harding, 2016

An interesting application is the 3D printing of DEM data. It can be a geological teaching tool to help students with conceptual difficulties and enhance the 3D problem-solving skills of many geologists. A small-scale 3D printed DEM may prove useful at the research site for survey planning.

It is my opinion that the noted DEM applications can be of value to the rich ongoing fieldwork at the Turkana Basin.

Summary and Future Directions

The collecting of SRTM data and interpolating it into DEMs of the Turkana Basin via Global Mapper was successful. Because of the long periods of processing and resulting file sizes, it would be ideal to interpolate SRTM data to DEM on smaller, unique regions that are of primary interest to the researcher. This will allow exporting at maximum resolutions while reducing file size footprints.

I wish to create DEMs from ASTER satellite data and compare it to the SRTM DEMs via layers in Global Mapper. Further exploiting the terrain analyses tools of Global Mapper will be of use for in-depth analysis of DEMs (see following images).

3D view in Global Mapper from DEM interpolated from SRTM Data
3D view with generated contour lines overlayed on the DEM
A vertical elevation profile generated in Global Mapper using the line draw tool. The red line on top is a Cut-and-Fill feature designed to summarize the areas and volumes of change. This feature if used with satellite derived DEMS from different points in time, will allow the identification and analyses of surface material removed, surface material addtion, and areas that are unchanged
Zoomed section of DEM terrain layered with generated contour lines
Watershed analysis via Global Mapper
Generated contours from DEM via Global Mapper
Random 3D view of Turkana Basin Terrain
Turkana Basin 3D view in Wiremode

All relevant files used and exported for this DEM project are listed below. All files are found on a shared folder via my Google Drive.

Carl Sagan’s Genius: Science Through Storytelling

Carl Sagan, the scientist who worked on NASA’s Voyager probe missions, was a powerful science communicator who literally seduced the minds of millions of viewers through his charismatic storytelling. Carl Sagan understood the power of media and the power of storytelling. He synthesized both to deliver the beauty of the cosmos and science to millions of viewers through standard television desktops.

One of Carl’s most powerful examples of science through storytelling is his use of the ancient Japanese Battle of Dan-no-ura and the Heiki warriors. He used this story to demonstrate the process of artificial selection:

Storytelling is a powerful tool to communicate scientific concepts and ideas.