![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/aethiopicus_WT17000_skull_CC_lt_3qtr_sq.jpg\")
Paranthropus aethiopicus<\/strong><\/a><\/em>
<\/a>ca. 2.5 million years old<\/em> <\/figcaption><\/figure><\/li>![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/wt40000.jpg\")
Kenyanthropus platyops
<\/strong><\/em><\/a>ca. 3.5 million years old<\/figcaption><\/figure><\/li>![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/habilis_KNMER1813_skull_CC_lt_3qtr_sq.jpg\")
Homo habilis
<\/strong><\/em><\/a>ca. 1.9 million years old<\/em> <\/figcaption><\/figure><\/li>![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/rudolfensis_KNMER1470_skull_CC_lt_3qtr_sq.jpg\")
Homo rudolfensis
<\/strong><\/em><\/a>ca. 1.9 million years old<\/em> <\/figcaption><\/figure><\/li>![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/9069358731_612470e3c2_b-1024x683.jpg\")
Homo erectus
<\/strong><\/em><\/a>ca. 1.6 million years old<\/em> <\/figcaption><\/figure><\/li>![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/anamensis_KP29285_tibia_CC_sq.jpg\")
\ufeffAustralopithecus anamensis
<\/strong><\/em><\/a>ca 4.1 million years old<\/em> <\/figcaption><\/figure><\/li>![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/boisei_-KNMER406_skull_CC_rt_3qtr_sq_0.jpg\")
Paranthropus boisei
<\/strong><\/em><\/a>ca. 1.7 million years old<\/em> <\/figcaption><\/figure><\/li><\/ul>\n\n\n\nThe Turkana Basin is home to perhaps the most tightly controlled and extensive collection of data for hominid evolution<\/a>, preserving an extensive record of biota within a dynamic geologic history stretching back to more than 4 million years.<\/a> 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. <\/p>\n\n\n\n
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). <\/p>\n\n\n\n
NASA\u2019s Shuttle Radar Topography Mission: The Road to Consistency. <\/strong><\/h3>\n\n\n\n
NASA set out to obtain the first Earth-wide high-resolution elevation topographic database of our planet using SAR interferometry<\/a>. 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<\/a>). The differences of radar transmitted waves hitting the Earth\u2019s 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. <\/p>\n\n\n\n
![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/srtmart-1024x708.jpg\")
<\/a>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<\/figcaption><\/figure>\n\n\n\n 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<\/a>.<\/p>\n\n\n\n
Obtaining the SRTM data: USGS EarthExplorer<\/strong><\/h3>\n\n\n\n
EarthExplorer<\/a> 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<\/a>. The tool was developed by the United States Geological Survey (USGS) for (free) research and academic use. NASA\u2019s SRTM datum are hosted on USGS EarthExplorer. EarthExplorer is the tool used to obtain specific SRTM data used for the creation of our DEM. <\/p>\n\n\n\n
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<\/g> a grid (see 5<\/g> th<\/g><\/sup> grid in Figure 1).<\/p>\n\n\n\n ![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/blog1.jpg\")
<\/a>Figure 1 – USGS EarthExplorer workflow.<\/figcaption><\/figure>\n\n\n\n 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,<\/a> and other data. The GeoTIFF files were stored locally on the laboratory computer at the Paleoenvironmental Research Laboratory <\/a>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<\/g> found at the end of this blog post. <\/p>\n\n\n\n SRTM \u2013 Accuracies & Known Limitations<\/strong><\/h3>\n\n\n\n
Although a primary goal of the SRTM was to collect data that was globally consistent, producing consistent <\/em>data with quantified known errors<\/em> 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<\/a> (GCPs) were used from NASA affiliates. The collective efforts show that ground truthing the SRTM data has an accuracy of roughly 50 cm. <\/p>\n\n\n\n
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\u2019s goal of vertical accuracy and confidence are met<\/a>, but one independent study found <\/a>that data in some continents did not adhere to SRTM\u2019s goal. However, the cumulative studies show that the continent of Africa\u2014where our research site is found\u2014adheres to SRTM\u2019s goal. Africa has a vertical accuracy of ~10 m, more than SRTM\u2019s goal of 16 m. <\/p>\n\n\n\n
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nI\u2019d\nlike to note that a possible limitation of using SRTM data is that it will not\naccount for topographical changes since its recording. The SRTM was a one-time\nmission that captured topographical data in 2000. Any significant or gradual\nland changes that occurred post-2000 due to weathering, erosion, tectonic\nactivities, deposition, or other geological processes will not be reflected in\ncontemporary SRTM terrain analyses. \n\n\n\n<\/p>\n\n\n\n
The Software: Global Mapper<\/strong><\/h3>\n\n\n\n
Global Mapper<\/a> 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<\/a> (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\u2014DLGV32 Pro\u2014in 2001. Within that year, DLGV32 Pro evolved in \u201cGlobal Mapper,\u201d a product of Global Mapper Software LLC, while the USGS kept distributing the DLGV32 Pro <\/a>version. In 2011, Blue Marble Geographics purchased Global Mapper LLC<\/a>. <\/p>\n\n\n\n
![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/gmapper-1024x555.jpg\")
<\/a>The interface of Global Mapper with the Turkana Basin DEM.<\/figcaption><\/figure>\n\n\n\n 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\u2014such as ArcGIS\u2014due to its small footprint and affordability<\/a>. 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<\/a>, 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<\/g> GIS experiences and needs of scientists, researchers, and other users. This allows Global Mapper\u2019s team to keep evolving their product, integrating new features in succeeding releases.<\/p>\n\n\n\n Methodology in Global Mapper<\/strong><\/h3>\n\n\n\n
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. <\/p>\n\n\n\n
The Enable Hill Shading feature was enabled. Shading uses light direction and shadows to emphasize the topography of a terrain, creating a 3D effect<\/a> 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\u00b0, azimuth 45\u00b0. <\/p>\n\n\n\n
Shaded relief is often colored.\nIt\u2019s a method to represent topography in a natural, aesthetic, and intuitive\nmanner. There are many philosophies and techniques of using colors in\ntopography. For example, a researcher creating a topographic map of a dense\nvegetated Amazonian region may want to use different shades of greens to\ndifferentiate botanical life, or a terrain analyst may want to create a theme\nof brown colors of their arid, mountainous site. The researcher can also artistically<\/em> represent the topographic\nregions with the colors that are pleasing to them. Global Mapper has a variety\nof options to create custom color schemes, modify values of slope colors, or\nimport palette files of different formats. Global Mapper has 10 color presets\nfor shaded relief. For our model, no custom color or modifying of existing\ncolor occurred. I used 3 pre-defined stock color presets to create 3 DEMs:\nAtlas Shader, Global Shader, and Slope Shader.<\/p>\n\n\n\n
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\u2019s Configuration tool. The Slope Shader based DEM has a Slope Degree legend. Legends and scales were set at 75% transparency.<\/p>\n\n\n\n
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<\/a>, I decided to also export 3 high-resolution KMZ files. KMZs are Google\u2019s Keyhole Markup Language (KML) file format that are compressed. KML\/KMZ is a language that\u2019s focused on geographic visualization and the annotation of its images and maps<\/a>. 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.)<\/p>\n\n\n\n
![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/pdfscale-671x1024.jpg\")
<\/a><\/figure>\n\n\n\n![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/atlas1-620x1024.png\")
<\/a>Figure 2 – Small scaled example of the exported Atlas Shader high-res JPG.<\/figcaption><\/figure><\/li> ![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/global1-618x1024.png\")
<\/a>Figure 3 – Small scaled example of the exported Global Shader high-res JPG.<\/figcaption><\/figure><\/li> ![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/slope1-619x1024.png\")
<\/a>Figure 4 – Small scaled example of the exported Slope Shader high-res JPG.<\/figcaption><\/figure><\/li><\/ul>\n\n\n\n ![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/zoom1-1015x1024.jpg\")
<\/a><\/figure>\n\n\n\n![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/zoom2.jpg\")
<\/a><\/figure>\n\n\n\nBelow are the exported KMZ files added to Google Earth Pro.<\/em><\/p>\n\n\n\n
![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/AtlasGoogle-1024x556.jpg\")
<\/a><\/figure><\/li>![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/GlobalGoogle-1024x556.jpg\")
<\/a><\/figure><\/li>![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/SlopeGoogle-1024x556.jpg\")
<\/a><\/figure><\/li><\/ul>\n\n\n\nDEM Applications<\/strong><\/h3>\n\n\n\n
DEMs are useful in examining the sand grain mineralogy distribution to topography<\/a>, hydrological flows, and to study the influence of geological structures and tectonic processes<\/a> 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<\/a> and the application of satellite-derived DEMs are useful for analyses.<\/p>\n\n\n\n
![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/complextopo.png\")
<\/a>Image from Winder et al. 2013. The Complex Topography hypothesis, or “Scrambler Man”<\/figcaption><\/figure><\/div>\n\n\n\n A multitude of other research postulates the correlation of land features to hominid evolution events. One research puts forth the \u201c<\/a>Scrambler <\/a>Man\u201d hypothesis<\/a>. 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.<\/p>\n\n\n\n
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<\/g> to produce paleo-digital elevation models<\/a>. Not only could paleo-DEMs be useful to understand ancient surface processes,<\/g> but can be applied to other hominid-landscape research, such as the \u201cScrambler Man\u201d hypothesis. Paleo-DEMs were invaluable to reconstruct and simulate historical tsunamis<\/a>. <\/p>\n\n\n\n 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<\/g> of site locations<\/a>. A DEM can be analyzed to create elevation profiles and to examine the link of geomorphologies to structures <\/a>which can then be plotted against existing archaeological data.<\/p>\n\n\n\n ![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/3dprint.jpg\")
<\/a>3D printed DEM from Hasiuk & Harding, 2016<\/figcaption><\/figure><\/div>\n\n\n\n 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 geologis<\/a>ts. A small-scale 3D printed DEM may prove useful at the research site for survey planning. <\/p>\n\n\n\n
It is my opinion that the noted DEM applications can be of value to the rich ongoing fieldwork at the Turkana Basin. <\/p>\n\n\n\n
Summary and Future Directions<\/strong><\/h3>\n\n\n\n
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. <\/p>\n\n\n\n
I wish to create DEMs from ASTER satellite data<\/a> 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).<\/p>\n\n\n\n
![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/sideview2-1024x546.jpg\")
<\/a>3D view in Global Mapper from DEM interpolated from SRTM Data <\/figcaption><\/figure>\n\n\n\n ![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/GS3-1024x563.png\")
<\/a>3D view with generated contour lines overlayed on the DEM<\/figcaption><\/figure>\n\n\n\n ![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/gs4-1024x600.jpg\")
<\/a>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 <\/figcaption><\/figure>\n\n\n\n ![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/topo3-1024x598.jpg\")
<\/a>Zoomed section of DEM terrain layered with generated contour lines<\/figcaption><\/figure>\n\n\n\n ![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/watershed3-1024x598.jpg\")
<\/a>Watershed analysis via Global Mapper<\/figcaption><\/figure>\n\n\n\n ![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/topo2-1024x600.jpg\")
<\/a>Generated contours from DEM via Global Mapper<\/figcaption><\/figure>\n\n\n\n ![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/3d-night-1024x540.jpg\")
<\/a>Random 3D view of Turkana Basin Terrain<\/figcaption><\/figure>\n\n\n\n ![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/wiremode1-1024x533.jpg\")
<\/a>Turkana Basin 3D view in Wiremode<\/figcaption><\/figure>\n\n\n\n <\/p>\n\n\n\n
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. <\/a><\/p>\n\n\n\n
<\/p>\n\n\n\n
![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/exportfiles.jpg\")
<\/a><\/figure><\/li>![\"\"](\"http:\/\/antoniokuilan.com\/blog\/wp-content\/uploads\/2019\/01\/srtmfiles.jpg\")
<\/a><\/figure><\/li><\/ul>\n","protected":false},"excerpt":{"rendered":"Introduction 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, … Continue reading A High-Resolution Digital Elevation Model of the Turkana Basin<\/span>