Spatial distribution and geomorphology of lunette dunes on the High Plains of Western Kansas: implications for geoarchaeological and paleoenvironmental research

Bowen, Mark W.; Johnson, William C.; King, Dylan

doi:10.1080/02723646.2017.1319683

Cited by 10 publications

(5 citation statements)

References 31 publications

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“…There are over 20,000 of these playas in Kansas, with a median area of 0.0064 km 2 , a mean area of 0.0165 km 2 , a maximum area of 1.872 km 2 , and a minimum area of 0.0003 km 2 [74], all of which follow quite closely but are slightly smaller than area parameters for Carolina bays. The median heights of the lunettes were reported as 3 m [78], similar to the heights of the sand rims found in Carolina bays. The similarities between the Kansan playa-lunette systems and Carolina Bays of great interest and deserve further attention in future research.…”

Section: Discussionsupporting

confidence: 72%

“…Another similar feature, found in great number in the high plains of Kansas, as well as in the West Siberian Plain, are playa-lunette systems [73][74][75][76][77][78]. These are depressions that Looking at the sedimentology and stratigraphic results, Carolina Bays show signs of aeolian and lacustrine processes, not signs of an impact origin.…”

Section: Discussionmentioning

confidence: 99%

“…Another similar feature, found in great number in the high plains of Kansas, as well as in the West Siberian Plain, are playa-lunette systems [73][74][75][76][77][78]. These are depressions that form in arid climates, where unconsolidated sediment (typically loess in Kansas, and alluvial deposits in the West Siberian Plain) gets scoured out by wind, and if the climate remains dry and unconducive to vegetative growth, sediment can often get deposited on one end of the depression and form a dune-like mound known as a lunette [77].…”

Section: Discussionmentioning

confidence: 99%

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Using Convolutional Neural Networks for Detection and Morphometric Analysis of Carolina Bays from Publicly Available Digital Elevation Models

Lundine

Trembanis

2021

Remote Sensing

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Carolina Bays are oriented and sandy-rimmed depressions that are ubiquitous throughout the Atlantic Coastal Plain (ACP). Their origin has been a highly debated topic since the 1800s and remains unsolved. Past population estimates of Carolina Bays have varied vastly, ranging between as few as 10,000 to as many as 500,000. With such a large uncertainty around the actual population size, mapping these enigmatic features is a problem that requires an automated detection scheme. Using publicly available LiDAR-derived digital elevation models (DEMs) of the ACP as training images, various types of convolutional neural networks (CNNs) were trained to detect Carolina bays. The detection results were assessed for accuracy and scalability, as well as analyzed for various morphologic, land-use and land cover, and hydrologic characteristics. Overall, the detector found over 23,000 Carolina Bays from southern New Jersey to northern Florida, with highest densities along interfluves. Carolina Bays in Delmarva were found to be smaller and shallower than Bays in the southeastern ACP. At least a third of Carolina Bays have been converted to agricultural lands and almost half of all Carolina Bays are forested. Few Carolina Bays are classified as open water basins, yet almost all of the detected Bays were within 2 km of a water body. In addition, field investigations based upon detection results were performed to describe the sedimentology of Carolina Bays. Sedimentological investigations showed that Bays typically have 1.5 m to 2.5 m thick sand rims that show a gradient in texture, with coarser sand at the bottom and finer sand and silt towards the top. Their basins were found to be 0.5 m to 2 m thick and showed a mix of clayey, silty, and sandy deposits. Last, the results compiled during this study were compared to similar depressional features (i.e., playa-lunette systems) to pinpoint any similarities in origin processes. Altogether, this study shows that CNNs are valuable tools for automated geomorphic feature detection and can lead to new insights when coupled with various forms of remotely sensed and field-based datasets.

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Section: Discussionsupporting

confidence: 72%

“…Another similar feature, found in great number in the high plains of Kansas, as well as in the West Siberian Plain, are playa-lunette systems [73][74][75][76][77][78]. These are depressions that Looking at the sedimentology and stratigraphic results, Carolina Bays show signs of aeolian and lacustrine processes, not signs of an impact origin.…”

Section: Discussionmentioning

confidence: 99%

“…Another similar feature, found in great number in the high plains of Kansas, as well as in the West Siberian Plain, are playa-lunette systems [73][74][75][76][77][78]. These are depressions that form in arid climates, where unconsolidated sediment (typically loess in Kansas, and alluvial deposits in the West Siberian Plain) gets scoured out by wind, and if the climate remains dry and unconducive to vegetative growth, sediment can often get deposited on one end of the depression and form a dune-like mound known as a lunette [77].…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Using Convolutional Neural Networks for Detection and Morphometric Analysis of Carolina Bays from Publicly Available Digital Elevation Models

Lundine

Trembanis

2021

Remote Sensing

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“…While this study has focused on alluvial environments, it has implications for the application of lidar data where archaeological resources do not lie immediately below the modern ground surface but are buried beneath accumulated sediments (e.g., colluvial, aeolian, coastal, estuarine, and lacustrine deposits). Lidar has been used extensively in geoarchaeological research to study a wide range of different environments (e.g., Bowen et al, 2018; Carlson & Baichtal, 2015; Gregory et al, 2021; Lausanne et al, 2021) and many of these investigations would benefit from the integration of lidar within a deposit modelling framework to define surface evidence for any variations within these complex depositional zones. As such, it would be beneficial to expand this study to evaluate a larger number of landforms and a wider range of environments.…”

Section: Discussionmentioning

confidence: 99%

Lidar visualization techniques for the construction of geoarchaeological deposit models: An overview and evaluation in alluvial environments

et al. 2023

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Lidar has become an essential tool for the mapping and interpretation of natural and archaeological features within the landscape. It is also increasingly integrated and visualized within geoarchaeological deposit models, providing valuable topographic and stratigraphic control from the contemporary ground surface downwards. However, there is a wide range of methods available for the visualization of lidar elevation models and a review of existing research suggests that it remains unclear which are most appropriate for geoarchaeological applications. This paper addresses this issue by providing an overview and quantitative evaluation of these techniques with examples from archaeologically resource‐rich alluvial environments. Owing to the relatively low‐relief nature of the terrain within these temperate lowland flood plain environments, the results show that there is a small number of visualization methods that demonstrably improve the detection of geomorphological landforms that can be related to the variable distribution of archaeological resources. More specifically, a combination of Relative Elevation Models combined with Simple Local Relief Models offered an optimal approach that subsequently allows integration with deposit models. Whilst the presented examples are from a flood plain setting, deposit models are pertinent to a range of landscape contexts and the methodology applied here has wider applicability.

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“…Playas are ephemeral or desiccated lakes found throughout arid and semi‐arid regions of the world (Goudie and Wells, ; Yechieli and Wood, ; Shaw and Bryant, ; Goudie, ). In North America, they have been described in the Northern (Last and Schweyen, ), Central (Bowen and Johnson, , ; Bowen et al ., ) and Southern Great Plains (Wood et al ., ; Gustavson et al, ; Holliday, ; Holliday et al ., ), arid basins of the southern Pacific Coast Ranges (Eghbal et al ., ), the Mexican Plateau (Alcocer and Escobar, ) and throughout the Basin and Range region (Currey, ; Scuderi et al ., ). Due to their ephemeral nature playas are highly sensitive to climatic fluctuations and are influenced, often simultaneously, by fluvial, lacustrine and eolian processes (Holliday, ; Holliday et al ., ; Bowen and Johnson, , ; Rich, ), making them useful paleoenvironmental archives.…”

Section: Introductionmentioning

confidence: 99%

Characterizing formation processes of Rimrock Lake, a Late Pleistocene–Holocene playa, Harney Basin, south‐eastern Oregon, USA, using an end‐member mixing analysis

Collins

Gill

Langford

2018

J Quaternary Science

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Playas collect sediments from different transported processes, producing grain-size distributions (GSDs) reflecting changes in environment. End-member mixing analysis (EMMA) was used to derive end-members (EMs) from 256 sediment samples from Rimrock Lake (Harney Basin, Oregon, USA) and a nearby relict channel. EMMA identified six EMs representing deposition in fluvial, lacustrine, littoral and colluvial environments. Stratigraphy was time-correlated using nine radiocarbon dates. Results show that Rimrock Lake existed by $ 18 535 cal a BP. A relict playa surface also was exposed along its margin and indicates lake contraction $ 6190-5990 cal a BP. In the relict channel, a dominant eolian environment is identified at $ 8000 cal a BP. These results represent a shift to a more arid environment in the Harney Basin beginning around the mid-Holocene and are in general agreement with other studies reported in the Great Basin. This study demonstrates the application of EMMA for analyzing complex playa sediments and for linking environmental response across separate but related geomorphic environments. Our results provide a paleoenvironmental record along Harney Basin's western margin between $ 18 500 and 6000 cal a BP and demonstrate the use of small playas in the basin as environmental archives. Figure 2. (A) Modified Google Earth image of Rimrock Lake with geomorphic features, core locations and Trench 1 identified. (B) Modified Google Earth image of Rimrock Draw Rockshelter with excavation units, Trench 2 and channel boundary identified (dashed line).

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Spatial distribution and geomorphology of lunette dunes on the High Plains of Western Kansas: implications for geoarchaeological and paleoenvironmental research

Cited by 10 publications

References 31 publications

Using Convolutional Neural Networks for Detection and Morphometric Analysis of Carolina Bays from Publicly Available Digital Elevation Models

Using Convolutional Neural Networks for Detection and Morphometric Analysis of Carolina Bays from Publicly Available Digital Elevation Models

Lidar visualization techniques for the construction of geoarchaeological deposit models: An overview and evaluation in alluvial environments

Characterizing formation processes of Rimrock Lake, a Late Pleistocene–Holocene playa, Harney Basin, south‐eastern Oregon, USA, using an end‐member mixing analysis

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