Recent advances in research on the aeolian geomorphology of China's Kumtagh Sand Sea

Dong, Zhibao; Lv, Ping

doi:10.5194/adgeo-37-41-2014

Cited by 6 publications

(5 citation statements)

References 13 publications

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“…There is currently ongoing debate amongst Chinese desert geomorphologists as to the definition and classification of the Desert's feather-like dune fields (Dong et al, 2008;Dong, 2009;Wang et al, 2009;Qu et al, 2011;Qian et al, 2015). Previous geomorphological studies in the Kumtagh Desert by Chinese scientists during the last decade have been selectively translated and reviewed by Dong and Lv (2014).…”

Section: Regional Settingmentioning

confidence: 99%

Inverted relief landforms in the Kumtagh Desert of northwestern China: a mechanism to estimate wind erosion rates

Wang

Lai

2015

Geol. J.

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Although commonly found in deserts, our knowledge about inverted relief landforms is very limited. The so‐called ‘Gravel Body’ in the northern Kumtagh Desert is an example of an inverted relief landform created by the exhumation of a former fluvial gravel channel. The common occurrence of these landforms indicates that fluvial processes played an important role in shaping the Kumtagh Desert in the past 151 ka. A physical model is presented to reconstruct the palaeohydrology of these fluvial channels in terms of several measurable parameters including terrain slope, boulder size, and channel width. Combining the calculated palaeoflood depth, the maximal depth of channel bed eroded by wind, and the current height of inverted channels with the age of the aeolian sediments covered by gravels, the local wind erosion rate is estimated to be 0.21–0.28 mm/year. It is shown that wind erosion occurring in the Kumtagh Desert is no more severe than in adjacent regions. Since the modern Martian environment is very similar to that of hyperarid deserts on Earth, and Mars was once subjected to fluvial processes, this study will be helpful for understanding the origin of analogous Martian surface landforms and their causative processes. Copyright © 2015 John Wiley & Sons, Ltd.

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Section: Regional Settingmentioning

confidence: 99%

Inverted relief landforms in the Kumtagh Desert of northwestern China: a mechanism to estimate wind erosion rates

Wang

Lai

2015

Geol. J.

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“…Additionally, with the rapid development of machine learning, deep learning and other methods to segment the content of images at the pixel level, image segmentation has been used in classification tasks. The related steps include creating training sets, designing Aeolian landforms are the most prevalent and active geomorphic features on Mars, and the ancient Chinese name for Mars "Yinghuo, " is in part due to the sand phenomenon that causes Mars to be bright and pale (Dong et al, 2020b). developed a similar visual degradation process based on the remote sensing images of "Tianwen-1" to synthesize real dust images and used these real dust images to train a deep learning model to identify dust-free images, inspired by the fog formation process on Earth.…”

Section: Methods Of Classifying Martian Landformsmentioning

confidence: 99%

New Advances in Lunar and Related Planetary Studies

Zhang

2024

Frontiers Research Topics

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Frontiers is more than just an open access publisher of scholarly articles: it is a pioneering approach to the world of academia, radically improving the way scholarly research is managed. The grand vision of Frontiers is a world where all people have an equal opportunity to seek, share and generate knowledge. Frontiers provides immediate and permanent online open access to all its publications, but this alone is not enough to realize our grand goals. Frontiers journal seriesThe Frontiers journal series is a multi-tier and interdisciplinary set of openaccess, online journals, promising a paradigm shift from the current review, selection and dissemination processes in academic publishing. All Frontiers journals are driven by researchers for researchers; therefore, they constitute a service to the scholarly community. At the same time, the Frontiers journal series operates on a revolutionary invention, the tiered publishing system, initially addressing specific communities of scholars, and gradually climbing up to broader public understanding, thus serving the interests of the lay society, too. Dedication to qualityEach Frontiers article is a landmark of the highest quality, thanks to genuinely collaborative interactions between authors and review editors, who include some of the world's best academicians. Research must be certified by peers before entering a stream of knowledge that may eventually reach the public -and shape society; therefore, Frontiers only applies the most rigorous and unbiased reviews. Frontiers revolutionizes research publishing by freely delivering the most outstanding research, evaluated with no bias from both the academic and social point of view. By applying the most advanced information technologies, Frontiers is catapulting scholarly publishing into a new generation. What are Frontiers Research Topics?Frontiers Research Topics are very popular trademarks of the Frontiers journals series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area.

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“…Additionally, with the rapid development of machine learning, deep learning and other methods to segment the content of images at the pixel level, image segmentation has been used in classification tasks. The related steps include creating training sets, designing Aeolian landforms are the most prevalent and active geomorphic features on Mars, and the ancient Chinese name for Mars "Yinghuo, " is in part due to the sand phenomenon that causes Mars to be bright and pale (Dong et al, 2020b). Li et al (2022) developed a similar visual degradation process based on the remote sensing images of "Tianwen-1" to synthesize real dust images and used these real dust images to train a deep learning model to identify dust-free images, inspired by the fog formation process on Earth.…”

Section: Methods Of Classifying Martian Landformsmentioning

confidence: 99%

Progress and prospects for research on Martian topographic features and typical landform identification

Liu,

Cheng

2023

Front. Astron. Space Sci.

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The study of Martian surface topography is important for understanding the geological evolution of Mars and revealing the spatial differentiation of the Martian landscape. Identifying typical landform units is a fundamental task when studying the origin and evolution of Mars and provides important information for landing on and exploring Mars, as well as estimating the age of the Martian surface and inferring the evolution of the Earth’s environment. In this paper, we first investigate Mars exploration, data acquisition and mapping, and the classification methods of Martian landforms. Then, the identification of several typical Martian landform types, such as aeolian landforms, fluvial landforms, and impact landforms, is shown in detail. Finally, the prospects of Mars data acquisition, landform mapping, and the construction and identification of the Martian landform classification system are presented. The construction of the Martian landform classification system and the identification of typical Martian landforms using deep learning are important development directions in planetary science.

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Recent advances in research on the aeolian geomorphology of China's Kumtagh Sand Sea

Cited by 6 publications

References 13 publications

Inverted relief landforms in the Kumtagh Desert of northwestern China: a mechanism to estimate wind erosion rates

Inverted relief landforms in the Kumtagh Desert of northwestern China: a mechanism to estimate wind erosion rates

New Advances in Lunar and Related Planetary Studies

Progress and prospects for research on Martian topographic features and typical landform identification

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