Observation of large fixed sand dunes of Taklimakan Desert using satellite imagery

2007 ◽  
Vol 39 (1) ◽  
pp. 60-64 ◽  
Author(s):  
Kiyoshi Tsuchiya ◽  
Yoshinari Oguro
Keyword(s):  
Satellite Imagery ◽  
Sand Dunes ◽  
Taklimakan Desert

scholarly journals Onset of permanent Taklimakan Desert linked to the mid-Pleistocene transition

Geology ◽  
2020 ◽  
Vol 48 (8) ◽  
pp. 782-786
Author(s):  
Weiguo Liu ◽  
Zhonghui Liu ◽  
Jimin Sun ◽  
Chunhui Song ◽  
Hong Chang ◽  
...  
Keyword(s):  
Tarim Basin ◽  
Sand Dunes ◽  
Western China ◽  
Taklimakan Desert ◽  
The Tibetan Plateau ◽  
Mountain Glaciers ◽  
Long Period ◽  
Carbonate Carbon ◽  
Eolian Sand ◽  
Desert Landscape

Abstract The initial occurrence of desert landscape or eolian sand dunes is thought to have occurred long before the Pleistocene, and desertification was subsequently enhanced under cold, dusty glacial conditions. However, when and how the desert landscape persisted during both glacial and interglacial periods, defined as “permanent” desert here, remain elusive. Here, we present carbonate carbon isotope and grain-size records from the Tarim Basin, western China, revealing a detailed desertification history for the Taklimakan Desert. Our records demonstrate that after desiccation of episodic lakes at ca. 4.9 Ma, alternations of eolian sand dunes and fluvial and playa-like conditions persisted for a long period until 0.7 Ma in the Tarim Basin. The onset of permanent desert landscape around 0.7–0.5 Ma occurred concurrently with the climatic reorganization across the mid-Pleistocene transition. The occurrence of mountain glaciers on the Tibetan Plateau and atmospheric circulation changes may have controlled the formation and extreme aridification of the permanent desert in inland Asia since the mid-Pleistocene transition.

Geomorphology of sand dunes in the Northeast Taklimakan Desert

Geomorphology ◽  
2002 ◽  
Vol 42 (3-4) ◽  
pp. 183-195 ◽  
Author(s):  
Xunming Wang ◽  
Zhibao Dong ◽  
Jiawu Zhang ◽  
Guangting Chen
Keyword(s):  
Sand Dunes ◽  
Taklimakan Desert

scholarly journals Auto-Extraction of Linear Archaeological Traces of Tuntian Irrigation Canals in Miran Site (China) from Gaofen-1 Satellite Imagery

2018 ◽  
Author(s):  
Lei Luo ◽  
Xinyuan Wang ◽  
Rosa Lasaponara ◽  
Bo Xiang ◽  
Jing Zhen ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Agricultural Landscape ◽  
Western China ◽  
Taklimakan Desert ◽  
Irrigation Canals ◽  
Multispectral Data ◽  
Edge Operator ◽  
Average Accuracy ◽  
Canny Edge ◽  
Gis Environment

This paper describes the use of the Chinese Gaofen-1 (GF-1) satellite imagery to automatically extract tertiary Linear Archaeological Traces of Tuntian Irrigation Canals (LATTICs) located in the Miran site. The site is adjacent to the ancient Loulan Kingdom at the eastern margin of the Taklimakan Desert in western China. GF-1 data was processed following atmospheric and geometric correction, and spectral analyses were carried out for multispectral data. The low values produced by SSI indicate that it is difficult to distinguish buried tertiary LATTICs from similar backgrounds using spectral signatures. Thus, based on the textual characteristics of high-resolutionGF-1 panchromatic data, this paper proposes an automatic approach that combines joint morphological bottom and hat transformation with a Canny edge operator. The operator was improved by adding stages of geometric filtering and gradient vector direction analysis. Finally, the detected edges of tertiary LATTICs were extracted using the GIS-based draw tool and converted into shapefiles for archaeological mapping within a GIS environment. The proposed automatic approach was verified with an average accuracy of 95.76% for 754 tertiary LATTICs in the entire Miran site and compared with previous manual interpretation results. The results indicate that GF-1 VHR PAN imagery can successfully uncover the ancient tuntian agricultural landscape. Moreover, the proposed method can be generalized and applied to extract linear archaeological traces such as soil and crop marks in other geographic locations.

scholarly journals DETECTION OF LAND COVER DISPLACEMENTS THROUGH TIME-SERIES ANALYSIS OF MULTISPECTRAL SATELLITE IMAGERY: APPLICATION TO DESERT

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 739-744
Author(s):  
D. Oxoli ◽  
M. A. Brovelli ◽  
D. Frizzi ◽  
S. Martinati
Keyword(s):  
Land Cover ◽  
Satellite Imagery ◽  
Sand Dunes ◽  
Open Data ◽  
Landsat 8 ◽  
Spatial And Temporal Patterns ◽  
Extensive Discussion ◽  
Detection Techniques ◽  
Desert Sand ◽  
Cross Correlation Analysis

Abstract. Detection of changes occurring on Earth surface has become an established practice in remote sensing science since the availability of high-resolution, global coverage, and multitemporal satellite imagery that has constantly increased during the last decades. Meanwhile, the open data policies embraced by some of the principal Earth Observation programs have boosted the spread of such analyses. This asset has attracted also the interest of the private sector which is developing strategies to exploit the potential of these data. In view of the above, we present an experimental procedure to investigate land cover displacements through an application on open multispectral imagery from the Landsat 8 and Sentinel-2 missions for desert sand dunes movements analysis. While most of the change detection techniques focus on locating changes and describing them by means of variation in the pixel spectral responses, the proposed technique aims at describing spatial and temporal patterns of displacements (i.e. directions and magnitude) applying cross-correlation analysis on a multitemporal images stack. Results of the proposed analysis are critical to a number of construction engineering operations that require sand mitigation planning and continuous site monitoring to prevent windblown sand interactions with infrastructures in the desert environment. An overview of the preliminary results is presented together with an extensive discussion on further improvements requested by the procedure. Computational steps leverage exclusively open data and free and open source GIS software thus providing large rooms to empower, replicate and improve thereof.

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