Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1073/pnas.2005583117 |
Automated detection of archaeological mounds using machine-learning classification of multisensor and multitemporal satellite data | |
Hector A. Orengo; Francesc C. Conesa; Arnau Garcia-Molsosa; Agustín Lobo; Adam S. Green; Marco Madella; Cameron A. Petrie | |
2020-07-20 | |
发表期刊 | Proceedings of the National Academy of Science
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出版年 | 2020 |
英文摘要 | This paper presents an innovative multisensor, multitemporal machine-learning approach using remote sensing big data for the detection of archaeological mounds in Cholistan (Pakistan). The Cholistan Desert presents one of the largest concentrations of Indus Civilization sites (from ca. 3300 to 1500 BC). Cholistan has figured prominently in theories about changes in water availability, the rise and decline of the Indus Civilization, and the transformation of fertile monsoonal alluvial plains into an extremely arid margin. This paper implements a multisensor, multitemporal machine-learning approach for the remote detection of archaeological mounds. A classifier algorithm that employs a large-scale collection of synthetic-aperture radar and multispectral images has been implemented in Google Earth Engine, resulting in an accurate probability map for mound-like signatures across an area that covers ca. 36,000 km2. The results show that the area presents many more archaeological mounds than previously recorded, extending south and east into the desert, which has major implications for understanding the archaeological significance of the region. The detection of small (<5 ha) to large mounds (>30 ha) suggests that there were continuous shifts in settlement location. These shifts are likely to reflect responses to a dynamic and changing hydrological network and the influence of the progressive northward advance of the desert in a long-term process that culminated in the abandonment of much of the settled area during the Late Harappan period. |
领域 | 地球科学 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/286820 |
专题 | 地球科学 |
推荐引用方式 GB/T 7714 | Hector A. Orengo,Francesc C. Conesa,Arnau Garcia-Molsosa,et al. Automated detection of archaeological mounds using machine-learning classification of multisensor and multitemporal satellite data[J]. Proceedings of the National Academy of Science,2020. |
APA | Hector A. Orengo.,Francesc C. Conesa.,Arnau Garcia-Molsosa.,Agustín Lobo.,Adam S. Green.,...&Cameron A. Petrie.(2020).Automated detection of archaeological mounds using machine-learning classification of multisensor and multitemporal satellite data.Proceedings of the National Academy of Science. |
MLA | Hector A. Orengo,et al."Automated detection of archaeological mounds using machine-learning classification of multisensor and multitemporal satellite data".Proceedings of the National Academy of Science (2020). |
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