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Article

Large-Scale, Multi-Temporal Remote Sensing of Palaeo-River Networks: A Case Study from Northwest India and its Implications for the Indus Civilisation

1
McDonald Institute for Archaeological Research, University of Cambridge, Downing Street, Cambridge CB2 3ER, UK
2
Department of Archaeology and Anthropology, University of Cambridge, Downing Street, Cambridge CB2 3DZ, UK
*
Author to whom correspondence should be addressed.
Academic Editors: Nicola Masini and Prasad S. Thenkabail
Remote Sens. 2017, 9(7), 735; https://doi.org/10.3390/rs9070735
Received: 6 June 2017 / Revised: 6 July 2017 / Accepted: 12 July 2017 / Published: 16 July 2017
Remote sensing has considerable potential to contribute to the identification and reconstruction of lost hydrological systems and networks. Remote sensing-based reconstructions of palaeo-river networks have commonly employed single or limited time-span imagery, which limits their capacity to identify features in complex and varied landscape contexts. This paper presents a seasonal multi-temporal approach to the detection of palaeo-rivers over large areas based on long-term vegetation dynamics and spectral decomposition techniques. Twenty-eight years of Landsat 5 data, a total of 1711 multi-spectral images, have been bulk processed using Google Earth Engine© Code Editor and cloud computing infrastructure. The use of multi-temporal data has allowed us to overcome seasonal cultivation patterns and long-term visibility issues related to recent crop selection, extensive irrigation and land-use patterns. The application of this approach on the Sutlej-Yamuna interfluve (northwest India), a core area for the Bronze Age Indus Civilisation, has enabled the reconstruction of an unsuspectedly complex palaeo-river network comprising more than 8000 km of palaeo-channels. It has also enabled the definition of the morphology of these relict courses, which provides insights into the environmental conditions in which they operated. These new data will contribute to a better understanding of the settlement distribution and environmental settings in which this, often considered riverine, civilisation operated. View Full-Text
Keywords: multi-temporal; seasonal; vegetation; palaeo-river; Indus Civilisation; archaeology multi-temporal; seasonal; vegetation; palaeo-river; Indus Civilisation; archaeology
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MDPI and ACS Style

Orengo, H.A.; Petrie, C.A. Large-Scale, Multi-Temporal Remote Sensing of Palaeo-River Networks: A Case Study from Northwest India and its Implications for the Indus Civilisation. Remote Sens. 2017, 9, 735. https://doi.org/10.3390/rs9070735

AMA Style

Orengo HA, Petrie CA. Large-Scale, Multi-Temporal Remote Sensing of Palaeo-River Networks: A Case Study from Northwest India and its Implications for the Indus Civilisation. Remote Sensing. 2017; 9(7):735. https://doi.org/10.3390/rs9070735

Chicago/Turabian Style

Orengo, Hector A., and Cameron A. Petrie. 2017. "Large-Scale, Multi-Temporal Remote Sensing of Palaeo-River Networks: A Case Study from Northwest India and its Implications for the Indus Civilisation" Remote Sensing 9, no. 7: 735. https://doi.org/10.3390/rs9070735

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