Large-scale, multi-temporal remote sensing of palaeo-river networks

DOI

JavaScript code to be implemented in Google Earth Engine(c) for large-scale, multi-temporal remote sensing of palaeo-river networks.

This research 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 research presented has been carried out as part of the TwoRains projectt, which is a multi-disciplinary investigation of climate change and the Indus civilization in northwest India.

Identifier
DOI https://doi.org/10.34810/DATA240
Related Identifier IsCitedBy https://doi.org/10.3390/rs9070735
Metadata Access https://dataverse.csuc.cat/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34810/DATA240
Provenance
Creator Orengo Romeu, Hèctor A. ORCID logo
Publisher CORA.Repositori de Dades de Recerca
Contributor Orengo Romeu, Hèctor A.
Publication Year 2022
Funding Reference https://ror.org/00k4n6c32 648609
Rights Condiciones de uso personalizadas para el dataset; info:eu-repo/semantics/openAccess; https://dataverse.csuc.cat/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.34810/data240
OpenAccess true
Contact Orengo Romeu, Hèctor A. (Institut Català d’Arqueologia Clàssica (ICAC))
Representation
Resource Type Program source code; Dataset
Format text/plain; charset=US-ASCII
Size 19027; 19659
Version 1.0
Discipline Ancient Cultures; Archaeology; Humanities