Large-scale, multi-temporal remote sensing of palaeo-river networks
JavaScript code to be implemented in Google Earth Engine(c) for large-scale, multi-temporal remote sensing of palaeo-river networks.<br/> <br>This research presents a seasonal multi-temporal approach to the detection of palaeo-rivers over large areas based on long-term vegetation dynamic...
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| Formato: | conjunto de datos |
| Fecha de publicación: | 2022 |
| País: | España |
| Recursos: | Consorci de Serveis Universitaris de Catalunya (CSUC) |
| Repositorio: | CORA.Repositori de Dades de Recerca |
| OAI Identifier: | oai:dnet:cora.rdr____::713f512101d491f08a28f9b093a1789f |
| Acesso em linha: | https://doi.org/10.34810/DATA240 |
| Access Level: | acceso abierto |
| Palavra-chave: | Arts and Humanities Computer and Information Science Remote Sensing archaeology palaeo-river Indus Civilisation |
| Resumo: | JavaScript code to be implemented in Google Earth Engine(c) for large-scale, multi-temporal remote sensing of palaeo-river networks.<br/> <br>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.<br/> |
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