Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/9248
Title: Remote sensing heritage in a petabyte-scale: satellite data and heritage Earth Engine© applications
Authors: Agapiou, Athos 
Major Field of Science: Engineering and Technology
Field Category: Civil Engineering
Keywords: Archaeology;Big data;Cultural heritage;Earth Engine;Orthogonal equations;Remote sensing;Urban sprawl
Issue Date: 2-Jan-2017
Source: International Journal of Digital Earth, 2017, vol. 10, no. 1, pp. 85-102
Volume: 10
Issue: 1
Start page: 85
End page: 102
Project: ATHENA. Remote Sensing Science Center for Cultural Heritage 
Journal: International Journal of Digital Earth 
Abstract: This paper aims to demonstrate results and considerations regarding the use of remote sensing big data for archaeological and Cultural Heritage management large scale applications. For this purpose, the Earth Engine© developed by Google© was exploited. Earth Engine© provides a robust and expandable cloud platform where several freely distributed remote sensing big data, such as Landsat, can be accessed, analysed and visualized. Two different applications are presented here as follows: the first one is based on the evaluation of multi-temporal Landsat series datasets for the detection of buried Neolithic tells (‘magoules’) in the area of Thessaly, in Greece using linear orthogonal equations. The second case exploits European scale multi-temporal DMSP-OLS Night-time Lights Time Series to visualize the impact of urban sprawl in the vicinity of UNESCO World Heritage sites and monuments. Both applications highlight the considerable opportunities that big data can offer to the fields of archaeology and Cultural Heritage, while the studies also demonstrate the great challenges that still are needed to be overcome in order to make the exploitation of big data process manageable and fruitful for future applications.
URI: https://hdl.handle.net/20.500.14279/9248
ISSN: 17538955
DOI: 10.1080/17538947.2016.1250829
Rights: © The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License , which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
Type: Article
Affiliation : Cyprus University of Technology 
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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