Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/18314
Title: Evaluation of Landsat 8 OLI/TIRS level-2 and sentinel 2 level-1C fusion techniques intended for image segmentation of archaeological landscapes and proxies
Authors: Agapiou, Athos 
Major Field of Science: Engineering and Technology
Field Category: Civil Engineering
Keywords: Fusion;Image segmentation;Archaeological landscapes;Archaeological proxies;Landsat 8;Sentinel 2;Object-based image analysis (OBIA)
Issue Date: 1-Feb-2020
Source: Remote Sensing, 2020, vol. 12, no.3, pp. 579
Volume: 12
Issue: 3
Start page: 579
Project: Synergistic Use of Optical and Radar data for cultural heritage applications (PLACES) 
Journal: Remote Sensing 
Abstract: The use of medium resolution, open access, and freely distributed satellite images, such as those of Landsat, is still understudied in the domain of archaeological research, mainly due to restrictions of spatial resolution. This investigation aims to showcase how the synergistic use of Landsat and Sentinel optical sensors can efficiently support archaeological research through object-based image analysis (OBIA), a relatively new scientific trend, as highlighted in the relevant literature, in the domain of remote sensing archaeology. Initially, the fusion of a 30mspatial resolution Landsat 8 OLI/TIRS Level-2 and a 10 m spatial resolution Sentinel 2 Level-1C optical images, over the archaeological site of "Nea Paphos" in Cyprus, are evaluated in order to improve the spatial resolution of the Landsat image. At this step, various known fusion models are implemented and evaluated, namely Gram-Schmidt, Brovey, principal component analysis (PCA), and hue-saturation-value (HSV) algorithms. In addition, all four 10mavailable spectral bands of the Sentinel 2 sensor, namely the blue, green, red, and near-infrared bands (Bands 2 to 4 and Band 8, respectively) were assessed for each of the different fusion models. On the basis of these findings, the next step of the study, focused on the image segmentation process, through the evaluation of different scale factors. The segmentation process is an important step moving from pixel-based to object-based image analysis. The overall results show that the Gram-Schmidt fusion method based on the near-infrared band of the Sentinel 2 (Band 8) at a range of scale factor segmentation to 70 are the optimum parameters for the detection of standing visible monuments, monitoring excavated areas, and detecting buried archaeological remains, without any significant spectral distortion of the original Landsat image. The new 10 m fused Landsat 8 image provides further spatial details of the archaeological site and depicts, through the segmentation process, important details within the landscape under examination.
Description: The author would like to acknowledge the “CUT Open Access Author Fund” for covering the open access publication fees of the paper.
ISSN: 2072-4292
DOI: 10.3390/rs12030579
Rights: © by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license
Type: Article
Affiliation : Cyprus University of Technology 
ERATOSTHENES Centre of Excellence 
Appears in Collections:Publications under the auspices of the EXCELSIOR H2020 Teaming Project/ERATOSTHENES Centre of Excellence

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