Detecting small-scale landslides along electrical lines using robust satellite-based techniques

Robust Satellite Technique (RST) was applied to detect small-scale landslides along electrical lines in Sicily, Italy. To this end, electrical poles were selected as targets within the study area. The methodology, implemented in Google Earth Engine (GEE) environment, exploits the Copernicus Sentinel...

Full description

Saved in:
Bibliographic Details
Main Authors: Mohammad Kazemi Garajeh, Annibale Guariglia, Parivash Paridad, Raffaele Santangelo, Valeria Satriano, Valerio Tramutoli
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Geomatics, Natural Hazards & Risk
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/19475705.2024.2409203
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850123750062686208
author Mohammad Kazemi Garajeh
Annibale Guariglia
Parivash Paridad
Raffaele Santangelo
Valeria Satriano
Valerio Tramutoli
author_facet Mohammad Kazemi Garajeh
Annibale Guariglia
Parivash Paridad
Raffaele Santangelo
Valeria Satriano
Valerio Tramutoli
author_sort Mohammad Kazemi Garajeh
collection DOAJ
description Robust Satellite Technique (RST) was applied to detect small-scale landslides along electrical lines in Sicily, Italy. To this end, electrical poles were selected as targets within the study area. The methodology, implemented in Google Earth Engine (GEE) environment, exploits the Copernicus Sentinel-2 platform to identify anomalous land cover variation, in terms of Normalized Difference Vegetation Index (NDVI), possibly related to small displacements affecting electric poles. Since the applied methodology is based on land cover change, dense vegetation plays an important role in detecting small-scale landslides. Therefore, we targeted months with the highest vegetation density, such as February, March, and April from 2016–2023. The results obtained reveal that out of the five targeted electrical poles, four of them exhibited anomalies > 2-sigma indicating significant changes in land cover possibly related to local ground movement as confirmed by aerial photos collected in the period 2015–2023. Our findings reveal anomalies of −2.17 and −2.36 on 7/17/2017 and 9/05/2017 for pole 1. For pole 2, the results show an anomaly of −2.02 on 8/11/2018. The results also indicate anomalies of −4.40 and −2.99 on 7/09/2021 and 9/27/2022 for pole 3. For pole 4, the findings show an anomaly of −3.10 on 1/18/2019.
format Article
id doaj-art-2aedd6b271f24174b1f8f1d6f313bc3f
institution OA Journals
issn 1947-5705
1947-5713
language English
publishDate 2024-12-01
publisher Taylor & Francis Group
record_format Article
series Geomatics, Natural Hazards & Risk
spelling doaj-art-2aedd6b271f24174b1f8f1d6f313bc3f2025-08-20T02:34:32ZengTaylor & Francis GroupGeomatics, Natural Hazards & Risk1947-57051947-57132024-12-0115110.1080/19475705.2024.2409203Detecting small-scale landslides along electrical lines using robust satellite-based techniquesMohammad Kazemi Garajeh0Annibale Guariglia1Parivash Paridad2Raffaele Santangelo3Valeria Satriano4Valerio Tramutoli5Department of Civil, Constructional and Environmental Engineering, Sapienza University of Rome, Rome, ItalyGeocart S.p.A, Potenza, ItalyGeocart S.p.A, Potenza, ItalyGeocart S.p.A, Potenza, ItalySchool of Engineering, Università degli Studi della Basilicata, Potenza, ItalySchool of Engineering, Università degli Studi della Basilicata, Potenza, ItalyRobust Satellite Technique (RST) was applied to detect small-scale landslides along electrical lines in Sicily, Italy. To this end, electrical poles were selected as targets within the study area. The methodology, implemented in Google Earth Engine (GEE) environment, exploits the Copernicus Sentinel-2 platform to identify anomalous land cover variation, in terms of Normalized Difference Vegetation Index (NDVI), possibly related to small displacements affecting electric poles. Since the applied methodology is based on land cover change, dense vegetation plays an important role in detecting small-scale landslides. Therefore, we targeted months with the highest vegetation density, such as February, March, and April from 2016–2023. The results obtained reveal that out of the five targeted electrical poles, four of them exhibited anomalies > 2-sigma indicating significant changes in land cover possibly related to local ground movement as confirmed by aerial photos collected in the period 2015–2023. Our findings reveal anomalies of −2.17 and −2.36 on 7/17/2017 and 9/05/2017 for pole 1. For pole 2, the results show an anomaly of −2.02 on 8/11/2018. The results also indicate anomalies of −4.40 and −2.99 on 7/09/2021 and 9/27/2022 for pole 3. For pole 4, the findings show an anomaly of −3.10 on 1/18/2019.https://www.tandfonline.com/doi/10.1080/19475705.2024.2409203Small-scale landslideelectrical infrastructureRobust satellite technique (RST)Sentinel-2Google Earth Engine (GEE)
spellingShingle Mohammad Kazemi Garajeh
Annibale Guariglia
Parivash Paridad
Raffaele Santangelo
Valeria Satriano
Valerio Tramutoli
Detecting small-scale landslides along electrical lines using robust satellite-based techniques
Geomatics, Natural Hazards & Risk
Small-scale landslide
electrical infrastructure
Robust satellite technique (RST)
Sentinel-2
Google Earth Engine (GEE)
title Detecting small-scale landslides along electrical lines using robust satellite-based techniques
title_full Detecting small-scale landslides along electrical lines using robust satellite-based techniques
title_fullStr Detecting small-scale landslides along electrical lines using robust satellite-based techniques
title_full_unstemmed Detecting small-scale landslides along electrical lines using robust satellite-based techniques
title_short Detecting small-scale landslides along electrical lines using robust satellite-based techniques
title_sort detecting small scale landslides along electrical lines using robust satellite based techniques
topic Small-scale landslide
electrical infrastructure
Robust satellite technique (RST)
Sentinel-2
Google Earth Engine (GEE)
url https://www.tandfonline.com/doi/10.1080/19475705.2024.2409203
work_keys_str_mv AT mohammadkazemigarajeh detectingsmallscalelandslidesalongelectricallinesusingrobustsatellitebasedtechniques
AT annibaleguariglia detectingsmallscalelandslidesalongelectricallinesusingrobustsatellitebasedtechniques
AT parivashparidad detectingsmallscalelandslidesalongelectricallinesusingrobustsatellitebasedtechniques
AT raffaelesantangelo detectingsmallscalelandslidesalongelectricallinesusingrobustsatellitebasedtechniques
AT valeriasatriano detectingsmallscalelandslidesalongelectricallinesusingrobustsatellitebasedtechniques
AT valeriotramutoli detectingsmallscalelandslidesalongelectricallinesusingrobustsatellitebasedtechniques