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...
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| Format: | Article |
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Taylor & Francis Group
2024-12-01
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| Series: | Geomatics, Natural Hazards & Risk |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/19475705.2024.2409203 |
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| 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 |
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| 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 |
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