Detection of asbestos-based cement rooftops in conflict-affected settings using EnMAP hyperspectral data: a research article
Abstract In volatile, conflict-affected regions, rapidly mapping asbestos-cement rooftops is critical to mitigate health risks from airborne fibres. Over a 4-month field campaign (Nov 2023–Apr 2024), we partnered with the Israel Space Agency and Ministry of Environmental Protection to acquire distur...
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-09738-w |
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| author | Jonti Evan Shepherd Elad Sagi Gal Zagron Eyal Ben-Dor |
| author_facet | Jonti Evan Shepherd Elad Sagi Gal Zagron Eyal Ben-Dor |
| author_sort | Jonti Evan Shepherd |
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| description | Abstract In volatile, conflict-affected regions, rapidly mapping asbestos-cement rooftops is critical to mitigate health risks from airborne fibres. Over a 4-month field campaign (Nov 2023–Apr 2024), we partnered with the Israel Space Agency and Ministry of Environmental Protection to acquire disturbance-free field spectra at multiple Kibbutzim, Moshavim and cities, using an ASD FieldSpec 4 High-Res with both the SoilPro® apparatus and contact probe to build a comprehensive spectral library (Sup Figs. 5–14). Leveraging EnMAP Level 2A hyperspectral imagery (17 May 2024), we applied MNF noise reduction, precise co-registration, and cloud/shadow masking before executing eight supervised classifiers; Linear Spectral Unmixing, Support Vector Machine, Spectral Angle Mapper, Adaptive Coherence Estimator, Mahalanobis Distance, Maximum Likelihood, Spectral Information Divergence, and Matched Filtering, in an iterative filtering cascade. Exhaustive ground-truth surveys across villages and cities achieved an 86% positive match rate despite urban complexity and security-driven coordinate restrictions. This integrative workflow combining rigorous field calibration, multi-algorithm spectral filtering, and exhaustive validation, demonstrates that orbit-based hyperspectral data can reliably map asbestos hazards at scale, guiding timely emergency response and long-term remediation in high-risk settings. |
| format | Article |
| id | doaj-art-2fc85fdda2c44a359a4cb453b261740c |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
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| spelling | doaj-art-2fc85fdda2c44a359a4cb453b261740c2025-08-20T03:45:59ZengNature PortfolioScientific Reports2045-23222025-07-011511810.1038/s41598-025-09738-wDetection of asbestos-based cement rooftops in conflict-affected settings using EnMAP hyperspectral data: a research articleJonti Evan Shepherd0Elad Sagi1Gal Zagron2Eyal Ben-Dor3The Remote Sensing Laboratory, Porter School of Environment and Earth Science, Faculty of Exact Sciences, Tel Aviv UniversityIsrael Space AgencyMinistry of Environmental ProtectionThe Remote Sensing Laboratory, Porter School of Environment and Earth Science, Faculty of Exact Sciences, Tel Aviv UniversityAbstract In volatile, conflict-affected regions, rapidly mapping asbestos-cement rooftops is critical to mitigate health risks from airborne fibres. Over a 4-month field campaign (Nov 2023–Apr 2024), we partnered with the Israel Space Agency and Ministry of Environmental Protection to acquire disturbance-free field spectra at multiple Kibbutzim, Moshavim and cities, using an ASD FieldSpec 4 High-Res with both the SoilPro® apparatus and contact probe to build a comprehensive spectral library (Sup Figs. 5–14). Leveraging EnMAP Level 2A hyperspectral imagery (17 May 2024), we applied MNF noise reduction, precise co-registration, and cloud/shadow masking before executing eight supervised classifiers; Linear Spectral Unmixing, Support Vector Machine, Spectral Angle Mapper, Adaptive Coherence Estimator, Mahalanobis Distance, Maximum Likelihood, Spectral Information Divergence, and Matched Filtering, in an iterative filtering cascade. Exhaustive ground-truth surveys across villages and cities achieved an 86% positive match rate despite urban complexity and security-driven coordinate restrictions. This integrative workflow combining rigorous field calibration, multi-algorithm spectral filtering, and exhaustive validation, demonstrates that orbit-based hyperspectral data can reliably map asbestos hazards at scale, guiding timely emergency response and long-term remediation in high-risk settings.https://doi.org/10.1038/s41598-025-09738-wAsbestos detectionHyperspectral remote sensingEnMAPSpectral library calibration |
| spellingShingle | Jonti Evan Shepherd Elad Sagi Gal Zagron Eyal Ben-Dor Detection of asbestos-based cement rooftops in conflict-affected settings using EnMAP hyperspectral data: a research article Scientific Reports Asbestos detection Hyperspectral remote sensing EnMAP Spectral library calibration |
| title | Detection of asbestos-based cement rooftops in conflict-affected settings using EnMAP hyperspectral data: a research article |
| title_full | Detection of asbestos-based cement rooftops in conflict-affected settings using EnMAP hyperspectral data: a research article |
| title_fullStr | Detection of asbestos-based cement rooftops in conflict-affected settings using EnMAP hyperspectral data: a research article |
| title_full_unstemmed | Detection of asbestos-based cement rooftops in conflict-affected settings using EnMAP hyperspectral data: a research article |
| title_short | Detection of asbestos-based cement rooftops in conflict-affected settings using EnMAP hyperspectral data: a research article |
| title_sort | detection of asbestos based cement rooftops in conflict affected settings using enmap hyperspectral data a research article |
| topic | Asbestos detection Hyperspectral remote sensing EnMAP Spectral library calibration |
| url | https://doi.org/10.1038/s41598-025-09738-w |
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