Detection of asbestos-based cement rooftops in conflict-affected settings using EnMAP hyperspectral data: a research article

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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Bibliographic Details
Main Authors: Jonti Evan Shepherd, Elad Sagi, Gal Zagron, Eyal Ben-Dor
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Asbestos detection
Hyperspectral remote sensing
EnMAP
Spectral library calibration
Online Access:https://doi.org/10.1038/s41598-025-09738-w
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Summary: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.
ISSN:2045-2322

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