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<p>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. <InternalRef RefID="MOESM1">5</InternalRef>–<InternalRef RefID="MOESM1">14</InternalRef>). 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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月7日

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  • Jonti Evan Shepherd,
  • Elad Sagi,
  • Gal Zagron,
  • Eyal Ben-Dor

摘要

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.