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This article concerns the issue of contactless estimation of the complex electrical permittivity of masonry materials by means of a microwave technique in the frequency domain. The main aim of the study was to develop a method enabling the determination of the real part of relative permittivity and the electrical conductivity of ceramic building materials using microwave reflection measurements, as well as to assess the applicability of the proposed approach for moisture diagnostics in porous media. The research was performed using a reflection-mode measuring setup comprising a vector network analyser and a broadband horn antenna, while measurements were carried out in the frequency range from 1 to 6 GHz on samples of solid ceramic brick with six gravimetric moisture levels. A one-dimensional model of electromagnetic wave propagation in the material was developed, considering complex permittivity, impedance transformation, and a calibration procedure compensating for the influence of the antenna and free-space propagation. Based on the fitting of the magnitude and phase characteristics of the reflection coefficient, the electrical parameters of the tested samples were estimated. The results obtained showed an increase in both permittivity and conductivity with increasing moisture content and revealed very good agreement with the reference values determined using the time-domain method. It can be concluded that the frequency-domain microwave approach may be effectively applied for contactless and non-destructive diagnostics and estimation of the dielectric properties and moisture content in ceramic materials. Full article

(This article belongs to the Section Physical Sensors)

33 pages, 4906 KB

Open AccessArticle

Interval-Based Design Rules for Fixed External Louvers in Glass Curtain Wall Office Buildings for Early-Stage Sustainable Design: A Case Study in Tianjin

by Jiakai Song and Mingyu Zhang

Sustainability 2026, 18(9), 4296; https://doi.org/10.3390/su18094296 (registering DOI) - 26 Apr 2026

Abstract

Fixed external louvers are widely used to improve the environmental performance of glass curtain wall office buildings, yet existing studies more often report preferred solutions than transferable decision ranges for early-stage design. This study develops interval-based design rules for a standard-floor prototype of a point-supported glass curtain wall office building in Tianjin, a representative cold-climate city in China. A seven-variable design space integrating spatial-scale and shading variables was evaluated for 3000 Latin hypercube samples in a Rhino–Grasshopper–Honeybee workflow linked to Radiance and EnergyPlus, using Tianjin’s typical meteorological year data and GB 55015—2021-based office schedules, including an occupant density of 10 m²/person and occupied heating/cooling setpoints of 20/26 °C. Raw-sample statistics, Bootstrap-based stability testing, and surrogate-model-assisted continuous-response analysis were used to identify dominant variables, single-objective preferred intervals, and a neutral equal-weight baseline compromise zone. Under a neutral equal-weight baseline adopted for early-stage comparison, the compromise interval is concentrated around 20–25°, with 15–30° as a practical starting range, while alternative weighting scenarios show directional shifts toward the prioritized objective. Full article

(This article belongs to the Topic Sustainable Built Environment, 2nd Volume)

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32 pages, 6714 KB

Open AccessArticle

Supporting Decision-Making in Cultural Heritage Management Utilizing the Level of Information Need and HBIM: The Case of Bou Inania Madrasa in Meknes, Morocco

by Youssef Hentour, Imane Bennani and Youssef El Ganadi

Buildings 2026, 16(9), 1707; https://doi.org/10.3390/buildings16091707 (registering DOI) - 26 Apr 2026

Abstract

The preservation of cultural heritage presents persistent challenges due to the heterogeneity of methodologies, data structures, and information requirements involved in heritage projects. While conventional Building Information Modeling (BIM) workflows commonly rely on the Level of Development (LOD), heritage contexts require flexible and requirement-driven approaches to manage both geometric and semantic information according to stakeholder needs. To address these challenges, this study adopts a design-oriented approach that investigates the integration of the Level of Information Need (LOIN) within an OpenBIM-based Historic Building Information Modeling (HBIM) framework. The proposed methodology combines a systematic literature review with a practical case study to develop and implement an interoperable workflow articulating HBIM, Level of Information Need (LOIN), Industry Foundation Classes (IFC), and Information Delivery Specification (IDS). Within this framework, LOIN governs the relevance and granularity of information, while IFC and IDS ensure interoperability, data exchange, and conformity checking. The methodology is applied to a Moroccan heritage case study focusing on the documentation and management of building pathologies, including cracks, humidity, capillary rise, and material degradation. The results demonstrate that the proposed approach overcomes the limitations of LOD by enabling requirement-driven information management, thereby improving pathology documentation and supporting informed decision-making for cultural heritage conservation. Full article

(This article belongs to the Section Construction Management, and Computers & Digitization)

28 pages, 713 KB

Open AccessArticle

Unpacking How Anthropomorphic Attribute and Social Presence Foster Consumer Trust and Continued Use of Gen-AI Chatbots: An Integration of AIDUA and Cognitive Appraisal Theory

by Jing Li, Jianglei Wei, Hua Pang and Yungeng Xie

J. Theor. Appl. Electron. Commer. Res. 2026, 21(5), 135; https://doi.org/10.3390/jtaer21050135 (registering DOI) - 26 Apr 2026

Abstract

As Gen-AI shopping chatbots become increasingly prevalent in e-commerce, limited research has examined how consumers’ appraisals of interactive cues shape trust and continued use in privacy-sensitive retail settings. Drawing on Cognitive Appraisal Theory (CAT) and the AIDUA framework, this study investigates how novelty value, anthropomorphic attribute, and social presence influence performance anticipation, effort anticipation, and perceived privacy risk and how these appraisals subsequently shape perceived trust and continued use. Data from 549 experienced users in mainland China were analyzed using partial least squares structural equation modeling (PLS-SEM). The results show that while novelty value enhances performance and effort anticipation, it does not significantly elevate perceived privacy risk. Anthropomorphic attribute positively affects performance anticipation and negatively affects perceived privacy risk, while social presence enhances performance anticipation and effort anticipation and reduces perceived privacy risk. Performance anticipation and effort anticipation positively predict perceived trust, whereas perceived privacy risk negatively predicts perceived trust; perceived trust, in turn, strongly predicts continued use. Mediation analyses further show that cognitive appraisal variables mediate the effects of primary appraisal factors on perceived trust, while perceived trust mediates the effects of cognitive appraisal variables on continued use. Serial mediation results additionally indicate that primary appraisal factors influence continued use through cognitive appraisal and trust formation. These findings deepen understanding of the cognitive and trust-building mechanisms underlying consumer interactions with Gen-AI shopping chatbots and offer practical implications for e-commerce platforms. Full article

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27 pages, 2217 KB

Open AccessArticle

Speech Recognition with an fMRISNN Constrained by Human Functional Brain Networks: A Study of Enhanced MFCC-Driven Sparse Spike Encoding

by Lei Guo, Nancheng Ma, Zhuoxuan Wang and Rumeng Liu

Biomimetics 2026, 11(5), 302; https://doi.org/10.3390/biomimetics11050302 (registering DOI) - 26 Apr 2026

Abstract

Spiking neural networks (SNNs) offer inherent advantages in processing temporal information. However, their network topologies are predominantly algorithm-generated, lacking constraints from biological brain connectivity, which limits their bio-plausibility. In our previous work, we constructed a spiking neural network (SNN) by incorporating the topological structure of functional brain networks derived from fMRI data of healthy subjects and proposed an fMRISNN model. This model was further employed as the reservoir layer of a liquid state machine (LSM) to build a speech recognition framework. In this framework, the Lyon ear model and the BSA were used to encode speech signals into spike sequences; however, this approach suffers from high computational cost and limited adaptability to temporal variations. To address these limitations, we propose an enhanced Mel-frequency cepstral coefficient (MFCC)-driven sparse spike encoding method. For the speech recognition task, we systematically compare the two preprocessing pipelines in terms of spike number, spike sparsity, encoding time, and downstream speech recognition performance. Experimental results show that the proposed method generates substantially fewer spikes, achieves markedly higher sparsity, and requires significantly less encoding time, while maintaining nearly the same recognition accuracy under the same LSM-based framework. These findings indicate that improved speech input representation can enhance the computational efficiency of SNN-based speech recognition without compromising recognition capability. In addition, the fMRISNN model significantly outperforms several baseline models with algorithmically generated topologies. Compared with mainstream models reported in the literature, although the deep convolutional neural network (CNN) still achieves higher absolute recognition accuracy, the fMRISNN exhibits clear advantages in terms of model parameter size and theoretical energy efficiency. Full article

(This article belongs to the Section Biological Optimisation and Management)

25 pages, 8011 KB

Open AccessArticle

Analysis of Steel–Concrete Composite Beam with an Innovative Connector Made of Corrugated Metal Sheet and Shot Nails

by Anna Derlatka and Paweł Kania

Materials 2026, 19(9), 1764; https://doi.org/10.3390/ma19091764 (registering DOI) - 26 Apr 2026

Abstract

This article analyses the possibility of the application of advanced fasteners in the construction of steel–concrete composite beams. The fasteners were made of corrugated metal sheet with a thickness of 1.00 mm, were in a dovetail shape, and had 2 or 4 shot nails in a single sheet fold. The nails were shot through the sheet into the flange of the steel I section. The 7.5 m-long beam was subjected to an experimental bending test. Based on the test results, the load-bearing capacity and failure mode of the beam were identified, enabling an evaluation of the feasibility of employing beams with innovative connectors in the construction of lightweight ceilings. A numerical model of the beam was constructed in ADINA using findings from experimental studies. A concrete material model, which considers both post-cracking and crushing behaviour and which enabled the identification of critical failure zones, was implemented. The beam connectors demonstrated sufficient load-bearing capacity, whereas the concrete slab was identified as the weakest component within the composite beam assembly. The proposed solution can be suitable for use as a fastener in steel–concrete composite ceiling structures in small utility public buildings. In accordance with Eurocode 4 requirements, the floor beam can carry a load of up to 5.7 kN/m². Full article

(This article belongs to the Section Construction and Building Materials)

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26 pages, 5595 KB

Open AccessArticle

A Digital Restoration Method Driven by Mathematical Composition Rules and Their Application: A Case Study of Ming Dynasty Pavilion-Style Stone Pagodas in Fuzhou and the Restoration of the Luoxing Pagoda’s Finial

by Yuanyi Zhang, Lele Zhu, Jinhong Li and Gang Chen

Buildings 2026, 16(9), 1701; https://doi.org/10.3390/buildings16091701 (registering DOI) - 26 Apr 2026

Abstract

In the practice of historic building conservation and restoration, the authentic restoration of damaged components often faces challenges due to the lack of definitive design evidence. To address this issue, this paper proposes a restoration derivation method that integrates digital survey technologies, such as UAV oblique photogrammetry and 3D laser scanning, with the analysis of historical mathematical composition rules. Taking five Ming Dynasty pavilion-style stone pagodas in Fuzhou as subjects, this study first employed digital surveying and cross-verification with ancient texts to reveal their shared, precise proportional system: the eave–column ratio of the Ruiyun Pagoda approaches √2 (≈1.414), while the other four pagodas approach the golden ratio of 1.618. Furthermore, the pagoda silhouettes are governed by a √2 hierarchical system and a √3/2 visual correction mechanism. Based on these mathematical rules, a triple logical chain of “historical evidence verification–functional constraints–traditional adaptation” was constructed and applied to the quantitative restoration design of the damaged finial of the Luoxing Pagoda. This process ultimately derived the relationship between its total height and the first-story width as (L/2 + √2/2), with the finial height being 1/7 of the pagoda body’s total height. This case study validates the effectiveness of the proposed method in transforming profound historical wisdom into clear engineering parameters, offering a replicable and verifiable technical pathway for the digital conservation and scientific restoration of similar architectural heritage. Full article

(This article belongs to the Special Issue Urban Renewal: Protection and Restoration of Existing Buildings)

24 pages, 8716 KB

Open AccessArticle

Effectiveness of Load Reset Control in Simultaneous Heating and Cooling Systems Under WELL Thermal Comfort Criteria

by Dae Uk Shin and Nam-Kyu Park

Sustainability 2026, 18(9), 4290; https://doi.org/10.3390/su18094290 (registering DOI) - 26 Apr 2026

Abstract

The WELL Building Standard (WELL) is a certification system designed to enhance occupant health and well-being in indoor environments. Conventional building energy-saving strategies typically rely on fixed temperature setpoint adjustments, which may conflict with WELL thermal comfort requirements. However, achieving high energy efficiency remains essential. This study uses a quantitative evaluation framework with TRNSYSs to examine the effectiveness of integrating load reset control (LRC) into simultaneous heating and cooling (SHC) systems. It compares LRC with conventional fixed setpoint (SP) and predicted mean vote (PMV) control strategies, based on WELL’s thermal comfort criteria (maintaining the PMV between −0.5 and +0.5). Six simulation cases were analyzed, considering radiant (RAD) and convection (CONV) terminals. The results indicate that radiant terminals provide more stable PMV performance while consuming less energy than convection terminals, demonstrating better compliance with WELL objectives. Although PMV control achieves the highest thermal comfort, it substantially increases energy consumption. In contrast, LRC emerges as an optimal strategy, effectively balancing the energy efficiency of SP control with the comfort of PMV control. The RAD-LRC configuration delivers the best overall performance. It achieves higher thermal comfort than SP, with comparable energy consumption, making it a highly practical approach for modern building energy management. Full article

(This article belongs to the Special Issue Human-Centric Buildings and Communities: Prioritising Comfort, Health, Well-being and Energy Efficiency)

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26 pages, 30235 KB

Open AccessArticle

Multi-Stage Parameter Search for Robot Path Planning in Bottom-Up Vat 3D Printing

by Evan Rolland, Ilian A. Bonev, Evan Jones, Pengpeng Zhang, Cheng Sun and Nanzhu Zhao

Robotics 2026, 15(5), 85; https://doi.org/10.3390/robotics15050085 (registering DOI) - 26 Apr 2026

Abstract

This article presents an approach to extend the capabilities of vat photopolymerization (VPP) 3D printing using a robotic arm, with a focus on robust path planning. The robotic cell consists of a Mecademic Meca500 six-axis robot mounted on a Zaber X-LRQ300AP linear guide. The kinematic chain is inverted to reflect the logic of VPP: the world reference frame is fixed to the robot’s tool (the build plate), while the tool frame is attached to the polymerization zone. A virtual degree of freedom for screen image rotation is introduced, bringing the system to eight degrees of freedom. Inverse kinematics are solved under constraints (pose tolerance, joint limits, collision avoidance, and continuity) and evaluated using multi-criteria metrics: manipulability, normalized joint-limit margin, and positional/angular sensitivity. The algorithm follows a deterministic coarse-to-fine search procedure: discrete sweeping of global part orientations, initial sampling with Halton sequences, abd feasibility filtering on a sparsified trajectory, followed by refinement and multi-criteria ranking. The pipeline successfully discarded infeasible orientations and identified feasible printing trajectories for six of the seven benchmark parts, while the remaining case highlights a limitation that may be addressed in future improvements. Full article

(This article belongs to the Section Industrial Robots and Automation)

30 pages, 2200 KB

Open AccessArticle

A Reliability Analysis Method of the Remote Power Supply System for Grid-like Cabled Underwater Information Networks

by Xichen Wang, Chang Shu, Fangmin Deng, Mingjiu Zuo and Xiaorui Qiao

J. Mar. Sci. Eng. 2026, 14(9), 793; https://doi.org/10.3390/jmse14090793 (registering DOI) - 26 Apr 2026

Abstract

Cabled underwater information networks (CUINs) are a focal point and priority in the field of global marine science and technology. Reliability and economic viability are among the primary constraints on the large-scale deployment of such networks. The remote power supply system for grid-like CUINs is the component with the highest technical risk, exerting a significant impact on both network reliability and economic feasibility. This paper designs and constructs a minimal model and a basic model of a constant-current remote power supply system (CCRPSS) for grid-like CUINs. Through simulation modeling and analysis, the system’s capability to handle faults in a single underwater unit or multiple underwater units in different power supply link segments (PSLSs) is validated, and the impact of underwater unit faults on the system’s operational state is analyzed. Based on this, a descriptive method for determining the power supply reliability (PSR) of observation equipment (OE) is proposed, and the variation patterns of this reliability across different power supply links (PSLs) are derived. Building on this foundation, a constrained engineering design method for the grid-like CCRPSS is proposed. This method aims to deploy a larger number of secondary nodes (SNs) at a lower cost. By integrating constraints including the PSR of OE for each PSL, the open-circuit and short-circuit fault rates of underwater units, and the allowable number of SNs per PSLS, it optimizes the system engineering design problem. This approach yields an optimal solution for the number of longitudinally and transversely deployed SNs as well as the reliability requirements for each underwater unit. Case simulation results validate the descriptive method for the PSR of OE and the variation patterns of such reliability, thereby confirming the feasibility of the constrained engineering design approach. The research findings presented in this paper can provide theoretical references for the reliability analysis, scale design, and long-term planning of CUINs and their remote power supply systems. Full article

(This article belongs to the Section Ocean Engineering)

21 pages, 1777 KB

Open AccessArticle

Issues Concerning the Seismic Design of Essential Mid-Rise MRF Buildings Exhibiting Linear Behavior

by José A. Rodríguez, Sonia E. Ruiz and Francisco J. Armenta

Buildings 2026, 16(9), 1700; https://doi.org/10.3390/buildings16091700 (registering DOI) - 26 Apr 2026

Abstract

This study evaluates the seismic performance and life-cycle economic implications of designing essential urban mid-rise reinforced concrete moment-resistant frame (MRF) buildings to maintain linear elastic behavior up to the Immediate Occupancy (IO) performance level. While most urban buildings are commonly designed to respond non-linearly in order to reduce initial construction costs, the current Mexico City Building Code (MCBC) permits that essential facilities, such as hospitals and schools, maintain linear behavior during moderate-to-strong earthquakes. This code establishes a maximum story drift ratio equal to 0.0075 for essential buildings constituted by MRF subjected to seismic events with a 250-year recurrence interval; in addition, it recommends ductile structural behavior to achieve Life Safety performance at a 450-year recurrence interval. Given the significant differences in occupancy, functionality, and contents of critical facilities, here it is analyzed whether the linear elastic design criterion is efficient for both secondary care hospitals and public schools. Two three-story and five-story MRF buildings, located on firm and transition soil, respectively, are analyzed. This study addresses the probability of brittle-type failure risk, the optimal allowable story drift at the IO performance level, the potential need for use-dependent drift limits, and the contribution of contents and nonstructural components to the total expected seismic losses. The seismic risk and economic performance are quantified through seismic hazard analysis, incremental dynamic analysis, fragility modeling, Monte Carlo simulation, and life-cycle cost evaluation. Full article

(This article belongs to the Special Issue Innovative Approaches for Seismic Performance Analysis and Design in Building Structures)

28 pages, 6628 KB

Open AccessArticle

Unified AI Framework for Decarbonization in Large-Scale Building Energy Systems: Integrating Acoustic-Vision Leak Detection and Schedule-Aware Machine Learning

by Mooyoung Yoo

Buildings 2026, 16(9), 1698; https://doi.org/10.3390/buildings16091698 (registering DOI) - 26 Apr 2026

Abstract

Compressed air systems (CASs) represent a significant portion of energy consumption in large-scale built environments and manufacturing facilities, suffering from both micro-level physical pipeline leaks and macro-level operational inefficiencies. This paper proposes a unified, dual-action artificial intelligence framework aimed at advancing building decarbonization by systematically integrating acoustic-vision leak quantification with schedule-aware machine learning. Specifically, the framework targets pneumatic pipe connection leaks, fitting leaks, and joint degradation faults within compressed air distribution networks, which are the primary sources of micro-level volumetric energy losses in industrial building systems. First, a probabilistic multimodal fusion algorithm (MPSF) using an ultrasonic camera is developed to detect and geometrically quantify physical leaks, successfully translating pixel areas into physical facility energy loss metrics (estimating 11.0 kW of wasted power from detected severe leaks). Second, to optimize the compressor’s supply matching the actual facility demand without risking data leakage from internal flow sensors, an eXtreme Gradient Boosting (XGBoost) model is proposed. By utilizing only external building environmental conditions and the real-time operational schedules of 13 distinct zones, the model achieves highly accurate dynamic power prediction (R² = 0.9698). Finally, comprehensive simulations based on real-world digital monitoring data from a facility-scale built environment demonstrate that only the concurrent application of both modules ensures stable end-point pressure. The integrated framework achieves a substantial system-wide building energy reduction of over 20% to 40% compared to baseline constant-pressure operations, yielding an estimated annual reduction of 116 tons of CO₂ emissions, thereby providing a direct pathway toward carbon-neutral building operations. Full article

(This article belongs to the Special Issue Built Environment and Building Energy for Decarbonization)

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14 pages, 4439 KB

Open AccessArticle

Study on Seismic Collapse Fragility of Corroded Platform Canopies with Different Fortification Intensities in China

by Haibing Liu, Junqi Lin and Jinlong Liu

Appl. Sci. 2026, 16(9), 4228; https://doi.org/10.3390/app16094228 (registering DOI) - 26 Apr 2026

Abstract

Twelve reinforced concrete (RC) railway platform canopies were designed for zones with different seismic fortification intensities (SFIs) in accordance with the Code for Seismic Design of Buildings (2024 Edition) GB/T 50011-2010. Numerical models were created in OpenSees for each structure under three conditions: no corrosion, 5% corrosion loss of reinforcement, and 15% corrosion loss of reinforcement, using the Modified Ibarra–Medina–Krawinkler (ModIMK) hysteretic model. Through IDA, seismic collapse fragility was assessed in accordance with the requirements of the Standard for Anti-collapse Design of Building Structures T/CECS 392-2021. The results are: (1) Double-column canopies strongly resist deterioration from reinforcement corrosion. Each structure with different SFIs meets the code’s collapse probability limit under all three corrosion levels when subjected to the maximum considered earthquake (MCE) and the extreme considered earthquake (ECE, an earthquake larger than MCE). (2) When subjected to MCE, Single-column canopies with different SFIs also meet the code’s collapse probability limit under the three corrosion levels. (3) When subjected to ECE, the collapse probability of single-column canopies with 5% corrosion increases compared to uncorroded structures at SFIs ranging from 6 to 8; for SFIs 8.5 and 9, the collapse probability decreases. The structure with SFI 8.5 has the highest risk and does not comply with the code. (4) When subjected to ECE, the collapse probability of the single-column canopy with 15% corrosion increases significantly compared to uncorroded structures at all SFIs. Structures with SFIs ranging from 7.5 to 9 fail to meet code requirements. This paper systematically investigates the collapse fragility of platform canopies with different seismic fortification intensities in China, examining three corrosion states: no corrosion, 5% corrosion, and 15% corrosion. It provides important guidance for the rational design of platform canopies and for analyzing the impact of corrosion levels on their collapse behavior. Full article

(This article belongs to the Section Civil Engineering)

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21 pages, 1802 KB

Open AccessArticle

Feasibility of Reuse of EPS Insulation from Buildings and Infrastructure

by Malin Sletnes, Arian Loli, Birgit Risholt and Carine Lausselet

Buildings 2026, 16(9), 1693; https://doi.org/10.3390/buildings16091693 (registering DOI) - 25 Apr 2026

Abstract

As demand for energy-efficient buildings grows, the use of expanded polystyrene (EPS) insulation is expected to increase, intensifying the need for material-efficient strategies such as recycling and reuse. This study investigates the technical feasibility, chemical safety, and climate implications of reusing EPS insulation recovered from building and infrastructure applications. EPS boards with service lives exceeding 20 years were collected from demolition sites and characterised for density, compressive strength, thermal conductivity, and hazardous substance content. Measured material properties were compared with historical test reports from 1976 to 2009 to assess long-term performance. The thermal conductivity and compressive strength of the used EPS samples fell within or close to the 95% prediction intervals for the corresponding products at the time of production, indicating limited long-term degradation. No brominated flame retardants or other substances of concern were detected above the detection limits. Life cycle assessment (LCA) results showed that reuse provides greater greenhouse gas (GHG) emission reduction potential than improved recycling alone, primarily through avoided virgin EPS production and reduced processing needs. An important insight from this study is that key material properties of used EPS can be reliably estimated from simple measurements of density, dimensions, and weight, and that direct reuse is feasible for less demanding applications. Additionally, further work is needed to test additional samples from diverse demolition sites across various applications and climates to establish a consistent basis for reuse. Full article

(This article belongs to the Special Issue A Circular Economy Paradigm for Construction Waste Management)

19 pages, 3497 KB

Open AccessArticle

A Python-Based Workflow for Asbestos Roof Mapping and Temporal Monitoring Using Satellite Imagery

by Giuseppe Bonifazi, Alice Aurigemma, José Salas-Cáceres, Javier Lorenzo-Navarro, Silvia Serranti, Federica Paglietti, Sergio Bellagamba and Sergio Malinconico

Geomatics 2026, 6(3), 41; https://doi.org/10.3390/geomatics6030041 (registering DOI) - 25 Apr 2026

Abstract

The detection and monitoring of asbestos–cement roofing remain a critical public health and environmental challenge, especially in urban and suburban areas where asbestos-containing materials are still widespread due to their extensive use in the 20th century. Although hyperspectral and high-resolution multispectral remote sensing have proven effective for mapping asbestos–cement roofs, many existing approaches rely on proprietary software, limiting transparency, reproducibility, and large-scale adoption. This study presents a fully reproducible, cost-free Python-based workflow for the detection and temporal monitoring of asbestos–cement roofing using high-resolution multispectral WorldView-3 imagery. The workflow integrates atmospheric correction (using the Py6S radiative transfer model), spatial preprocessing, supervised pixel-based classification, postprocessing, and building-level aggregation within an open framework. A Maximum Likelihood Classifier is applied to VNIR and SWIR data using empirically defined roof typologies to enhance class separability. Pixel-level results are aggregated to the building scale through adaptive thresholding enabling the translation of spectral classifications into meaningful building-level information. Tested over the city of Mantua (Italy), the approach achieved reliable classification performance and enabled multi-temporal comparison to identify changes potentially due to roof remediation. Evaluation metrics (precision, recall, and F1-score) highlight the importance of carefully choosing the building-level threshold. By relying exclusively on open-source tools, the workflow enhances transparency, reproducibility, and scalability for long-term monitoring. Full article

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