Belgium; hyperspectral data; remote sensing; roof materials; spectral library; spectrometry; urban materials; Western Europe; Hyperspectral Data; Remote-sensing; Roof material; Spectra's; Spectral libraries; Spectral range; Spectral signature; Urban materials; Information Systems; Computer Science Applications; Information Systems and Management
Abstract :
[en] The exploitation of urban-material spectral properties is of increasing importance for a broad range of applications, such as urban climate-change modeling and mitigation or specific/dangerous roof-material detection and inventory. A new spectral library dedicated to the detection of roof material was created to reflect the regional diversity of materials employed in Wallonia, Belgium. The Walloon Roof Material (WaRM) spectral library accounts for 26 roof material spectra in the spectral range 350–2500 nm. Spectra were acquired using an ASD FieldSpec3 Hi-Res spectrometer in laboratory conditions, using a spectral sampling interval of 1 nm. The analysis of the spectra shows that spectral signatures are strongly influenced by the color of the roof materials, at least in the VIS spectral range. The SWIR spectral range is in general more relevant to distinguishing the different types of material. Exceptions are the similar properties and very close spectra of several black materials, meaning that their spectral signatures are not sufficiently different to distinguish them from each other. Although building materials can vary regionally due to different available construction materials, the WaRM spectral library can certainly be used for wider applications; Wallonia has always been strongly connected to the surrounding regions and has always encountered climatic conditions similar to all of Northwest Europe. Dataset: https://doi.org/10.5281/zenodo.7414740 Dataset License: CC-BY-ND-SA-1.0
Disciplines :
Earth sciences & physical geography
Author, co-author :
Wyard, Coraline ; Université de Liège - ULiège > Département de géographie > Climatologie et Topoclimatologie ; Remote Sensing and Geodata Unit, Institut Scientifique de Service Public (ISSeP), Liège, Belgium
Marion, Rodolphe ; Commissariat à l’Energie Atomique et aux Énergies Alternatives, CEA/DAM/DIF, Arpajon, France
Hallot, Eric ; Université de Liège - ULiège > Département de géographie ; Remote Sensing and Geodata Unit, Institut Scientifique de Service Public (ISSeP), Liège, Belgium
Language :
English
Title :
WaRM: A Roof Material Spectral Library for Wallonia, Belgium
SPW Agriculture, Ressources naturelles et Environnement - Service Public de Wallonie. Agriculture, Ressources naturelles et Environnement
Funding text :
This research was funded by Service Public de Wallonie—Environnement in the framework of the CASMATTELE project, through the ENVIeS Plan, action I-4-10.
scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.
Bibliography
Hamdi R. Kusaka H. Van Doan Q. Cai P. He H. Luo G. Kuang W. Caluwaerts S. Duchêne F. Van Schaeybroek B. et al. The State-of-the-Art of Urban Climate Change Modeling and Observations Earth Syst. Environ. 2020 4 631 646 10.1007/s41748-020-00193-3
Al Qattan A.A.M. Using Cool Coating for Pavements, Asphalt, Façades and Building Roofs in the Urban Environment to Reduce the Summer Urban Heat Effect in Giza Square, Egypt Innovating Strategies and Solutions for Urban Performance and Regeneration Piselli C. Altan H. Balaban O. Kremer P. Springer International Publishing Cham, Switzerland 2022 117 126 978-3-030-98187-7
Santamouris M. Yun G.Y. Recent Development and Research Priorities on Cool and Super Cool Materials to Mitigate Urban Heat Island Renew. Energy 2020 161 792 807 10.1016/j.renene.2020.07.109
Abriha D. Kovács Z. Ninsawat S. Bertalan L. Balázs B. Szabó S. Identification of Roofing Materials with Discriminant Function Analysis and Random Forest Classifiers on Pan-Sharpened WorldView-2 Imagery—A Comparison Hung. Geogr. Bull. 2018 67 375 392 10.15201/hungeobull.67.4.6
Samsudin S.H. Shafri H.Z.M. Hamedianfar A. Development of Spectral Indices for Roofing Material Condition Status Detection Using Field Spectroscopy and WorldView-3 Data J. Appl. Remote Sens. 2016 10 025021 10.1117/1.JRS.10.025021
Abbasi M. Mostafa S. Vieira A.S. Patorniti N. Stewart R.A. Mapping Roofing with Asbestos-Containing Material by Using Remote Sensing Imagery and Machine Learning-Based Image Classification: A State-of-the-Art Review Sustainability 2022 14 8068 10.3390/su14138068
Wu P.-Y. Mjörnell K. Sandels C. Mangold M. Machine Learning in Hazardous Building Material Management: Research Status and Applications Recent Prog. Mater. 2021 3 17 10.21926/rpm.2102017
Souffer I. Sghiouar M. Sebari I. Zefri Y. Hajji H. Aniba G. Automatic Extraction of Photovoltaic Panels from UAV Imagery with Object-Based Image Analysis and Machine Learning Lecture Notes in Electrical Engineering Volume 745 Springer Singapore 2022 699 709 9789813368927
Banolia C. Deshpande S. Balamuralidhar P. Industrial/Metal Roof Detection from Hyperspectral Image in an Urban Scene Proceedings of the Remote Sensing Technologies and Applications in Urban Environments VII Berlin, Germany 26 October 2022 Chrysoulakis N. Erbertseder T. Zhang Y. 21
Wyard C. Beaumont B. Grippa T. Nys G.-A. Fauvel H. Hallot É. Mapping Roof Materials Using WV3 Imagery and a State-of-the-Art OBIA Processing Chain: Application over Liège, Belgium Proceedings of the ESA Living Planet Symposium 2022 Bonn, Germany 23–27 May 2022
StatBel. Statistique Cadastrale du Parc de Bâtiments, Belgique et Régions, 2022 Available online: https://bestat.statbel.fgov.be/bestat/crosstable.xhtml?view=43d7cdce-3647-4f5c-86f1-a4e0c864f692 (accessed on 9 February 2023)
Beck H.E. Zimmermann N.E. McVicar T.R. Vergopolan N. Berg A. Wood E.F. Present and Future Köppen-Geiger Climate Classification Maps at 1-Km Resolution Sci. Data 2018 5 180214 10.1038/sdata.2018.214
Heiden U. Segl K. Roessner S. Kaufmann H. Determination of Robust Spectral Features for Identification of Urban Surface Materials in Hyperspectral Remote Sensing Data Remote Sens. Environ. 2007 111 537 552 10.1016/j.rse.2007.04.008
Krówczyńska M. Wilk E. Pabjanek P. Kycko M. Hyperspectral Discrimination of Asbestos-cement Roofing Geomat. Environ. Eng. 2017 11 47 10.7494/geom.2017.11.1.47
Le Bris A. Chehata N. Briottet X. Paparoditis N. Spectral Band Selection for Urban Material Classification Using Hyperspectral Libraries Proceedings of the 23. ISPRS Congress, International Society for Photogrammetry and Remote Sensing (ISPRS). INT. Prague, Czech Republic 12–19 July 2016 Volume 3 10.5194/isprs-annals-III-7-33-2016
Long Y. Rivard B. Rogge D. Tian M. Hyperspectral Band Selection Using the N-Dimensional Spectral Solid Angle Method for the Improved Discrimination of Spectrally Similar Targets Int. J. Appl. Earth Obs. Geoinf. 2019 79 35 47 10.1016/j.jag.2019.03.002
Braun A. Warth G. Bachofer F. Hochschild V. Identification of Roof Materials in High-Resolution Multispectral Images for Urban Planning and Monitoring Proceedings of the 2019 Joint Urban Remote Sensing Event (JURSE) Vannes, France 22–24 May 2019 1 4
Wan Z. Ng D. Dozier J. Spectral Emissivity Measurements of Land-Surface Materials and Related Radiative Transfer Simulations Adv. Sp. Res. 1994 14 91 94 10.1016/0273-1177(94)90197-X
Snyder W.C. Wan Z. BRDF Models to Predict Spectral Reflectance and Emissivity in the Thermal Infrared IEEE Trans. Geosci. Remote Sens. 1998 36 214 225 10.1109/36.655331
Herold M. Roberts D.A. Gardner M.E. Dennison P.E. Spectrometry for Urban Area Remote Sensing—Development and Analysis of a Spectral Library from 350 to 2400 Nm Remote Sens. Environ. 2004 91 304 319 10.1016/j.rse.2004.02.013
Kokaly R.F. Clark R.N. Swayze G.A. Livo K.E. Hoefen T.M. Pearson N.C. Wise R.A. Benzel W.M. Lowers H.A. Driscoll R.L. et al. USGS Spectral Library Version 7 U.S. Geological Survey Reston, VA, USA 2017
Baldridge A.M. Hook S.J. Grove C.I. Rivera G. The ASTER Spectral Library Version 2.0 Remote Sens. Environ. 2009 113 711 715 10.1016/j.rse.2008.11.007
Meerdink S.K. Hook S.J. Roberts D.A. Abbott E.A. The Ecostress Spectral Library Version 1.0 Remote Sens. Environ. 2019 230 111196 10.1016/j.rse.2019.05.015
Ben-Dor E. Levin N. Saaroni H. A Spectral Based Recognition of the Urban Environment Using the Visible and Near-Infrared Spectral Region (0.4-1.1 Μm). A Case Study over Tel-Aviv, Israel Int. J. Remote Sens. 2001 22 2193 2218 10.1080/014311601300190677
Heiden U. Roessner S. Segl K. Kaufmann H. Analysis of Spectral Signatures of Urban Surfaces for Their Identification Using Hyperspectral HyMap Data Proceedings of the IEEE/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas (Cat. No.01EX482) Rome, Italy 8–9 November 2001 173 177
Ilehag R. Schenk A. Huang Y. Hinz S. KLUM: An Urban VNIR and SWIR Spectral Library Consisting of Building Materials Remote Sens. 2019 11 2149 10.3390/rs11182149
Sobrino J.A. Oltra-Carrió R. Sòria G. Bianchi R. Paganini M. Impact of Spatial Resolution and Satellite Overpass Time on Evaluation of the Surface Urban Heat Island Effects Remote Sens. Environ. 2012 117 50 56 10.1016/j.rse.2011.04.042
Nasarudin N.E.M. Shafri H.Z.M. Development and Utilization of Urban Spectral Library for Remote Sensing of Urban Environment J. Urban Environ. Eng. 2011 5 44 56 10.4090/juee.2011.v5n1.044056
Kotthaus S. Smith T.E.L. Wooster M.J. Grimmond C.S.B. Derivation of an Urban Materials Spectral Library through Emittance and Reflectance Spectroscopy ISPRS J. Photogramm. Remote Sens. 2014 94 194 212 10.1016/j.isprsjprs.2014.05.005
Zambrano-Prado P. Josa A. Rieradevall J. Pérez-Aragüés F. Marchan J.F. Gassó-Domingo S. Gabarrell X. Laboratory-Based Spectral Data Acquisition of Roof Materials Int. J. Remote Sens. 2020 41 9180 9205 10.1080/01431161.2020.1798548
Kalacska M. Arroyo-Mora J.P. Soffer R.J. Elmer K. ASD FieldSpec3 Field Measurement Protocols Protocols.io 2019 Available online: https://dx.doi.org/10.17504/protocols.io.qu7dwzn (accessed on 20 December 2022)
Soffer R.J. Ifimov G. Arroyo-Mora J.P. Kalacska M. Validation of Airborne Hyperspectral Imagery from Laboratory Panel Characterization to Image Quality Assessment: Implications for an Arctic Peatland Surrogate Simulation Site Can. J. Remote Sens. 2019 45 476 508 10.1080/07038992.2019.1650334
Elmer K. Soffer R.J. Arroyo-Mora J.P. Kalacska M. ASDToolkit: A Novel MATLAB Processing Toolbox for ASD Field Spectroscopy Data Data 2020 5 96 10.3390/data5040096
HSE (Health and Safety Executive) Asbestos: The Analysts’ Guide 2nd ed. TSO (The Stationary Office) Norwich, UK 2021 240p 9780616667079
Similar publications
Sorry the service is unavailable at the moment. Please try again later.
This website uses cookies to improve user experience. Read more
Save & Close
Accept all
Decline all
Show detailsHide details
Cookie declaration
About cookies
Strictly necessary
Performance
Strictly necessary cookies allow core website functionality such as user login and account management. The website cannot be used properly without strictly necessary cookies.
This cookie is used by Cookie-Script.com service to remember visitor cookie consent preferences. It is necessary for Cookie-Script.com cookie banner to work properly.
Performance cookies are used to see how visitors use the website, eg. analytics cookies. Those cookies cannot be used to directly identify a certain visitor.
Used to store the attribution information, the referrer initially used to visit the website
Cookies are small text files that are placed on your computer by websites that you visit. Websites use cookies to help users navigate efficiently and perform certain functions. Cookies that are required for the website to operate properly are allowed to be set without your permission. All other cookies need to be approved before they can be set in the browser.
You can change your consent to cookie usage at any time on our Privacy Policy page.