Determinants influencing the amount of asbestos-cement roofing in Poland

Wilk, Ewa; Krówczyńska, Małgorzata; Pabjanek, Piotr

doi:10.1515/mgrsd-2015-0014

Cited by 5 publications

(5 citation statements)

References 13 publications

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“…The topic has its relevance from various perspectives: materials can be flammable (wooden, hay) or can be risk factors of 'carcinogenicity' (asbestos). In this study we focus on traditional roofing materials and asbestos (Cilia, C. et al 2015;Wilk, E. et al 2015;Gibril, M.B.A. et al 2016;Krówczyńska, M. et al 2016). Asbestos mapping has a wide literature, and several authors have attempted to identify this dangerous type of roofing.…”

Section: Introductionmentioning

confidence: 99%

Identification of roofing materials with Discriminant Function Analysis and Random Forest classifiers on pan-sharpened WorldView-2 imagery – a comparison

et al. 2018

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Identification of roofing material is an important issue in the urban environment due to hazardous and risky materials. We conducted an analysis with Discriminant Function Analysis (DFA) and Random Forest (RF) on WorldView-2 imagery. We applied a three-and a six-class approach (red tile, brown tile and asbestos; then dividing the data into shadowed and sunny roof parts). Furthermore, we applied pan-sharpening to the image. Our aim was to reveal the efficiency of the classifiers with a different number of classes and the efficiency of pan-sharpening. We found that all classifiers were efficient in roofing material identification with the classes involved, and the overall accuracy was above 85 per cent. The best results were gained by RF, both with three and with six classes; however, quadratic DFA was also successful in the classification of three classes. Usually, linear DFA performed the worst, but only relatively so, given that the result was 85 per cent. Asbestos was identified successfully with all classifiers. The results can be used by local authorities for roof mapping to build registers of buildings at risk.

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Section: Introductionmentioning

confidence: 99%

Identification of roofing materials with Discriminant Function Analysis and Random Forest classifiers on pan-sharpened WorldView-2 imagery – a comparison

et al. 2018

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“…The preliminary results of the research undertaken have indicated that the location of manufacturing plants that used asbestos in production has a significant impact on the estimation of the amount of asbestos-cement products used [32]. Data regarding asbestos manufacturing plants were obtained through surveys, individual interviews and on-site visits [33].…”

Section: Data Processingmentioning

confidence: 99%

Modelling the Spatial Distribution of Asbestos—Cement Products in Poland with the Use of the Random Forest Algorithm

2019

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The unique set of physical and chemical properties of asbestos has led to its many industrial applications worldwide, of which roofing and facades constitute approximately 80% of currently used asbestos-containing products. Since asbestos-containing products are harmful to human health, their use and production have been banned in many countries. To date, no research has been undertaken to estimate the total amount of asbestos-cement products used at the country level in relation to regions or other administrative units. The objective of this paper is to present a possible new solution for developing the spatial distribution of asbestos-cement products used across the country by applying the supervised machine learning algorithm, i.e., Random Forest. Based on the results of a physical inventory taken on asbestos-cement products with the use of aerial imagery, and the application of selected features, considering the socio-economic situation of Poland, i.e., population, buildings, public finance, housing economy and municipal infrastructure, wages, salaries and social security benefits, agricultural census, entities of the national economy, labor market, environment protection, area of built-up surfaces, historical belonging to annexations, and data on asbestos manufacturing plants, best Random Forest models were computed. The selection of important variables was made in the R v.3.1.0 program and supported by the Boruta algorithm. The prediction of the amount of asbestos-cement products used in communes was executed in the randomForest package. An algorithm explaining 75.85% of the variance was subsequently used to prepare the prediction map of the spatial distribution of the amount of asbestos-cement products used in Poland. The total amount was estimated at 710,278,645 m 2 (7.8 million tons). Since the best model used data on built-up surfaces which are available for the whole of Europe, it is worth considering the use of the developed method in other European countries, as well as to assess the environmental risk of asbestos exposure to humans.

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“…state level, or large administrative division unit level) the modelling process was executed during this survey. It has been assumed that the amount of asbestos roofing refers to the building areas, and it depends on the social-economic situation of users, and houses better placed still are not covered with asbestos-containing products (Wilk et al, 2015). Moreover, on the basis of the physical inventory taking, it was concluded that asbestos roofing is still used on the economically underdeveloped areas, where there was a lack of financial resources for the acquisition of new asbestos-free roofing, and in the agricultural areas, where many farm buildings are still covered with asbestos.…”

Section: Introductionmentioning

confidence: 99%

“…Since the preliminary survey on determinants influencing the amount of asbestos-cement roofing in Poland using correlation techniques have shown encouraging results (Wilk et al, 2015), it was decided to use advanced statistical methods. The aim of this work is to estimate the amount of asbestos used in Poland on the basis of social-economic information, land use data, and the proximity of asbestos manufacturing plants.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the amount of asbestos-cement roofing in Poland

et al. 2017

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The unique set of physical and chemical properties has led to many industrial applications of asbestos worldwide; one of them was roof covering. Asbestos is harmful to human health, and therefore its use was legally forbidden. Since in Poland there is no adequate data on the amount of asbestos-cement roofing, the objective of this study was to estimate its quantity on the basis of physical inventory taking with the use of aerial imagery, and the application of selected statistical features. Data pre-processing and analysis was executed in R Statistical Environment v. 3.1.0. Best random forest models were computed; model explaining 72.9% of the variance was subsequently used to prepare the prediction map of the amount of asbestos-cement roofing in Poland. Variables defining the number of farms, number and age of buildings, and regional differences were crucial for the analysis. The total amount of asbestos roofing in Poland was estimated at 738,068,000 m (8.2m t). It is crucial for the landfill development programme, financial resources distribution, and application of monitoring policies.

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Determinants influencing the amount of asbestos-cement roofing in Poland

Cited by 5 publications

References 13 publications

Identification of roofing materials with Discriminant Function Analysis and Random Forest classifiers on pan-sharpened WorldView-2 imagery – a comparison

Identification of roofing materials with Discriminant Function Analysis and Random Forest classifiers on pan-sharpened WorldView-2 imagery – a comparison

Modelling the Spatial Distribution of Asbestos—Cement Products in Poland with the Use of the Random Forest Algorithm

Estimation of the amount of asbestos-cement roofing in Poland

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