21 research outputs found
Pleural mesothelioma in Poland: Spatial analysis of malignant mesothelioma prevalence in the period 1999-2013
Malignant mesothelioma (MM), a rare and very deadly tumour, can be due to asbestos exposure. To better understand the cause of incidence of MM, spatial autocorrelation analysis with reference to the quantity of asbestos-cement products in use and the localisation of former asbestos manufacturing plants was applied. Geostatistical analysis shows that strong spatial clustering of MM incidence (referring to the general population as well as females and males separately) during the period 1999-2013 in the administrative units of Poland (provinces and counties). Incidence hotspots were found to be concentrated primarily in southern Poland but also seen in the county of Szczecin, which stands out in local autocorrelation analysis in north-western Poland. High incidence rates were discovered, in particular with reference to counties around former plants manufacturing asbestos-containing products, mainly asbestos-cement manufacturers. The highest frequency of MM incidence rate was found in within a 55 km radius of plants in or near the towns Trzebinia, Ogrodzieniec and Szczucin in the South, where asbestos-cement products had been manufactured for close to 40 years. Areas with significantly high incidence rates were also discovered in the provinces of Śląskie, Małopolskie and Świętokrzyskie in southern Poland
Simple yet effective: historical proximity variables improve the species distribution models for invasive giant hogweed (Heracleum mantegazzianum s.l.) in Poland
Species distribution models are scarcely applicable to invasive species because of their breaking of the models’ assumptions. So far, few mechanistic, semi-mechanistic or statistical solutions like dispersal constraints or propagule limitation have been applied. We evaluated a novel quasi-semi-mechanistic approach for regional scale models, using historical proximity variables (HPV) representing a state of the population in a given moment in the past. Our aim was to test the effects of addition of HPV sets of different minimal recentness, information capacity and the total number of variables on the quality of the species distribution model for Heracleum mantegazzianum on 116000 km2 in Poland. As environmental predictors, we used fragments of 103 1×1 km, world- wide, free-access rasters from WorldGrids.org. Single and ensemble models were computed using BIOMOD2 package 3.1.47 working in R environment 3.1.0. The addition of HPV improved the quality of single and ensemble models from poor to good and excellent. The quality was the highest for the variants with HPVs based on the distance from the most recent past occurrences. It was mostly affected by the algorithm type, but all HPV traits (minimal recentness, information capacity, model type or the number of the time periods) were significantly important determinants. The addition of HPVs improved the quality of current projections, raising the occurrence probability in regions where the species had occurred before. We conclude that HPV addition enables semi-realistic estimation of the rate of spread and can be applied to the short-term forecasting of invasive or declining species, which also break equal-dispersal probability assumptions
Determinants influencing the amount of asbestos-cement roofing in Poland
Because of its harmfulness to human health, asbestos has been banned in 55 countries, including the EU. In Poland, the use and production of asbestos and asbestos-containing products has been forbidden since 1997. However, there is no precise data about the amount of asbestos-containing products to be eliminated from the territory of Poland. This survey aims to identify characteristics that have a significant impact on the estimation of asbestos-containing products used in Poland. Statistical correlation between the results of the physical inventory count done in 155 municipalities was examined. As a result of the survey it was found that the amount of asbestos-cement roofing depends on the following factors: the number of individual farms in the village, the distance from the asbestos manufacturing plants, the age of the buildings and the economic situation of municipality. The results obtained may contribute to the ability to predict the amount of asbestos-containing products used in other municipalities
An accuracy assessment of European Soil Sealing Dataset (SSL2009): Stara Miłosna area, Poland - a case study
The purpose of the undertaken survey is to assess the accuracy of the SSE2009, based on a reference dataset. The dataset contains 3,600 samples with the same spatial resolution as the final Soil Sealing Layer product and covers a rectangle of 36 km2. The basis for assessing the accuracy was the photointerpretation of the orthophotomap. The overall accuracy with data division into 6 classes amounted to 65%; while divided into 2 classes: sealed and non-sealed reached 95%. The evaluation results accuracy may form the basis for future improvements in evaluation methods impervious surface
Accuracy of the soil sealing enhancement product for Poland
Increasing urbanization results in constant enlarging of the artificial area closed to water infiltration. In
2006–2008, the Soil Sealing Enhancement (SSE) database was the part of the GMES Fast Track Service on Land Monitoring.
The accuracy of the final product set by the authors should reach at least 85%. Orthorectified high resolution aerial
photos of Poland were used to develop reference data constituting 20,000 random samples around the country. In each
sample, the points were classified into three possible surface classes: natural, artificial and semi-sealed. Comparison
of reference data to original project statistics revealed the values of accuracy, commission and omission errors in the
SSE dataset. Although, SSE accuracy in Poland fulfils the criteria set by SSE authors with overall accuracy of 99.5%,
the individual analysis for each category reveals many weaknesses. Preliminary interpretation of mistakes leads to
the conclusion that the spatial resolution of pictures used in the SSE project is insufficient. In several cases, validation
proved that omission errors were made in relation to construction sites or recently constructed buildings. It should be
stated that the accuracy of SSE product for Poland should be treated as the maximum value of impervious surfaces
An accuracy assessment of European Soil Sealing Dataset (SSL2009): Stara Miłosna area, Poland - a case study
the purpose of the undertaken survey is to assess the accuracy of the SSe2009, based on a reference dataset. the dataset contains 3,600 samples with the same spatial resolution as the final Soil Sealing layer product and covers a rectangle of 36 km2. the basis for assessing the accuracy was the photointerpretation of the orthophotomap. the overall accuracy with data division into 6 classes amounted to 65%; while divided into 2 classes: sealed and non-sealed reached 95%. the evaluation results accuracy may form the basis for future improvements in evaluation methods impervious surface
Mapping asbestos-cement roofing with the use of APEX hyperspectral airborne imagery: Karpacz area, Poland – a case study
Asbestos and asbestos containing products are harmful to human health, and therefore its use has been legally forbidden in the EU. Since there is no adequate data on the amount of asbestos-cement roofing in Poland, the objective of this study was to map asbestos-cement roofing with the use of hyperspectral APEX data (288 bands at the spatial resolution of 2.7 m) in the Karpacz area (southwest Poland). A field survey constituted the basis for training and verification polygons in the classification process. A SAM classification method was performed with the following classification results: 62% producer’s accuracy, 73% user’s accuracy and an overall accuracy of 95%. The asbestos-cement roofing for buildings may be discriminated with a high classification accuracy with the use of hyperspectral imagery. The vast majority of the classified buildings were characterised by their small area (i.e. residential type buildings), which reduced the overall accuracy of the classification
Mapping asbestos-cement roofing with the use of APEX hyperspectral airborne imagery: Karpacz area, Poland – a case study
Asbestos and asbestos containing products are harmful to human health, and therefore its use has been legally forbidden in the EU. Since there is no adequate data on the amount of asbestos-cement roofing in Poland, the objective of this study was to map asbestos-cement roofing with the use of hyperspectral APEX data (288 bands at the spatial resolution of 2.7 m) in the Karpacz area (southwest Poland). A field survey constituted the basis for training and verification polygons in the classification process. A SAM classification method was performed with the following classification results: 62% producer’s accuracy, 73% user’s accuracy and an overall accuracy of 95%. The asbestos-cement roofing for buildings may be discriminated with a high classification accuracy with the use of hyperspectral imagery. The vast majority of the classified buildings were characterised by their small area (i.e. residential type buildings), which reduced the overall accuracy of the classification
Accuracy of the Soil Sealing Enhancement Product for Poland
Increasing urbanization results in constant enlarging of the artificial area closed to water infiltration. In 2006–2008, the Soil Sealing Enhancement (SSE) database was the part of the GMES Fast Track Service on Land Monitoring. The accuracy of the final product set by the authors should reach at least 85%. Orthorectified high resolution aerial photos of Poland were used to develop reference data constituting 20,000 random samples around the country. In each sample, the points were classified into three possible surface classes: natural, artificial and semi-sealed. Comparison of reference data to original project statistics revealed the values of accuracy, commission and omission errors in the SSE dataset. Although, SSE accuracy in Poland fulfils the criteria set by SSE authors with overall accuracy of 99.5%, the individual analysis for each category reveals many weaknesses. Preliminary interpretation of mistakes leads to the conclusion that the spatial resolution of pictures used in the SSE project is insufficient. In several cases, validation proved that omission errors were made in relation to construction sites or recently constructed buildings. It should be stated that the accuracy of SSE product for Poland should be treated as the maximum value of impervious surfaces
Replication Data for: Simple yet effective: historical proximity variables improve the species distribution models for invasive giant hogweed (Heracleum mantegazzianum s.l.) in Poland
Species distribution models are scarcely applicable to invasive species because of their breaking of the models’ assumptions. So far, few mechanistic, semi-mechanistic or statistical solutions like dispersal constraints or propagule limitation have been applied. We evaluated a novel quasi-semi-mechanistic approach for regional scale models, using historical proximity variables (HPV) representing a state of the population in a given moment in the past. Our aim was to test the effects of addition of HPV sets of different minimal recentness, information capacity and the total number of variables on the quality of the species distribution model for Heracleum mantegazzianum on 116000 km2 in Poland. As environmental predictors, we used fragments of 103 1×1 km, world- wide, free-access rasters from WorldGrids.org. Single and ensemble models were computed using BIOMOD2 package 3.1.47 working in R environment 3.1.0. The addition of HPV improved the quality of single and ensemble models from poor to good and excellent. The quality was the highest for the variants with HPVs based on the distance form the most recent past occurrences. It was mostly affected by the algorithm type, but all HPV traits (minimal recentness, information capacity, model type or the number of the time periods) were significantly important determinants. The addition of HPVs improved the quality of current projections, raising the occurrence probability in regions where the species had occurred before. We conclude that HPV addition enables semi-realistic estimation of the rate of spread and can be applied to the short-term forecasting of invasive or declining species, which also break equal-dispersal probability assumptions