Identifying the main physical and socioeconomic drivers of illegal landfills in the Canary Islands
The management of disposed waste in illegal landfills (ILs) is a significant problem in contemporary societies due to respective hazards for the environment and human health. This paper presents a characterisation of ILs on the islands of La Palma (LP) and Gran Canaria (GC) based on multivariable st...
| Veröffentlicht in: | Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA. - 1991. - 36(2018), 11 vom: 01. Nov., Seite 1049-1060 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2018
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| Zugriff auf das übergeordnete Werk: | Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA |
| Schlagworte: | Journal Article Canary Islands GIS Waste feature selection illegal landfills logistic regression principal component analysis |
| Zusammenfassung: | The management of disposed waste in illegal landfills (ILs) is a significant problem in contemporary societies due to respective hazards for the environment and human health. This paper presents a characterisation of ILs on the islands of La Palma (LP) and Gran Canaria (GC) based on multivariable statistical analysis. Inspection of numerous sites on both islands revealed a total of 153 and 286 ILs on LP and GC, respectively. A geospatial database was created composed of different potentially explanatory features of different typology (177): waste type, control and vigilance, socioeconomic, accessibility, distance to elements of interest, visibility and physical. The degree of association between the explanatory features and the occurrence of ILs was analysed with the support of exploratory statistics and the multivariable analysis techniques of principal component analysis (PCA) and binary logistic regression (LR). PCA explained 82.34% and 81.83% of total data variance in LP and GC, respectively, considering 7 and 6 components (Kaiser-Mayer-Olkin; LP: 0.715; GC: 0.711). The LR models for LP and GC had an overall accuracy of 93.5% and 92.5%. In LP and GC, 6 of 23 features and 9 of 21 features were, respectively, selected. The features most associated with the occurrence of ILs were: in LP, building density, distance to agricultural spaces and distance to green zones; in GC, the industrial activity indicator, density of ground use transition to artificial covers, density of greenhouses and distance to communication routes |
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| Beschreibung: | Date Completed 09.09.2019 Date Revised 09.09.2019 published: Print-Electronic Citation Status MEDLINE |
| ISSN: | 1096-3669 |
| DOI: | 10.1177/0734242X18804031 |