Mapping and Prioritizing Potential Illegal Dump Sites Using Geographic Information System Network Analysis and Multiple Remote Sensing Indices
Due to rapid urbanization and population growth, identification and management of illegal dump sites has been a global challenge. In this study, satellite imagery and geographic information system were used to map potential illegal dump sites (PIDS). An original analytical approach was developed to...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-11-01
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| Series: | Earth |
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| Online Access: | https://www.mdpi.com/2673-4834/3/4/65 |
| _version_ | 1797460380254994432 |
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| author | Nima Karimi Kelvin Tsun Wai Ng |
| author_facet | Nima Karimi Kelvin Tsun Wai Ng |
| author_sort | Nima Karimi |
| collection | DOAJ |
| description | Due to rapid urbanization and population growth, identification and management of illegal dump sites has been a global challenge. In this study, satellite imagery and geographic information system were used to map potential illegal dump sites (PIDS). An original analytical approach was developed to identify PIDS using a set of remote sensing indices and vector files. The Network Analysis tool was used to prioritize PIDS considering driving distance between PIDS and neighboring populated points. A total of five variables (Landfills, LST, HCHO, Highways, and EVI) were considered. A study area in Saskatchewan, Canada, was selected, and the identified PIDS account for about 37.3% of the total area. Road network intensity and accessibility appear important to the occurrence of PIDS. Overall road densities in identified PIDS ranged from 0.098 to 0.251 km/km<sup>2</sup>. All five variables have observable effects on the occurrence of PIDS; however, LST and highways are recommended for future studies due to their higher membership grade and spatial sensitivity. The combination of multiple remote sensing indices and network analysis on PIDS prioritization is advantageous. The proposed PIDS mapping and prioritization method can be easily employed elsewhere. |
| first_indexed | 2024-03-09T17:04:14Z |
| format | Article |
| id | doaj.art-21049677873d4731a6cbf6e1ded162e5 |
| institution | Directory Open Access Journal |
| issn | 2673-4834 |
| language | English |
| last_indexed | 2024-03-09T17:04:14Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Earth |
| spelling | doaj.art-21049677873d4731a6cbf6e1ded162e52023-11-24T14:25:46ZengMDPI AGEarth2673-48342022-11-01341123113710.3390/earth3040065Mapping and Prioritizing Potential Illegal Dump Sites Using Geographic Information System Network Analysis and Multiple Remote Sensing IndicesNima Karimi0Kelvin Tsun Wai Ng1Faculty of Engineering and Applied Science, University of Regina, Regina, SK S4S 0A2, CanadaFaculty of Engineering and Applied Science, University of Regina, Regina, SK S4S 0A2, CanadaDue to rapid urbanization and population growth, identification and management of illegal dump sites has been a global challenge. In this study, satellite imagery and geographic information system were used to map potential illegal dump sites (PIDS). An original analytical approach was developed to identify PIDS using a set of remote sensing indices and vector files. The Network Analysis tool was used to prioritize PIDS considering driving distance between PIDS and neighboring populated points. A total of five variables (Landfills, LST, HCHO, Highways, and EVI) were considered. A study area in Saskatchewan, Canada, was selected, and the identified PIDS account for about 37.3% of the total area. Road network intensity and accessibility appear important to the occurrence of PIDS. Overall road densities in identified PIDS ranged from 0.098 to 0.251 km/km<sup>2</sup>. All five variables have observable effects on the occurrence of PIDS; however, LST and highways are recommended for future studies due to their higher membership grade and spatial sensitivity. The combination of multiple remote sensing indices and network analysis on PIDS prioritization is advantageous. The proposed PIDS mapping and prioritization method can be easily employed elsewhere.https://www.mdpi.com/2673-4834/3/4/65illegal dump sitesremote sensingsatellite imagerygeographic information systemnetwork analysismunicipal solid waste |
| spellingShingle | Nima Karimi Kelvin Tsun Wai Ng Mapping and Prioritizing Potential Illegal Dump Sites Using Geographic Information System Network Analysis and Multiple Remote Sensing Indices Earth illegal dump sites remote sensing satellite imagery geographic information system network analysis municipal solid waste |
| title | Mapping and Prioritizing Potential Illegal Dump Sites Using Geographic Information System Network Analysis and Multiple Remote Sensing Indices |
| title_full | Mapping and Prioritizing Potential Illegal Dump Sites Using Geographic Information System Network Analysis and Multiple Remote Sensing Indices |
| title_fullStr | Mapping and Prioritizing Potential Illegal Dump Sites Using Geographic Information System Network Analysis and Multiple Remote Sensing Indices |
| title_full_unstemmed | Mapping and Prioritizing Potential Illegal Dump Sites Using Geographic Information System Network Analysis and Multiple Remote Sensing Indices |
| title_short | Mapping and Prioritizing Potential Illegal Dump Sites Using Geographic Information System Network Analysis and Multiple Remote Sensing Indices |
| title_sort | mapping and prioritizing potential illegal dump sites using geographic information system network analysis and multiple remote sensing indices |
| topic | illegal dump sites remote sensing satellite imagery geographic information system network analysis municipal solid waste |
| url | https://www.mdpi.com/2673-4834/3/4/65 |
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